experimental theory in psychology

Kolb’s Learning Styles and Experiential Learning Cycle

Saul McLeod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

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David Kolb published his learning styles model in 1984, from which he developed his learning style inventory.

Kolb’s experiential learning theory works on two levels: a four-stage learning cycle and four separate learning styles. Much of Kolb’s theory concerns the learner’s internal cognitive processes.

Kolb states that learning involves the acquisition of abstract concepts that can be applied flexibly in a range of situations. In Kolb’s theory, the impetus for the development of new concepts is provided by new experiences.

“Learning is the process whereby knowledge is created through the transformation of experience” (Kolb, 1984, p. 38).

The Experiential Learning Cycle

Kolb’s experiential learning style theory is typically represented by a four-stage learning cycle in which the learner “touches all the bases”:

The terms “Reflective Cycle” and “Experiential Learning Cycle” are often used interchangeably when referring to this four-stage learning process. The main idea behind both terms is that effective learning occurs through a continuous cycle of experience, reflection, conceptualization, and experimentation.

• Concrete Experience – the learner encounters a concrete experience. This might be a new experience or situation, or a reinterpretation of existing experience in the light of new concepts.
• Reflective Observation of the New Experience – the learner reflects on the new experience in the light of their existing knowledge. Of particular importance are any inconsistencies between experience and understanding.
• Abstract Conceptualization – reflection gives rise to a new idea, or a modification of an existing abstract concept (the person has learned from their experience).
• Active Experimentation – the newly created or modified concepts give rise to experimentation. The learner applies their idea(s) to the world around them to see what happens.

Effective learning is seen when a person progresses through a cycle of four stages: of (1) having a concrete experience followed by (2) observation of and reflection on that experience which leads to (3) the formation of abstract concepts (analysis) and generalizations (conclusions) which are then (4) used to test a hypothesis in future situations, resulting in new experiences.

Kolb (1984) views learning as an integrated process, with each stage mutually supporting and feeding into the next. It is possible to enter the cycle at any stage and follow it through its logical sequence.

However, effective learning only occurs when a learner can execute all four stages of the model. Therefore, no one stage of the cycle is effective as a learning procedure on its own.

The process of going through the cycle results in the formation of increasingly complex and abstract ‘mental models’ of whatever the learner is learning about.

Learning Styles

Kolb’s learning theory (1984) sets out four distinct learning styles, which are based on a four-stage learning cycle (see above). Kolb explains that different people naturally prefer a certain single different learning style.

Various factors influence a person’s preferred style. For example, social environment, educational experiences, or the basic cognitive structure of the individual.

Whatever influences the choice of style, the learning style preference itself is actually the product of two pairs of variables, or two separate “choices” that we make, which Kolb presented as lines of an axis, each with “conflicting” modes at either end.

A typical presentation of Kolb’s two continuums is that the east-west axis is called the Processing Continuum (how we approach a task), and the north-south axis is called the Perception Continuum (our emotional response, or how we think or feel about it).

Kolb believed that we cannot perform both variables on a single axis simultaneously (e.g., think and feel). Our learning style is a product of these two choice decisions.

It’s often easier to see the construction of Kolb’s learning styles in terms of a two-by-two matrix. Each learning style represents a combination of two preferred styles.

The matrix also highlights Kolb’s terminology for the four learning styles; diverging, assimilating, and converging, accommodating:

Knowing a person’s (and your own) learning style enables learning to be orientated according to the preferred method.

That said, everyone responds to and needs the stimulus of all types of learning styles to one extent or another – it’s a matter of using emphasis that fits best with the given situation and a person’s learning style preferences.

Here are brief descriptions of the four Kolb learning styles:

Diverging (feeling and watching – CE/RO)

These people are able to look at things from different perspectives. They are sensitive. They prefer to watch rather than do, tending to gather information and use imagination to solve problems. They are best at viewing concrete situations from several different viewpoints.

Kolb called this style “diverging” because these people perform better in situations that require ideas-generation, for example, brainstorming. People with a diverging learning style have broad cultural interests and like to gather information.

They are interested in people, tend to be imaginative and emotional, and tend to be strong in the arts. People with the diverging style prefer to work in groups, to listen with an open mind and to receive personal feedback.

Assimilating (watching and thinking – AC/RO)

The assimilating learning preference involves a concise, logical approach. Ideas and concepts are more important than people.

These people require good, clear explanations rather than a practical opportunity. They excel at understanding wide-ranging information and organizing it in a clear, logical format.

People with an assimilating learning style are less focused on people and more interested in ideas and abstract concepts.  People with this style are more attracted to logically sound theories than approaches based on practical value.

This learning style is important for effectiveness in information and science careers. In formal learning situations, people with this style prefer readings, lectures, exploring analytical models, and having time to think things through.

Converging (doing and thinking – AC/AE)

People with a converging learning style can solve problems and will use their learning to find solutions to practical issues. They prefer technical tasks, and are less concerned with people and interpersonal aspects.

People with a converging learning style are best at finding practical uses for ideas and theories. They can solve problems and make decisions by finding solutions to questions and problems.

People with a converging learning style are more attracted to technical tasks and problems than social or interpersonal issues. A converging learning style enables specialist and technology abilities.

People with a converging style like to experiment with new ideas, to simulate, and to work with practical applications.

Accommodating (doing and feeling – CE/AE)

The Accommodating learning style is “hands-on,” and relies on intuition rather than logic. These people use other people’s analysis, and prefer to take a practical, experiential approach. They are attracted to new challenges and experiences, and to carrying out plans.

They commonly act on “gut” instinct rather than logical analysis. People with an accommodating learning style will tend to rely on others for information than carry out their own analysis. This learning style is prevalent within the general population.

Educational Implications

Both Kolb’s (1984) learning stages and the cycle could be used by teachers to critically evaluate the learning provision typically available to students, and to develop more appropriate learning opportunities.

Educators should ensure that activities are designed and carried out in ways that offer each learner the chance to engage in the manner that suits them best.

Also, individuals can be helped to learn more effectively by the identification of their lesser preferred learning styles and the strengthening of these through the application of the experiential learning cycle.

Ideally, activities and material should be developed in ways that draw on abilities from each stage of the experiential learning cycle and take the students through the whole process in sequence.

Kolb, D. A. (1976). The Learning Style Inventory: Technical Manual . Boston, MA: McBer.

Kolb, D.A. (1981). Learning styles and disciplinary differences, in: A.W. Chickering (Ed.) The Modern American College (pp. 232–255). San Francisco, LA: Jossey-Bass.

Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development (Vol. 1). Englewood Cliffs, NJ: Prentice-Hall.

Kolb, D. A., & Fry, R. (1975). Toward an applied theory of experiential learning. In C. Cooper (Ed.), Studies of group process (pp. 33–57). New York: Wiley.

Kolb, D. A., Rubin, I. M., & McIntyre, J. M. (1984). Organizational psychology: readings on human behavior in organizations . Englewood Cliffs, NJ: Prentice-Hall.

Further Reading

• How to Write a Psychology Essay
• David Kolb’s Website
• Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning styles: Concepts and evidence. Psychological science in the public interest, 9(3) , 105-119.

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Wilhelm Maximilian Wundt

Wilhelm Maximilian Wundt (1832–1920) is known to posterity as the “father of experimental psychology” and the founder of the first psychology laboratory (Boring 1950: 317, 322, 344–5), [ 1 ] whence he exerted enormous influence on the development of psychology as a discipline, especially in the United States. Reserved and shy in public (cf. Kusch 1995: 249, f.), Wundt aggressively dominated his chosen arenas, the lecture hall and the pages of books, with a witty and sardonic persona (cf., e.g., Wundt 1911a: 61; Boring 1950: 317). His scope was vast, his output incredible. His writings, totaling an estimated 53,000 pages, include: articles on animal and human physiology, poisons, vision, spiritualism, hypnotism, history, and politics; text- and handbooks of “medical physics” and human physiology; encyclopedic tomes on linguistics, logic, ethics, religion, a “system of philosophy;” not to mention his magna opera , the Grundzüge der physiologischen Psychologie and the Völkerpsychologie (in ten volumes). [ 2 ] Although his work spans several disciplines—physiology, psychology, and philosophy—Wundt would not have considered himself an “interdisciplinary” or “pluralistic” thinker: he was to the core a foundationalist, whose great ambition was establishing a philosophico-scientific system of knowledge, practice, and politics (see Section 7 , below) (Boring 1950: 327). Despite his intentions, however, the sheer length of his career (some 65 years) and the volume of his output make it hard to speak of a coherent Wundtian doctrine. [ 3 ] His corpus is riven by tensions and ambiguities, and though his work has undergone periodic scholarly reconsiderations, Wundt’s lasting importance for the field of psychology remains the topic of lively debate among psychologists. [ 4 ]

For philosophers, Wundt is worth studying for two reasons. First, the arguments he made more than a century ago for the legitimacy of a non-reductionist account of consciousness offer both challenges and resources to contemporary psychology and philosophy of mind alike. Should those arguments be found lacking, there remains a second, perhaps more important reason to read him: not understanding Wundt is to tolerate a lacuna at a crucial nexus of the recent history of philosophy. Not only was he a powerful influence (albeit mostly by repulsion) upon the founders of Pragmatism, Phenomenology, and neo-Kantianism, it was also Wundt and his pioneering students who developed the empirical methodologies that first granted psychology a disciplinary identity distinct from philosophy. It is these philosophically germane aspects of his thought that this article describes.

1. Biographical Timeline

2. life & times, 4.1 sensation, 4.2 consciousness, 5. the theoretical framework of experimental psychology, 6. völkerpsychologie, 7.1 psychology in its relation to the sciences, 7.2 psychology and logic, 8. conclusion, wundt: selected publications, wundt’s works in english, secondary sources concerning wundt, related or cited works, other internet resources, related entries.

Wilhelm Maximilian Wundt was born on August 16, 1832, in the German town of Neckarau, outside of Mannheim, the son of a Lutheran minister (Titchener 1921b: 161). The family moved when Wilhelm was six to the town of Heidenheim, in central Baden (Boring 1950: 316). By all accounts, he was a precocious, peculiar boy, schooled mainly by his father’s assistant, the vicar, Friedrich Müller; young Wilhelm was so attached to Müller that he moved in with him when the latter got a post in a neighboring village (Boring 1950: 316). Wundt studied at the Gymnasien at Bruchsal and Heidelberg and entered the University of Tübingen at 19, in 1851 (Boring 1950: 317). After one year he transferred to the University of Heidelberg, where he majored in medicine. By his third year, his intense work ethic yielded his first publication (Boring 1950: 318). Nevertheless, doctoring was not Wundt’s vocation and he turned instead to physiology, which he studied for a semester under Johannes Müller (the “father of experimental physiology”) at Berlin (Boring 1950: 318). In 1856, at the age of 24, Wundt took his doctorate in medicine at Heidelberg, and habilitated as a Dozent in physiology. Two years later, the physicist, physiologist, and psychologist, Hermann von Helmholtz, [ 6 ] received the call to Heidelberg as a professor of physiology, a decisive moment for Wundt’s career, with Wundt working as Helmholtz’s assistant from 1858 until 1865 (Boring 1950: 300, 319; Araujo 2014: 55).

When Helmholtz moved to Berlin in 1871, Wundt was passed over as Helmholtz’s replacement; three years later he took the chair in “inductive philosophy” at the University of Zürich. He remained at Zürich for only one year before receiving an appointment to “a first-class chair of philosophy at Leipzig in 1875” (Ben-David and Collins 1966: 462). Leipzig’s philosophy department, dominated by Herbartians, provided the ideal environment for his intellectual flowering, the soil having been prepared by Fechner, Weber, and Lotze (Littman 1979: 74; cf. Kim 2009). Wundt became famous at Leipzig. It was here, in 1879, that the university formally recognized his little room of equipment as a bona fide laboratory, the world’s first devoted to psychology. [ 7 ] Students flocked to Wundt, [ 8 ] and while he set the tone and direction of research, it was largely they who constructed apparatus, performed experiments, and published results.

Enrollment in his courses doubled about every 15 years, reaching a peak of 620 students in the summer of 1912. Wundt ended up sponsoring 186 Ph.D. dissertations, about a third of which apparently involved purely philosophical topics (Tinker, 1932). (Quote—including reference to Tinker–from Hearst 1979b: 22)

Though Wundt participated actively in labor politics in his early years at Heidelberg, even being elected to the Baden parliament, he steadily drifted rightwards, eventually being persuaded by his “virulently anti-Semitic” [ 9 ] son, Max, a historian of philosophy, to join the ultranationalist Deutsche Philosophische Gesellschaft , after 1917. [ 10 ] It is hard to ignore Wundt’s unattractive “application” of his late social and cultural psychology to the tendentious critique of Germany’s enemies (Kusch 1995: 220–1). Nevertheless, his drive and unflagging intellectual advocacy will arouse admiration in some: even at age 80, he remained involved in academic controversy. [ 11 ] But let us consider the man through his work.

To understand Wundt’s philosophical importance one must know something of his intellectual context. Early nineteenth-century German psychology labored under the looming shadow of Kant and his arguments that a science of psychology is in principle impossible. This fact by itself illustrates the oddity of the situation, from our point of view: why would a psychologist care what a philosopher thought about his practice? The answer is that since ancient times, psychology had been a basic part of philosophical speculation, though after Kant’s criticisms many considered it a dying branch, dangerously close to breaking off. Psychologists were philosophers on the defensive (cf. L III: 163).

Psychology, as a part of philosophy, had already several times changed the way it defined its object: as “soul”, “mental substance”, “mind”, etc. By the late eighteenth and early nineteenth centuries, many regarded psychology to be the account of consciousness or “inner experience”, distinct from the natural scientific accounts of external, sensible reality. After having dealt the coup de grâce to the speculative, rational, a priori psychology of the soul epitomized by Christian Wolff, however, Kant tried to cut off any retreat into the empirical study of consciousness, as well. In the Metaphysical Foundations of Natural Science , he argued that empirical psychology cannot be an exact science because the phenomena it seeks to explain are not mathematically expressible (Kitcher 1990: 11). Moreover, it can never become an experimental science “because it is not possible to isolate different thoughts” (Kitcher 1990: 11). Finally, and most fatally, the only access to the phenomena of inner experience, introspection, ipso facto alters those phenomena: if I try, by introspection, to study what it’s like to be tristful, the phenomena of my sadness are now something different, namely, phenomena of my sadness-being-studied-by-me (Kitcher 1990: 11). Thus psychologists found their object declared beyond the limit of possible investigation and their methods vain. While such arguments did not persuade all of Kant’s successors of the hopelessness of their enterprise, their attempts were unpromising. On the one hand, the German Idealists’ fanciful speculation about Geist collapsed upon itself. On the other hand, the efforts of J.F. Herbart to devise a mathematical mental mechanics suggested a possible way forward although in the end it proved equally fruitless. Thus, for those mid-nineteenth-century enthusiasts of mental phenomena, the future of a genuine psychology seemed blocked.

At the same time, however, progress was being made in human physiology, especially of the sensory systems. In 1834, the physiologist, E.H. Weber, published a startling discovery in his De tactu . His experiments on the sensation of weight had led him to find that there obtains a constant ratio between, on the one hand, a given stimulus and, on the other hand, a second stimulus sufficiently larger for the difference between the two stimuli to be just noticeable, no matter the magnitude of the first stimulus. [ 12 ] In other words, if the first stimulus is of intensity \(I\), then \(\Delta I\) is the amount by which it must be increased for the difference to be just noticeable; the ratio of \(I\) and \(\Delta I\) is constant (\(k\)): \(\Delta I / I = k\) (cf. L III: 186). This equation, which later came to be known as Weber’s Law, [ 13 ] was crucial to the development of psychology because it apparently demonstrated that where Herbart had failed in his aprioristic construction of mathematical regularities of mind, experimentation could succeed. The situation nevertheless remained murky as interpretations of Weber’s Law multiplied. Fechner, for example, elaborated Weber’s experiments but took his results as the basis for an arcane panpsychic monism (Wundt’s own “psychological” interpretation is treated in Section 4 ) (cf., e.g., Boring 1950: 286).

In founding the experimental science of psychology, Wundt in effect “triangulated” a media via between the available options: he rejected Fechner’s mysticism while maintaining his experimental approach; at the same time, Wundt went beyond the purely physical interpretation of physiological experiments à la Helmholtz, arguing that at least in humans experimentation could reveal law-like regularities of inner (psychological) reality. Thus, to use the phrase of Ben-David and Collins, he established the “hybrid science” whose dual provenance is expressed in Wundt’s name for it, “physiological psychology” (Ben-David and Collins 1966: 459; Kusch 1995: 122, ff.). [ 14 ] Wundt’s interest, both to scholars of the history of philosophy and to contemporary philosophers of mind, flows ultimately from the definition, methodology, and “metaphysics” of this physiological psychology. Sections 3 and 4 are devoted to a description of its definition, method, and doctrine, while Section 5 is concerned with its theoretical underpinnings. The practical and theoretical limits of experimental psychology will be treated in Section 6 , on Völkerpsychologie .

3. Experimental psychology: object and method

“The exact description of consciousness [ Bewusstsein ] is the sole aim of experimental psychology” (cited by Titchener 1921b: 164). Wundt identifies “physiological” with “experimental” psychology. [ 15 ] Thus, for Wundt, experimental psychology is the unmediated study of consciousness, aided by the experimental protocols of the natural sciences. Yet this definition involves two contestable assumptions: first, that “consciousness” is susceptible to experiment (rejected by Kant); second, that psychology, even if conceived as experimental, has for its object consciousness or “the mental” (later rejected by the Behaviorists) (cf. Hearst 1979b: 10). Let us focus on the first assumption, since it is one Wundt addresses.

Wundt defines consciousness as “inner experience;” it is only the “immediately real” [ 16 ] phenomena constituting this experience, and nothing behind or beyond it, that is the object of psychological , as opposed to physiological or psychophysical investigation ( PP II: 636). Wundt’s project is not only a “psychology without a soul”, in F.A. Lange’s phrase, but also a science without a substrate tout court . [ 17 ] Wundt therefore presents himself as a radical empiricist. The subject of psychology “is itself determined wholly and exclusively by its predicates”, and these predicates derive solely from direct, internal observation (on which below). The basic domain of inquiry, accordingly, is that of “individual psychology” (cf. e.g. L III: 160, ff), i.e. of the concrete mental contents appearing to particular human beings, and not some mental substance or bundle of faculties. [ 18 ] In Wundt’s declaration that individual psychology must become a science via the experimental manipulation of inner phenomena, we see a pragmatic attitude perhaps peculiar to the working scientist: the future science as doctrine takes shape in and through the present practice of experimentation, its essays, assays, trials, and errors. Instead of simply submitting to Kant’s injunctions against the very possibility of a scientific psychology, Wundt finds that certain aspects of our inner experience can be, and in fact have been, made susceptible to experiment and mathematical representation: Weber and Fechner did this.

Nevertheless, Wundt repeatedly addresses the objections raised against the very possibility of psychological, as opposed to physiological or psychophysical, experimentation. How are we to subject the mind-body complex to physiological stimulation such that the reactions may be given a purely psychological interpretation? From the physiological point of view, experimentation with stimulus and response are not experiments of sensation, but of externally observable excitations and reactions of nerve and muscle tissue. For example, a nerve fiber or a skin surface may be given an electric shock or brought into contact with acid, and twitches of muscle fiber are observed to follow. It is obvious, especially when the nerve-tissue in question belongs to a dead frog (Wundt describes such an experiment in PP ), that these experiments say nothing about the “inner” experience or consciousness of sensation. Wundt’s innovation is the attempt to project the experimental rigor of physiology into the domain of inner experience by supplementing these experiments with a purely psychological set of procedures. These procedures constitute Wundt’s well-known yet misunderstood method of Selbstbeobachtung , i.e. “introspection” or, better, “self-observation”.

Because “inner” distinguishes itself from “external” experience by virtue of its immediacy, all psychology must begin with self-observation, so that physiological experiment is given an ancillary function (Boring 1950: 320–21). Now Wundt is well aware of the common criticism that self-observation seems inescapably to involve the paradoxical identity (described in the previous section) of the observing subject and observed object. Indeed, he takes pains to distinguish his notion of self-observation from that of “most advocates of the so-called empirical psychology”, which he calls “a fount of self-delusions [ Selbsttäuschungen ]”:

Since in this case the observing subject coincides with the observed object, it is obvious that the direction of attention upon these phenomena alters them. Now since our consciousness has less room for many simultaneous activities the more intense these activities are, the alteration in question as a rule consists in this: the phenomena that one wishes to observe are altogether suppressed [i.e., by the activity of focused attention upon them]. ( L III: 162)

Wundt believes that one can experimentally correct for this problem by

using, as much as possible, unexpected processes, processes not intentionally adduced, but rather such as involuntarily present themselves [ sich darbieten ]. ( L III: 162) [ 19 ]

In other words, it is in the controlled conditions of a laboratory that one can, by means of experimenter, experimental subject, and various apparatus, arbitrarily and repeatedly call forth precisely predetermined phenomena of consciousness. The psychologist is not then interested in the psychophysical connections between the somatic or nervous sense-mechanisms and the elicited “inner” phenomena, but solely in describing, “and where possible measuring”, the psychological regularities that such experiments can reveal, viz., regular causal links within the domain of the psychic alone ( L III: 165). According to Wundt, psychological experiments thus conceived accomplish in the realm of consciousness precisely what natural-scientific experiments do in nature: they do not leave consciousness to itself, but force it to answer the experimenter’s questions, by placing it under regulated conditions. Only in this way is

a [psychological] observation [as opposed to a mere perception { Wahrnehmung }] at all possible in the scientific sense, i.e., the attentive, regulated pursuit of the phenomena. ( L III: 165) [ 20 ]

A detailed account of these experiments themselves, however, lies far beyond the scope of this article. [ 21 ]

4. Wundt’s “individual psychology”

Wundt, like most early experimental psychologists, [ 22 ] concentrated his investigations upon sensation and perception; of all psychic phenomena, sensation is the most obviously connected to the body and the physical world (Hearst 1979b: 33). For Wundt, sensations and our somatic sensory apparatus are especially important for the project of physiological psychology for the simple reason that sensations are the “contact points” between the physical and the psychological ( PP I: 1). Sensations ( Empfindungen ), as the medium between the physical and psychic, are uniquely susceptible to a double-sided inquiry, [ 23 ] viz. from the “external” physical side of stimulus, and the “internal” psychological side of corresponding mental representation ( Vorstellung ). [ 24 ] The Wundtian psychologist therefore controls the external, physiological side experimentally, in order to generate diverse internal representations that can only “appear” to the introspective observer. According to Wundt, the representations ( Vorstellungen ) that constitute the contents ( Inhalt ) of consciousness all have their elemental basis in sensations ( Empfindungen ) ( PP I: 281). [ 25 ] Sensations are never given to us as elemental, however; we never apperceive them “purely”, but always already “combined” ( verbunden ) in the representation of a synthesized perception ( PP I: 281). Yet, the manifestly composite nature of our representations forces us to abstract such elementary components ( PP I: 281) (cf. PP II: 256). Pure sensations, according to Wundt, display three differentiae: quality, intensity, and “feeling-tone” ( Gefühlston ) ( PP I: 282–3). [ 26 ]

His treatment of quality and intensity are especially important for getting a clearer notion of his notion of psychological experimentation. It is a “fact of inner experience” that “every sensation possesses a certain intensity with respect to which it may be compared to other sensations, especially those of similar quality” ( PP I: 332). The outer sensory stimuli may be measured by physical methods, whereas psychology is given the corresponding

task of determining to what degree our immediate estimation [ Schätzung ] [of the strength of sensory stimuli] that we make aided by our sensations—to what degree this estimation corresponds to or deviates from the stimuli’s real strength. ( PP I: 332–3)

There are two possible tasks for psychophysical measurement of sense-stimuli: the “determination of limit-values between which stimulus-changes are accompanied by changes in sensation”; and “the investigation of the lawful relations between stimulus-change and change in sensation” ( PP I: 333). Sensation can thus be measured with respect to changes in intensity corresponding to changes in strength of stimuli ( PP I: 335–6).

Weber’s Law (WL) is the most striking example of such a relation, and Wundt’s interpretation of WL sheds much light on what he means by “physiological psychology”. Wundt writes:

We can formulate [this law] as follows: A difference between any two stimuli is estimated [ geschätzt ] to be equal if the relationship between the stimuli is equal. Or: If in our apprehension [ Auffassung ] the intensity of the sensation is to increase by equal amounts, then the relative stimulus-increase must remain constant. This latter statement may also be expressed as follows: The strength of a stimulus must increase geometrically if the strength of the apperceived sensation is to increase arithmetically. ( PP I: 359)

Now these various formulations [ 27 ] of WL admit, as Wundt says, of three different, and indeed incompatible interpretations; that is, there are three different conceptions of what WL is a law of . First, the physiological interpretation takes it as a manifestation of the “peculiar laws of excitation of the neural matter;” [ 28 ] second, the psychophysical (Fechnerian) interpretation takes WL as governing the interrelation between somatic and psychic activity ( PP I: 392). Wundt rejects both of these in favor of a third, the psychological interpretation; his arguments are instructive. Against the physiological interpretation Wundt raises the following main point, viz. that

the estimation of the intensity of sensation ( Empfindungsintensität ) is a complicated process, upon which—in addition to the central sensory excitation—the effectiveness of the center of apperception will exert considerable influence. We can obviously say nothing immediate about how the central sense-excitations would be sensed independently of the latter; thus Weber’s Law, too, concerns only apperceived sensations, and therefore can just as well have its basis in the processes of the apperceptive comparison of sensation as in the original constitution of the central sensory excitations. ( PP I: 391–2)

Now apperception (see below) is a purely psychological act in consciousness—and it is solely as a law of the psychological processes involved in the “measuring comparison of sensations” that Wundt understands WL ( PP I: 393). In other words, WL

does not apply to sensations in and for themselves, but to processes of apperception, without which a quantitative estimation of sensations could never take place. ( PP I: 393; cf. PP II: 269)

Wundt sees WL as simply a mathematical description of the more general experience that

we possess in our consciousness no absolute, but merely a relative measure of the intensity of the conditions [ Zustände ] obtaining in it, and that we therefore measure in each case one condition against another, with which we are obliged in the first place to compare it. ( PP I: 393)

For this reason Wundt’s “psychological interpretation” makes WL into a special case of a more general law of consciousness, viz. “of the relation or relativity of our inner conditions [ Zustände ]” ( PP I: 393). WL is therefore not a law of sensation so much as of apperception.

This solution typifies Wundt’s general view that the domains of psychic and physical phenomena do not stand in conflict, but rather constitute separate spheres of (causal) explanation. His interpretation of WL nicely illustrates how, on his view, physiological experiments can yield mathematically expressible results, not about the physical, somatic processes involved in sensation, but about the relationships among these sensations as apperceived , i.e., as psychological elements and objects of consciousness. He writes that “the psychological interpretation offers the advantage of not excluding a simultaneous [i.e. parallel] physiological explanation” (presumably once the neurophysiological facts of the matter have been better elucidated — cf. PP I: 391); by contrast, the two competing interpretations “only permit a one-sided explanation” of WL ( PP I: 393).

Psychology finds consciousness to be constituted of three major act-categories: representation, willing, and feeling; our discussion is limited to the first two. Now while Wundt is forced to speak of representations and representational acts as distinct, he is nevertheless clear that they are merely different aspects of a single flowing process. This is his so-called theory of actuality ( Aktualitätstheorie ) (1911a: 145). Representations are representational acts , never the “objects with constant properties” propounded by adherents of a so-called theory of substantiality ( Substantialitätstheorie ) (1911a: 145). This identity of representation and representational act typifies what we may call Wundt’s “monistic perspectivism”. [ 29 ] Everywhere he insists that the “psychic processes form a unitary flow of events [ einheitliches Geschehen [ 30 ] ]”, the constituents of which—“representing, feeling, willing, etc.”—are “only differentiated through psychological analysis and abstraction” (1911a: 145). Keeping in mind the underlying active unity of the psychic, let us examine some of Wundt’s “analyses and abstractions”.

As discussed in the previous section, all consciousness originates in sensations. These, however, are never given to consciousness in a “pure” state as individual sensory atoms, but are always perceived as already compounded [ 31 ] into representations ( Vorstellungen ), that is, into “images of an object or of a process in the external world” ( PP II: 3; 1). Representations may be either perceptions ( Wahrnehmungen ) or intuitions ( Anschauungen ): the same representation is called a “perception” if considered as the presentation of objective reality, and an “intuition” if considered in terms of the accompanying conscious, subjective activity ( PP II: 1). If the representation’s object is not real (cf. PP II: 479) but merely thought, then it is a so-called reproduced representation. [ 32 ]

Now the formative process , by which sensations are connected into representations either through temporal sequencing or spatial ordering ( PP II: 3), constitutes a main aspect of the activity we call consciousness; the other is the “coming and going of [these] representations” ( PP II: 256). On the evidence of “innumerable psychological facts”, [ 33 ] Wundt claims that all representations are formed through “psychological synthesis of sensations”, and that this synthesis accompanies every representational act ( PP II: 256). We are therefore entitled to take the act of representational synthesis as a “characteristic feature of consciousness itself” ( PP II: 256). Although consciousness consists in the formation of representations, on the one hand, and of the coming and going of such representations, on the other hand—i.e., although its contents are a continuous streaming of fusing and diffusing representations—yet it is not merely this ( PP II: 256). We are also aware within our consciousness of another activity operating upon our representations, namely of paying them attention ( PP II: 266).

Attention may be understood in terms of the differing degrees to which representations are present ( gegenwärtig ) in consciousness. These varying degrees of presence correspond to the varying degrees to which consciousness is “turned towards [ zugewandt ]” them ( PP II: 267). Wundt appeals to an analogy:

This feature of consciousness can be clarified by that common image we use in calling consciousness an inner vision. If we say that the representations present [ gegenwärtig ] at a particular moment are in consciousness’s field of vision [ Blickfeld ], then that part of the field upon which our attention is turned may be called the inner focal point of vision [ Blickpunkt ]. The entry of a representation into the field of inner vision we call “perception”, and its entry into the focal point of vision we call “apperception”. ( PP II: 267)

Thus consciousness is a function of the scope of attention, which may be broader (as perception) or narrower (as apperception [ 34 ] ). Apperception, in turn, may either actively select and focus upon a perceived representation, or it may passively find certain representations suddenly thrusting themselves into the center of attention ( PP II: 267; 562). There is no distinct boundary between the perceived and the apperceived, and Wundt’s analogy may be misleading (cf. esp. PP II: 268) to the extent that it gives the impression of two separable forms of attention able in principle to subsist together simultaneously (that is, apperception focusing upon a point in the perceptual field while that field continues to be perceived). No: perceptive attention becomes apperceptive attention just as it focuses more strenuously, constricting the perceptive field. The more it contracts, the “brighter” the representation appears, now becoming the focal point of apperception as the fringes of the perceptual field retreat into “darkness” ( PP II: 268). For Wundt, the distinguishing feature of the apperceptive focus is that it “always forms a unitary representation”, so that a narrower focal point (or rather, the focal “field” [ PP II: 268; 477]) results in a correspondingly higher intensity of attention ( PP II: 269). Hence

the degree of apperception is not to be measured according to the strength of the external impression [i.e. physically or physiologically], but solely according to the subjective activity through which consciousness turns to a particular sense-stimulus. ( PP II: 269)

Thus, apperception [ 35 ] is closely akin to the will, indeed is a primordial expression of will: “the act of apperception in every case consists in an inner act of will [ Willenshandlung ]” ( L I: 34). By contrast, Wundt argues that the processes by which the representations are themselves formed, fused, synthesized, and “delivered” into the perceptual field, are associative processes “independent of apperception” ( PP II: 278–9; 437, ff). Passive apperception may be characterized simply by saying that here the associative form of representational connection is predominant (cf. L I: 34), whereas when “the active apperception successively raises representations into the focal field of consciousness”, this active passage of representations obeys the special laws of what Wundt calls “apperceptive connection” ( PP II: 279). He does not consider the types of association to be genuine psychological laws, i.e. laws governing the “succession of representations”, because they merely generate the possible kinds of representational compounds. It is apperception, in accordance with its own laws, that “decides” which of these possible connections are realized in consciousness ( L I: 34). We see here the important role played by his so-called voluntarism: [ 36 ] associationist psychologists, according to Wundt, cannot give an account of the (subjective) activity that immediately characterizes consciousness (cf. Wundt 1911b: 721, ff.; Lipps 1903: 202, ff.; cf. esp. L I: 33). Yet this is not to deny association of sensations altogether. Rather, it is to conceive of association as merely a subliminal process, the products of which, representations, then become the actual objects of consciousness. Thus the “apperceptive connections of representations presuppose the various types of association”, especially the associative fusion [ 37 ] of sensations into representations. [ 38 ]

Apperception operates according to its own peculiar laws ( PP II: 470). These laws, like those of association, govern acts of combination ( Verbindung ) and separation ( Zerlegung ). How do apperceptive laws differ from those of association? Wundt writes:

Association everywhere gives the first impetus to [apperceptive] combinations. Through association we combine, e.g., the representations of a tower and of a church. [ 39 ] But no matter how familiar the coexistence of these representations may be, mere association does not help us form the representation of a church-tower. For this latter representation does not contain the two constitutive representations in a merely external coexistence; rather, in the [representation of the church-tower], the representation of the church has come to adhere [ anhaften ] to the representation of the tower, more closely determining the latter. In this way, the agglutination of representations forms the first level of apperceptive combination. ( PP II: 476; on “agglutination of representations”, see also L I: 38, f.)

It is on the basis of such “agglutinative” representations, exhibiting characteristics essentially different from their constituents, that apperception continues to synthesize ever more representations, a process resulting in their compression ( Verdichtung ) or displacement ( Verschiebung ) ( PP II: 476–7; cf. L I: 43). The more the original associative or agglutinated representations are compressed or displaced, the more they disappear altogether from consciousness, leaving in their stead a single representation whose original composite structure has disappeared. This process, which Wundt calls “representational synthesis” proper, is reiterated at ever higher levels until even the sensory foundation vanishes, as in the case of abstract and symbolic concepts ( L I: 39).

Apperception is not only a synthetic process; it is also governed by rules of separation. Apperceptive separation operates only upon the representations already synthesized out of the “associative stock [ Assoziationsvorrath ]”, but does not necessarily decompose them into their original parts ( PP II: 478). Wundt’s notion of apperceptive separation is one of the most philosophically original, consequential, and ambiguous of his theories. He argues that it is usually the case that

the original representational totality [ ursprüngliche Gesammtvorstellung ] is present to our consciousness at first as an indistinct complex of individual representations. These individual parts and the manner of their connection become distinct only through the separative activity of apperception. ( PP II: 478)

Thus, conscious thought and judgment (on judgment, see SP I: 34, ff., esp. 37, ff.) (separating and combining subject and predicate) is not, as may seem at first blush, an act of

gathering together [representational] components and then fitting them together in the successive articulation of the total representation [ Gesammtvorstellung ]. ( PP II: 478)

Rather, “the whole, albeit in an indistinct form, must have been apperceived prior to its parts” ( PP II: 478). Only in this way can one explain the

well-known fact that we can easily and without trouble finish [composing] a complicated sentence-structure. This would be impossible if the whole had not been represented at the outset. The accomplishment of the judgment-function therefore consists, from the psychological point of view, only in our successively making clearer the obscure outlines of the total picture [ Gesammtbild ], so that at the end of the composite thought-act the whole, too, stands more clearly before our consciousness. ( PP II: 478)

Because according to Wundt’s principle of “actuality [ Aktualität ]” consciousness is purely an activity, it is impossible to render his theory in terms of “structures”. It consists in constantly interacting processes : on the one hand, there are associative processes that fuse sensations into elemental representations. These stream into and thereby constitute a fluctuating field of attention: flowing and broad, it is called “perception;” ebbing and concentrate, “apperception”. As an activity, attention is an expression of will; since consciousness just is attention in its shifting forms, it is the activity of will manifested in the selection, combination, and separation of disposable representations ( PP II: 564). These representations are constantly “worked over” by apperception, which through its synthetic and diaeretic activity constructs them into ever “higher developmental forms of consciousness”, such that in the end their origins in sensation and perception might be completely erased. In other words, as the apperceptive activity becomes increasingly intense it seems as it were to rise above the field of perception, above the field of its own constructs, becoming aware of itself as pure activity, as pure self -consciousness:

rooted in the constant activity [ Wirksamkeit ] of apperception, [self-consciousness] … retreats completely into apperception alone, so that, after the completion of the development of consciousness, the will appears as the only content of self-consciousness…. ( PP II: 564) [ 40 ]

Thus the self as will appears to itself as independent from and opposed to an external world of both sensation and culture, though Wundt hastens to add that this is but an illusion; in reality, “the abstract self-consciousness maintains constantly the full sensible background of the empirical self-consciousness” ( PP II: 564). [ 41 ]

As we have seen ( Section 3.2 ), for Wundt the possibility of a physiological psychology (as opposed to a purely physiological inquiry into sensation, behavior, learning, etc.) depends on the possibility of self-observation. Self-observation, in turn, is of scientific use only if the sequence of “inner” phenomena of consciousness is assumed to fall under an independent principle of psychic causality. For if it does not, then these phenomena could never be more than a chaotic muddle, of which there could be no science. Alternatively, if the “inner” phenomena could be shown to fall under the physical causality of the natural sciences, then there would be no need for a special psychological method, such as self-observation (cf. Natorp 1912). In fact, however, a system of psychic causality can be determined, Wundt argues, one that at no point is reducible to physical causality: “no connection of physical processes can ever teach us anything about the manner of connection between psychological elements” (Wundt 1894: 43, quoted in Kusch 1995: 134). This “fact”, which Wundt thinks is given in the psycho-physiological experiments described above, leads him to his so-called principle of psychophysical parallelism (PPP).

The PPP has caused a great deal of confusion in the secondary literature, which persists in characterizing it as a metaphysical [ 42 ] doctrine somehow derived from Leibniz (e.g., Wellek 1967: 350; Thompson and Robinson 1979: 412) or Spinoza (cf. L I: 77). Wundt however is crystal-clear that the PPP is not a metaphysical “hypothesis”. It is merely an admittedly misleading name for an “empirical postulate” necessary to explain the phenomenal “fact” of consciousness of which we are immediately aware (Wundt 1911a: 22; cf. esp. 28). By denying any metaphysical interpretation of his principle, Wundt insists that the “physical” and the “psychic” do not name two ontologically distinct realms whose events unfold on separate yet parallel causal tracks. He is therefore not an epiphenomenalist, as some commentators have claimed. Rather, the “physical” and “psychic” name two mutually irreducible perspectives from which one and the same world or Being ( Sein ) may be observed: “nothing occurs in our consciousness that does not find its sensible foundation in certain physical processes”, he writes, and all psychological acts (association, apperception, willing) “are accompanied by physiological nerve-actions” ( PP II: 644). In distinguishing the empirical from the metaphysical PPP, Wundt contrasts his own view against Spinoza’s, which, according to Wundt, makes the realm of material substance exist separately from, though parallel to that of mental substance (Wundt 1911a: 22, 44–5; cf. esp. Wundt 1911a: 143, ff.).

The investigator of psychological phenomena, therefore, must assume, solely for heuristic reasons, two “parallel” and irreducible causal chains by which two distinct types of phenomena may be accounted for (Wundt 1911a: 143; cf. Van Rappard 1979: 109). Wundt compares the distinction between psychological and physiological explanation to the different viewpoints taken by chemistry and physics of the same object, a crystal. The chemical and physical accounts are not of two different entities; rather, they describe and explain the same entity from two distinct points of view, and in this sense the two accounts are “parallel”. Similarly, (neuro-) physiology and psychology do not describe different processes, one neural and one mental, but the same process seen from the outside and the inside, respectively. As Wundt writes,

“inner” and “outer” experience merely designate distinct perspectives that we can apply in our grasp and scientific investigation of what is, in itself, a unitary experience. (Wundt 1896a; quoted at Natorp 1912: 264).

Whereas experimental psychology focuses in the first place on the effects of the physical (outer) upon the psychic (inner), the willing consciousness is characterized by intervening in the external world, that is, by expressing the internal ( PP I: 2). This latter feature of consciousness lies beyond the scope of experiment, because the origins of conscious expression cannot be controlled. Moreover, psychological development is obviously not determined merely by sensation, but also by the meaningful influences of the individual’s “spiritual [ geistig ] environment”—his culture—influences again not obviously susceptible to experimentation. [ 43 ] Hence, just as Wundt reserved for physiology an ancillary role in experimental psychology, so too he now argues for the utility of a distinct methodological approach to analyze and explain the

psychic processes that are bound, in virtue of their genetic and developmental conditions, to spiritual communities [ geistige Gemeinschaften ]. ( L III: 224)

It is the inquiry into “cultural products [ Erzeugnisse ]” of the “totality of spiritual life [ geistiges Gesammtleben ] in which certain psychological laws have embodied themselves”, specifically, language, art, myth, and customs ( Sitten ) ( PP I: 5; L III: 230). These objects cannot be investigated in the same way as those of individual “inner” experience, but require a mode of explanation appropriate to their external, yet non-physical phenomenology. This inquiry, which complements and together with experimental psychology completes the discipline of psychology, Wundt calls “ Völkerpsychologie ” (hereafter abbreviated: VP ) ( L III: 225). [ 44 ]

While Wundt had already discussed the role of a VP necessary for the completion of psychology in his early writings, it was not until old age that he committed himself to its realization. The result was his ten-volume work, entitled Völkerpsychologie . While an examination of the contents of these tomes lies beyond the scope of this article, his justification and clarification of the völkerpsychologisch project as such are of interest for those interested in truth and method in the social and human sciences. Wundt stresses that although VP shares object-domains with such sciences as history, philology, linguistics, [ 45 ] ethnology, [ 46 ] or anthropology ( L III: 226), yet it is only interested in these domains insofar as they “are determined by general psychological laws, and not just by historical conditions” ( PP I: 5). In other words, VP is not interested in the unique and specific facts of this nation’s history or that tribe’s language as such, but only insofar as these reveal “the general psychological developments that arise from the connection of individual [developments]” ( L III: 226). This quotation is important. While VP does not concern itself with historical or linguistic facts as such, this does not mean that it is not concerned with individuality. Indeed, it is through the study of the psychological motives only apparent in history or language—i.e., in communal existence—that our understanding of the individual is completed (cf. L III: 224, 228). This view is typical of Wundt’s perspectivism. Just as psychology is an alternative perspective to that of physiology, so too ( within psychology) VP provides an alternative perspective to that of experimental psychology. Wundt considers none of these various perspectives dispensable, since each one is a complement necessary for total science. But while each of these perspectives reveals a (phenomenologically) irreducible (“parallel”) network of causal chains, the process so explained, Wundt holds, is in every case one and the same. There is just one empirical world and reality, but many irreducible varieties of experience. Thus, in the case of VP , too, he claims that there is no “general law of spiritual events [ geistiges Geschehen ] that is not already completely contained in the laws of the individual consciousness” ( L III: 225).

7. The order of knowledge

As we have seen, Wundt was concerned not only with expanding the set of known psychological facts, but also with interpreting them within an appropriate explanatory framework. Of course, the necessity of establishing such a closed framework distinct from physiology amounted to distinguishing psychological causality from physical causality in general, and hence psychology from the natural sciences altogether. But psychology has to be defined against two other areas of “scientific” ( wissenschaftlich ) inquiry; first, in its völkerpsychologisch dimension, against the Geisteswissenschaften or “human sciences”, and second, against the non-psychological domains of philosophy. As these relationships are laid out below, it must always be remembered that although these four areas—psychology, philosophy, natural science, human science—are irreducible, this irreducibility is not a metaphysical or ontological one, but merely one of explanatory function (and commensurate methodology). They do not have distinct objects, but again merely represent ways of describing irreducible perspectives upon the same object, namely experience. Wundt writes:

Objects of science do not in and of themselves yield starting points for a classification of the sciences. Rather, it is only regarding the concepts that these objects call for that we can undertake this classification. Therefore, the same object [ Gegenstand ] can become the object [ Objekt ] of several sciences: geometry, epistemology, and psychology each deals with space, but space is approached in each discipline from a different angle. … The tasks of the sciences are therefore never determined by the objects in themselves, but are predominantly dependent upon the logical points of view from which they are considered. ( SP I: 12–3; cf. L III: 228)

Wundt’s monism has serious consequences for the sort of claim philosophy (and thus psychology) can make to be scientific. The most obvious is that neither can lay claim to synthetic knowledge that is not founded in or (also) describable in terms of the natural or human sciences.

For Wundt, it is only the sciences that have methodologies by which to synthesize our representations, sensible as well as “processed”, into “facts” or “pieces of” knowledge ( Erkenntnisse ). Hence, while strictly speaking he is committed to considering psychology (i.e., physiological psychology and VP ) a part of philosophy, he usually speaks of them as distinct enterprises. This is because psychology is hybrid, adapting scientific methodologies to its particular aims; in this sense psychology, although part of philosophy, synthesizes facts, just like the sciences. [ 47 ] By contrast, philosophy’s pure task is universal, operating over all scientific domains; it is, he writes, “the general science whose task it is to unify the general pieces of knowledge yielded by the particular sciences into a system free of contradiction” ( SP I: 9). Philosophy’s positive role, therefore, is not to provide the foundations of science, nor can it ever “step into the role of a particular science” (cf. Kusch 1995: 129); rather it is “to take in every case the already secured results of those sciences as its foundation”, and organize them into a single, overarching system by determining their points of connection ( PP I: 8; 6). Wundt calls this side of philosophy Prinzipienlehre or “doctrine of principles”. By contrast, its negative or critical role is to regulate the sciences in accord with the imperative of consistent systematicity. In short, it has no constitutive but merely a regulative role vis-à-vis the sciences. Thus, when we return to the philosophical as opposed to the scientific aspect of psychology’s hybrid structure, we see that this aspect consists in its aim (as opposed to its method) of explaining rules of genesis, connection, and separation of those mental representations with an epistemic character. Wundt calls this psychological contribution to philosophy Erkenntnislehre or “doctrine of knowledge” (i.e., the theory of the coming-to-be of knowledge). This explanation then provides to philosophy the scientific foundation for its pure task. [ 48 ]

Wundt divides up the sciences into two large families, the “formal” sciences and the “real” sciences. The former include mathematics; the latter study the natural and spiritual aspects of reality, [ 49 ] and correspondingly are divided into the natural and the human sciences. The human sciences in turn are divided into two genera, one of which deals with spiritual processes ( geistige Vorgänge ), the other with spiritual products ( geistige Erzeugnisse ). The former just is the science of psychology; the latter includes the general study of these products as such (e.g., philology, political science, law, religion, etc.), as well as the parallel historical study of these products as they have in fact been created (This taxonomy is given in SP I: 19–20). Since the process precedes the product (cf. Kusch 1995: 132), psychology as “the doctrine of spiritual [ geistig ] processes as such” is the foundation of all the other human sciences ( SP I: 20). [ 50 ] Philosophy, in turn, takes psychology ’s results and again abstracts from them the normative rules governing the organization of the human and natural sciences, something the latter cannot do themselves. In this way psychology as a science mediates between the sciences and philosophy.

One aspect of Wundt’s hierarchy of method and knowledge deserves special attention, namely the place of logic in the sciences. Like almost all the similarly titled tomes produced by the German mandarins, Wundt’s Logik (in two, later three 600-page volumes in four editions) molders away in research libraries. Its contents are for the most part unrecognizable as “logic” in any contemporary sense. What most philosophers meant by “ Logik ” in Wundt’s day was the rules and procedure of inference governing the sciences, where this often included lengthy treatments of the actual scientific application of these rules. What we would expect to find in a book called “ Logik ” today, viz., symbolic or mathematical logic, was called at that time “ Logistik ”, and was considered by some a mathematical (that is, merely formal) game unworthy of philosophy’s scientific (that is, substantive) role (cf., e.g., Natorp 1910: 4–10). Thus we should not be surprised to read Wundt, too, declare logic’s task to be the justifying and accounting for “those laws of thinking active in scientific knowledge” ( L I: 1).

For Wundt, however, this task involves psychology, and indeed much of his Logik is devoted to this topic. As he reasonably points out, logic comprises the rules of correct thinking, and the principles of logic are known to us as conscious representations ( L I: 76; 13; cf. Wundt 1920: 267); thinking and consciousness are objects of psychological inquiry; therefore any account of logic must include a psychological description of the genesis of logical principles ( L I: 13). Even the normative character of logic had, in his view, to be given a psychological interpretation (cf. L I: 76). Inevitably Wundt was accused of logical psychologism —the all-purpose term of abuse flung about in fin-de-siècle German philosophical debate. Husserl, for example, condemned him for expounding an “extreme” form of psychologism (Husserl 1901: 124–5; cf. Farber 1943: 123, 208, ff.; cf. Wundt 1910b: 511, ff.), viz. “species-relativism”, the notion that “truth varies with different species” of animal (Kusch 1995: 49). Yet Wundt himself calls his Logik the “most rigorous rejection of the psychologism that reigned at the time [i.e., 1880]” (Wundt 1920: 264), and held that “logical thinking is universally binding for every thinker” (Wundt 1920: 266). How can we reconcile these statements?

Wundt’s view of logic is unusual, but fully in line with his rigorously anti-metaphysical monistic perspectivism. That is, there is no logical “third realm”, but merely a single process called “thinking [ Denken ]” ( L I: 6); it is an immediately given fact of thinking that there are logical laws that stand over against all our other thoughts and representations as norms ( L I: 76). Their psychological immediacy does not, Wundt thinks, compromise their normativity, since what is given in consciousness precisely is their normative character. [ 51 ] Once this character is taken for granted, the science of logic develops its systems of correct deductions ( Schliessen ) without further worry about the source of that normativity. All that remains is “develop[ing] the foundations and methods of scientific knowledge” ( L I: 8).

According to Wundt, the three features of logical thinking that set it apart from all other types of representational connection are its “spontaneity, evidence, and universal validity [ Spontaneität, Evidenz, Allgemeingültigkeit ]” ( L I: 76). Let us briefly describe these. Wundt’s notion of the spontaneity of logical thinking is perhaps the most psychologistic-sounding of the three. Because, as was described above, thinking is

experienced immediately as an inner activity, … we must regard it as an act of will [ Willenshandlung ], and accordingly regard the logical laws of thought [ Denkgesetze ] as laws of the will. ( L I: 76–7)

In other words, logical thinking is accompanied essentially by a feeling of the thinking subject’s freedom in thinking. But while logical thinking may be accompanied by an especially strong self-awareness of the mind’s own activity, this feeling is not unique to logical thinking, since active apperception more generally is also accompanied by the sense of subjective activity. By contrast, logical evidence and universal validity are characteristics possessed by logical thinking “to a higher degree than by any other psychic function” ( L I: 78). By “evidence”, Wundt means the character of compelling necessity accompanying a logical judgment, what we might call self-evidence ( L I: 78, 79). A thought ( Gedanke ) may exhibit immediate certainty, obvious without any mediating thought-acts; or a thought may be mediately certain, grounded in prior thought-acts. Immediate and mediate evidence have their source and foundation in intuition ( Anschauung ): immediate evidence immediately, mediate evidence mediately ( L I: 82–3). Intuition is not identical with evidence, for evidence only

comes to be at the moment when logical thinking relates the contents of intuition and presupposes the relations of such intuitive contents as objectively given. ( L I: 83)

Wundt thus charts a middle course between, on the one hand, making logical evidence a “transcendent or transcendental” function of thinking (as Kant and “recent speculative philosophy” are alleged to do), and, on the other hand, considering it an “empirical trait of sensible objects” (as do empiricists and positivists) ( L I: 83).

By the standards of such philosophers as Husserl, Natorp, and Frege, Wundt appears committed to a logical psychologism. But it is worth considering his response to this charge, for it again illustrates his monistic perspectivism. While he rejects any interpretation of the origin of logical principles that would impugn their normative character of necessity, he also rejects the opposite extreme, what he calls “ Logizismus ”—the complete divorce of logical thinking from thinking as it actually occurs in minds. For Wundt, the logicist makes a metaphysical leap as suspect as it is unnecessary in conjuring up a “pure”, “absolute”, “transcendental”, but in any case separate source of logical normativity (cf. Wundt 1910b: 515). Instead of solving the puzzle of logical normativity, he exacerbates it by adding the puzzles of the ontological status of a third realm, or of a transcendental ego, or of “pure thinking”, and the influence of all of these on your thinking as you read this. Wundt finds a simpler solution in his perspectivism. The logical may be considered “purely” from a logical point of view, i.e., in terms of its normative character, or “genetically” from a psychological point of view. But there are no logical laws that are not also describable psychologically, just as there is no psychological phenomenon not also describable physiologically. But being “describable” in this sense is not the same as being explicable , and it is this separate task of explanation that falls to logic and psychology, respectively. The logical description saves the phenomenon of normativity, just as the psychological description saves the phenomenon of the interiority of consciousness.

Wundt’s conception of psychology was always controversial. At least in Germany, the struggle over the status and philosophical meaning of “consciousness” resulted, on the one hand, in the exclusion of Wundtian empiricism from philosophy departments, striving to maintain their speculative purity, and, on the other, the institutional establishment of experimental psychology as an independent discipline. This was not the outcome Wundt had desired. He had wished to reform philosophy , not as a synthetic science, but with a direct, indispensable, juridical relation vis-à-vis both the natural and human sciences. He never saw his psychological scientism as a threat to philosophy—on the contrary, he considered his psychology to be a part of philosophy (cf. Boring 1950: 325), one necessary for philosophy to take its proper place in the totality of the sciences. Indeed, philosophy could only assume that position through the mediating position of psychology ( PP I: 3). Yet academic philosophers, denied the possibility of any legislative or executive functions in the sciences, rejected the juridical ones as well, bitterly resisting contamination of their pure pursuit by the empiricism of the new psychology. In Germany, resistance was especially stiff among neo-Kantians, and later the Phenomenologists. In the end, the quarreling parties ineluctably assumed positions similar to their opponents’—though of course in a “purified” way. [ 52 ]

Let us return to James’s mean remark [ 53 ] about Wundt: he has no noeud vital , no central idea, and so this would-be Napoleon-planarian can never be “killed all at once”. Setting aside Wundt’s need to be killed at once or in bits, a fair and attentive reader will respectfully reject such scintillating criticisms. For although Wundt has many ideas—“the theory of actuality”, the “principle of psychophysical parallelism”, “voluntarism”, “creative resultants”, etc., etc.—yet they all do have a single unifying node, namely what I have here called “monistic perspectivism”. If Wundt has a big idea, it is that Being is a single flow of Becoming with many sides and many ways of being described. Consequently we , as part of this Being, have many ways of describing and explaining it. Few have as unblinkingly accepted the consequences of their starting points, or more doggedly pursued them to their various ends as Wundt.

Boring 1950 has an excellent annotated bibliography (344, ff.). Wundt’s entire oeuvre was compiled by his daughter, Eleonore Wundt (1927; cf. esp. Wong 2009: 230–3). An excellent select bibliography organized by theme has been compiled by S. Araujo for Oxford Bibliographies (subscription required). It includes volumes on Wundt’s correspondence, his estate, international library collections and archives, and his global influence.

• Araujo, S.F., 2003, “A obra inicial de Wundt: Um capitulo esquecido nahistoriografia da psicologia”, Revista do Departamento de Psicologia da UFF , 15(2): 63–76.
• –––, 2012, “Why Did Wundt Abandon His Early Theory of the Unconscious?”, History of Psychology , 15(1): 33–49.
• –––, 2014a, “Bringing New Archival Sources to Wundt Scholarship: The case of Wundt’s assistantship with Helmholtz”, History of Psychology , 17(1): 50–9.
• –––, 2014b, “The emergence and development of Bekhterev’s psychoreflexology in relation to Wundt`s experimental psychology”, Journal of the History of the Behavioral Sciences , 50(2): 189–210.
• –––, 2016, Wundt and the Philosophical Foundations of Psychology: A Reappraisal , Cham: Springer.
• –––, 2019, “ Völkerpsychologie as cultural psychology: The place of culture in Wundt’s psychological program”, in Jovanović, et al.: 75–84.
• –––, 2021, “A useful and reliable guide to Wundt’s entire work”, History of Psychology , 24(2): 188–9.
• Ash, M.G., 1980, “Academic politics in the history of science: experimental psychology in Germany, 1879–1941”, Central European History , 13(3): 255–86.
• Binder, N., 2016, Subjekte im Experiment: Zu Wilhelm Wundts Programm einer objektiven Psychologie , Frankfurt: Peter Lang.
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How to cite this entry . Preview the PDF version of this entry at the Friends of the SEP Society . Look up topics and thinkers related to this entry at the Internet Philosophy Ontology Project (InPhO). Enhanced bibliography for this entry at PhilPapers , with links to its database.

• Mind, Brain, and the Experimental Psychology of Consciousness , an excerpt of pp. 39–44 of Mind and body: René Descartes to William James , by Robert H. Wozniak, National Library of Medicine (U.S.), American Psychological Association, 1992. The full work is available online .

Herbart, Johann Friedrich | introspection | mental imagery | panpsychism | phenomenology | psychologism

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Library of Congress Catalog Data: ISSN 1095-5054

Experimental Psychology Studies Humans and Animals

Understanding Experimental Psychology

Our personalities, and to some degree our life experiences, are defined by the way we behave. But what influences the way we behave in the first place? How does our behavior shape our experiences throughout our lives? 

Experimental psychologists are interested in exploring theoretical questions, often by creating a hypothesis and then setting out to prove or disprove it through experimentation. They study a wide range of behavioral topics among humans and animals, including sensation, perception, attention, memory, cognition and emotion.

Experimental Psychology Applied

Experimental psychologists use scientific methods to collect data and perform research. Often, their work builds, one study at a time, to a larger finding or conclusion. Some researchers have devoted their entire career to answering one complex research question. 

These psychologists work in a variety of settings, including universities, research centers, government agencies and private businesses. The focus of their research is as varied as the settings in which they work. Often, personal interest and educational background will influence the research questions they choose to explore. 

In a sense, all psychologists can be considered experimental psychologists since research is the foundation of the discipline, and many psychologists split their professional focus among research, patient care, teaching or program administration. Experimental psychologists, however, often devote their full attention to research — its design, execution, analysis and dissemination. 

Those focusing their careers specifically on experimental psychology contribute work across subfields . For example, they use scientific research to provide insights that improve teaching and learning, create safer workplaces and transportation systems, improve substance abuse treatment programs and promote healthy child development.

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Psychology subfields

An Introduction to Experimental Psychology: Principles, Applications, and Discoveries

Curious about the inner workings of the human mind? Experimental psychology delves into the complexities of human behavior and cognition through rigorous scientific methods.

In this article, we explore the goals and principles of experimental psychology, its diverse applications in fields such as clinical and educational psychology, and some of the groundbreaking discoveries that have shaped our understanding of human behavior.

Join us on a journey through the fascinating world of experimental psychology.

• Experimental psychology uses an empirical approach to study behavior and mental processes.
• Objectivity, control, and replication are essential principles in experimental psychology.
• This field has applications in clinical, educational, industrial, and forensic settings.
• Some famous discoveries in experimental psychology include classical and operant conditioning, obedience and eyewitness studies, and attachment research.
• 1.1 What Is the Goal of Experimental Psychology?
• 2.1 Empirical Approach
• 2.2 Objectivity
• 2.3 Control
• 2.4 Replication
• 3.1 Clinical Psychology
• 3.2 Educational Psychology
• 3.3 Industrial and Organizational Psychology
• 3.4 Forensic Psychology
• 4.1 Pavlov’s Classical Conditioning
• 4.2 Skinner’s Operant Conditioning
• 4.3 Milgram’s Obedience Study
• 4.4 Loftus and Palmer’s Eyewitness Testimony Study
• 4.5 Bandura’s Bobo Doll Experiment
• 4.6 Harlow’s Attachment Study
• 5.1 What is experimental psychology?
• 5.2 What are the main principles of experimental psychology?
• 5.3 How is experimental psychology applied in real life?
• 5.4 What are some famous discoveries in experimental psychology?
• 5.5 What are some common research methods used in experimental psychology?
• 5.6 How can I get involved in experimental psychology?

What Is Experimental Psychology?

Experimental psychology is a branch of psychology that focuses on understanding human behavior, perception, cognition, and emotions through systematic research and studies.

One of the key goals of experimental psychology is to apply scientific methods to investigate various phenomena, such as memory, attention, decision-making, and motivation. Researchers in this field often employ controlled experiments to test hypotheses and gather empirical evidence. By manipulating variables in carefully designed studies, experimental psychologists aim to elucidate the underlying mechanisms that drive human behavior. Through these investigations, they can also uncover patterns and principles that contribute to the development of psychological theories and models.

What Is the Goal of Experimental Psychology?

The primary goal of experimental psychology is to uncover the underlying mechanisms that govern human behavior, perception, cognition, and emotions through controlled scientific studies and rigorous experimentation.

By conducting carefully designed experiments and observing human responses in controlled settings, experimental psychologists aim to establish causal relationships between variables and outcomes, shedding light on the intricate workings of the human mind and behavior.

Scientific rigor is paramount in this field, ensuring that findings are reliable and valid, contributing to the cumulative knowledge base of psychology.

Through the systematic manipulation of independent variables and measurement of dependent variables, researchers in experimental psychology strive to elucidate the complexities of human cognition, emotion, and behavior.

What Are the Principles of Experimental Psychology?

The principles of experimental psychology are founded on key tenets such as an empirical approach , objectivity, control, and replication, which form the basis for conducting rigorous scientific investigations into human behavior, perception, cognition, and emotions.

Experimental psychology’s reliance on an empirical approach ensures that research conclusions are based on observable evidence rather than subjective opinions. This emphasis on objectivity minimizes bias and strengthens the reliability of study outcomes. The control over variables allows researchers to isolate specific factors influencing behavior, aiding in the establishment of causal relationships. By replicating findings, psychologists verify the robustness and validity of their results, contributing to the advancement of knowledge within the field.

Empirical Approach

The empirical approach in experimental psychology emphasizes the reliance on direct observation, data collection, and experimentation to investigate and understand human behavior, perception, cognition, and emotions in a systematic and scientific manner.

This approach is fundamental in gathering objective and quantifiable data that can be analyzed to draw meaningful conclusions about various aspects of human psychology. Utilizing controlled experiments, researchers can manipulate variables to observe the cause and effect relationships, which provides valuable insights into the underlying mechanisms of behavior. Through meticulous experimental designs, such as within-subject and between-subject studies, researchers can compare different conditions and assess the impact of specific factors on human responses. Employing rigorous data collection techniques, including surveys, interviews, and physiological measurements, enables researchers to gather comprehensive data sets for in-depth analysis.

Objectivity

Objectivity is a crucial principle in experimental psychology, ensuring that researchers maintain a neutral and unbiased perspective when conducting studies, analyzing data, and interpreting results related to human behavior, perception, cognition, and emotions.

It is essential for researchers to approach their experiments with a mindset free from personal biases, preconceptions, or preferences, as these can cloud judgment and impact the validity of their findings. By adhering to the principle of objectivity, psychologists strive to minimize the influence of their own beliefs, emotions, or expectations on the research process.

Impartiality in data collection and analysis is fundamental for drawing accurate and reliable conclusions. Researchers must gather information systematically, without favoring certain outcomes, and interpret results objectively to avoid skewing the findings in any particular direction.

Control is a fundamental principle in experimental psychology, enabling researchers to manipulate variables, establish cause-and-effect relationships, and minimize extraneous influences that could impact the study of human behavior, perception, cognition, and emotions.

This principle of control plays a crucial role in the meticulous design of experiments. By carefully designing studies with controlled variables, researchers can precisely isolate the effects of the variables under investigation.

Through skilled manipulation of these variables, within a controlled setting, researchers can ascertain the causal relationships between them and the resulting outcomes observed.

This meticulous process not only allows for a deeper understanding of human behavior, perception, cognition, and emotions but also contributes significantly to the advancement of knowledge in the field of experimental psychology.

Replication

Replication is a critical principle in experimental psychology that emphasizes the need to reproduce research findings consistently through repeated studies, enhancing the reliability and validity of conclusions related to human behavior, perception, cognition, and emotions.

By replicating studies, researchers can verify the accuracy and generalizability of their results, ensuring that the observed effects are not merely due to chance or specific experimental conditions.

Replication also allows for the identification of potential errors or biases that may have influenced initial findings. The process of replication contributes to the cumulative nature of scientific knowledge, building a solid foundation of evidence that can withstand scrutiny and contribute to the advancement of the field.

What Are the Applications of Experimental Psychology?

Experimental psychology finds diverse applications in various subfields such as clinical psychology, educational psychology, industrial and organizational psychology, and forensic psychology, where insights into human behavior, perception, cognition, and emotions are utilized to address specific challenges and phenomena.

For instance, in clinical psychology, experimental findings help in understanding the mechanisms underlying mental disorders and developing effective therapeutic interventions. Educational psychology benefits from research on learning processes and memory retention to enhance teaching methods and curriculum designs.

In the industrial and organizational psychology domain, experimental studies play a crucial role in optimizing workplace environments, employee motivation, and leadership strategies. Forensic psychology relies on experimental investigations to analyze witness testimonies, jury decision-making, and offender behavior for legal proceedings.

Clinical Psychology

Clinical psychology utilizes insights from experimental psychology to understand and treat mental health disorders, behavioral issues, and emotional disturbances by applying evidence-based interventions and therapies rooted in scientific research on human behavior, perception, cognition, and emotions.

By integrating the findings of experimental psychology into clinical practice, psychologists are able to enhance their understanding of the underlying mechanisms that drive various psychological conditions. For instance, research on memory, learning, and decision-making processes has greatly contributed to the development of effective therapeutic techniques for individuals dealing with trauma or addiction.

This interdisciplinary approach allows clinicians to tailor their treatment strategies to address the specific needs of each patient, leading to more personalized and successful outcomes in therapy. Experimental psychology informs the assessment methods used in diagnosing disorders and monitoring treatment progress, enabling psychologists to make data-driven decisions to optimize patient care.

Educational Psychology

Educational psychology integrates experimental research on learning , memory , motivation , and cognition to enhance teaching practices, curriculum design, and student outcomes, leveraging scientific insights into human behavior and cognition to optimize educational strategies and interventions.

Experimental psychology plays a pivotal role within educational settings by providing valuable empirical evidence that informs and shapes the methodologies and approaches used in teaching. Through rigorous experimentation and analysis, researchers in this field uncover patterns and trends in how individuals learn, process information, and engage with educational content.

By applying the findings from experimental psychology studies, educators can tailor their instructional techniques, adjust curricula, and enhance classroom environments to better suit the diverse learning needs of students. This evidence-based approach ensures that teaching practices are rooted in science and adapted to align with the cognitive processes and needs of learners.

Industrial and Organizational Psychology

Industrial and organizational psychology employs experimental methods to investigate workplace behaviors, organizational dynamics, leadership styles, and employee motivation, utilizing scientific insights into human behavior, cognition, and emotions to enhance productivity, job satisfaction, and organizational effectiveness.

Through the lens of experimental psychology, organizations can gain valuable insights into how individuals interact within teams, respond to stressors, and make decisions in the workplace. By conducting controlled experiments and observational studies, researchers can uncover underlying psychological mechanisms influencing performance, communication patterns, and job satisfaction. These findings not only help in designing effective training programs and assessment tools but also provide a foundation for developing strategies to create a positive work environment, reduce conflicts, and foster leadership development.

Forensic Psychology

Forensic psychology relies on experimental research to analyze criminal behavior, witness testimony, investigative techniques, and judicial decision-making, using scientific insights into human behavior, cognition, and emotions to inform legal proceedings, criminal investigations, and justice systems.

Experimental psychology plays a vital role in the field of forensic psychology by providing a scientific approach to understanding the complexities of human behavior in legal contexts. Through controlled experiments and research studies, psychologists can delve into the underlying factors that influence criminal conduct and witness testimonies.

The application of experimental findings in forensic contexts aids in assessing the credibility of witnesses, identifying patterns of deception, and enhancing investigative strategies to uncover crucial evidence for legal proceedings. By integrating empirical data and psychological theories, forensic psychologists can contribute valuable insights to the judicial system and law enforcement agencies.

What Are Some Famous Discoveries in Experimental Psychology?

Experimental psychology has witnessed several landmark discoveries that have shaped our understanding of human behavior, perception, cognition, and emotions, including Pavlov’s Classical Conditioning, Skinner’s Operant Conditioning, Milgram’s Obedience Study, Loftus and Palmer’s Eyewitness Testimony Study, Bandura’s Bobo Doll Experiment, and Harlow’s Attachment Study.

These experiments have significantly influenced the field by providing key insights into human learning, social behavior, memory, and attachment. For instance, Pavlov’s Classical Conditioning demonstrated how associations can be formed between stimuli and responses, laying the foundation for understanding various learned behaviors. Skinner’s Operant Conditioning further elucidated the role of consequences in shaping behavior, emphasizing the importance of reinforcement and punishment in learning processes.

Milgram’s Obedience Study shed light on the power of authority in influencing individuals’ actions, revealing the disturbing extent to which people may comply with unethical commands. Loftus and Palmer’s Eyewitness Testimony Study challenged the reliability of memory and highlighted how external factors can distort recollections of events.

Bandura’s Bobo Doll Experiment pioneered the concept of observational learning, showing how individuals can acquire new behaviors through modeling others, impacting our understanding of social learning processes. Harlow’s Attachment Study revolutionized our understanding of attachment in primates by demonstrating the importance of social and emotional bonds in development.

Pavlov’s Classical Conditioning

Pavlov’s Classical Conditioning experiment demonstrated how associative learning occurs in response to stimuli, establishing a foundational principle in psychology that explains how behaviors can be modified through conditioning processes involving stimulus-response associations.

The groundbreaking study conducted by Ivan Pavlov involved ringing a bell before presenting food to dogs, initially causing them to salivate only at the sight and smell of food. Through repeated pairings of the bell and food, the dogs started associating the bell with the upcoming meal, eventually eliciting a salivary response even without food presence.

• The findings of Pavlov’s experiment showcased the phenomenon of conditioned response where previously neutral stimuli come to evoke specific behaviors due to repeated pairings with meaningful stimuli.

This essential insight into behavioral conditioning has led to a profound understanding of how learning and modification of behaviors can be achieved by manipulating environmental cues and responses.

Skinner’s Operant Conditioning

Skinner’s Operant Conditioning research elucidated how behaviors are influenced by consequences such as rewards and punishments, providing insights into operant behaviors and reinforcement principles that shape learning and behavior modification.

Skinner’s experiments involved studying how organisms learn through the consequences of their actions. He identified two main types of consequences: reinforcement and punishment. Reinforcement, which includes positive reinforcement where a behavior is strengthened by a rewarding stimulus, and negative reinforcement, where a behavior is strengthened by the removal of an aversive stimulus, plays a crucial role in shaping behavior. On the other hand, punishment involves the application of an aversive stimulus to decrease the likelihood of a behavior recurring. These concepts not only help understand how behaviors are learned but also provide effective tools for behavior modification in various fields such as education, psychology, and therapy.

Milgram’s Obedience Study

Milgram’s Obedience Study investigated the extent to which individuals comply with authority figures, revealing the powerful influence of situational factors on human behavior, obedience, and ethical considerations in social psychology.

The experimental setup of Milgram’s Obedience Study involved a simulated scenario where participants, who believed they were administering electric shocks to another person, were instructed by an authority figure to continue escalating the voltage despite hearing cries of pain. This controlled environment aimed to examine how ordinary individuals respond to perceived authority, shedding light on the psychological mechanisms underlying obedience.

The findings of the study were startling, indicating that a significant proportion of participants were willing to administer potentially harmful shocks to the ‘learner’ simply due to the influence of the authoritative instruction. This highlighted the profound impact of situational factors, such as the presence of an authority figure, on shaping behavior even against one’s moral compass.

Loftus and Palmer’s Eyewitness Testimony Study

Loftus and Palmer’s Eyewitness Testimony Study demonstrated how memory reconstruction can be influenced by leading questions, highlighting the malleability of memory and the impact of suggestion on eyewitness accounts in legal contexts.

Elizabeth Loftus and John Palmer conducted a series of experiments where participants were shown a video of a car accident. They were then asked questions, with one group being asked how fast the cars smashed into each other while another was asked how fast they contacted each other. The study found that the language used significantly altered participants’ estimates of the speed of the cars, showcasing the power of wording on memory retrieval and perception.

Bandura’s Bobo Doll Experiment

Bandura’s Bobo Doll Experiment illustrated the concept of observational learning, showing how individuals acquire new behaviors by observing and imitating others, thereby contributing to our understanding of social learning processes and behavior modeling.

The experiment, conducted in 1961 by psychologist Albert Bandura, involved children observing an adult model behaving aggressively towards a Bobo doll. The children were then placed in a room with toys, including the Bobo doll, and were observed to see if they would imitate the aggressive behaviors. Results showed that children who had witnessed the adult’s aggressive actions were more likely to replicate them, highlighting the power of observational learning in shaping behavior.

Harlow’s Attachment Study

Harlow’s Attachment Study with infant rhesus monkeys revealed the critical role of contact comfort in attachment formation, challenging prevailing beliefs about attachment theory and highlighting the significance of social bonding and emotional connections in developmental psychology.

The groundbreaking experiment conducted by Harlow involved separating infant monkeys from their biological mothers and providing them with two surrogate mothers – one made of wire with a feeding bottle and the other covered in soft cloth without a feeding mechanism. Most surprisingly, the baby monkeys chose to spend the majority of their time clinging to the cloth mother , emphasizing the importance of comfort and security in attachment relationships. This study reshaped the understanding of attachment dynamics by demonstrating that emotional closeness and comfort are fundamental for healthy social and emotional development, rather than just physical nourishment.

Frequently Asked Questions

What is experimental psychology.

Experimental psychology is a branch of psychology that focuses on using scientific methods to study human behavior and mental processes.

What are the main principles of experimental psychology?

The main principles of experimental psychology include objectivity, control, and replicability. Objectivity involves using unbiased methods to collect and analyze data. Control refers to the ability to manipulate variables and isolate their effects. Replicability involves being able to repeat an experiment and obtain similar results.

How is experimental psychology applied in real life?

Experimental psychology has various applications, such as understanding and treating mental disorders, improving education and learning, and informing public policies and practices. It is also used in market research, product development, and advertising.

What are some famous discoveries in experimental psychology?

Some famous discoveries in experimental psychology include Ivan Pavlov’s classical conditioning, B.F. Skinner’s operant conditioning, Stanley Milgram’s obedience experiments, and Philip Zimbardo’s Stanford prison experiment.

What are some common research methods used in experimental psychology?

Experimental psychologists use a variety of research methods, such as laboratory experiments, field experiments, surveys, and observational studies. These methods allow them to systematically test hypotheses and gather data on human behavior and mental processes.

How can I get involved in experimental psychology?

If you are interested in experimental psychology, you can pursue a degree in psychology and focus on experimental methods. You can also participate in research studies or volunteer at a psychology research lab. Additionally, you can stay updated on current research and attend conferences or workshops in the field.

Gabriel Silva is a cultural psychologist interested in how cultural contexts influence individual psychology and vice versa. His fieldwork spans multiple continents, studying the diversity of human experience through the lens of psychology. Gabriel’s writings reflect his journey, offering readers a global perspective on the ways culture shapes our identity, values, and interactions with the world.

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The psychology of experimental psychologists: Overcoming cognitive constraints to improve research: The 47th Sir Frederic Bartlett Lecture

Like many other areas of science, experimental psychology is affected by a “replication crisis” that is causing concern in many fields of research. Approaches to tackling this crisis include better training in statistical methods, greater transparency and openness, and changes to the incentives created by funding agencies, journals, and institutions. Here, I argue that if proposed solutions are to be effective, we also need to take into account human cognitive constraints that can distort all stages of the research process, including design and execution of experiments, analysis of data, and writing up findings for publication. I focus specifically on cognitive schemata in perception and memory, confirmation bias, systematic misunderstanding of statistics, and asymmetry in moral judgements of errors of commission and omission. Finally, I consider methods that may help mitigate the effect of cognitive constraints: better training, including use of simulations to overcome statistical misunderstanding; specific programmes directed at inoculating against cognitive biases; adoption of Registered Reports to encourage more critical reflection in planning studies; and using methods such as triangulation and “pre mortem” evaluation of study design to foster a culture of dialogue and criticism.

Introduction

The past decade has been a bruising one for experimental psychology. The publication of a paper by Simmons, Nelson, and Simonsohn (2011) entitled “False-positive psychology” drew attention to problems with the way in which research was often conducted in our field, which meant that many results could not be trusted. Simmons et al. focused on “undisclosed flexibility in data collection and analysis,” which is now variously referred to as p -hacking, data dredging, noise mining, or asterisk hunting: exploring datasets with different selections of variables and different analyses to attain a p -value lower than .05 and, subsequently, reporting only the significant findings. Hard on the heels of their demonstration came a wealth of empirical evidence from the Open Science Collaboration (2015) . This showed that less than half the results reported in reputable psychological journals could be replicated in a new experiment.

The points made by Simmons et al. (2011) were not new: indeed, they were anticipated in 1830 by Charles Babbage, who described “cooking” of data:

This is an art of various forms, the object of which is to give ordinary observations the appearance and character of those of the highest degree of accuracy. One of its numerous processes is to make multitudes of observations, and out of these to select only those which agree, or very nearly agree. If a hundred observations are made, the cook must be very unhappy if he cannot pick out fifteen or twenty which will do for serving up. (p. 178–179)

P -hacking refers to biased selection of data or analyses from within an experiment. Bias also affects which studies get published in the form of publication bias—the tendency for positive results to be overrepresented in the published literature. This is problematic because it gives an impression that findings are more consistent than is the case, which means that false theories can attain a state of “canonisation,” where they are widely accepted as true ( Nissen, Magidson, Gross, & Bergstrom, 2016 ). Figure 1 illustrates this with a toy simulation of a set of studies testing a difference between means from two conditions. If we have results from a series of experiments, three of which found a statistically significant difference and three of which did not, this provides fairly strong evidence that the difference is real (panel a). However, if we add a further four experiments that were not reported because results were null, the evidence cumulates in the opposite direction. Thus, omission of null studies can drastically alter our impression of the overall support for a hypothesis.

The impact of publication bias demonstrated with plots of cumulative log odds in favour of true versus null effect over a series of experiments. The log odds for each experiment can be computed with knowledge of alpha (.05) and power (.8); 1 denotes an experiment with significant difference between means, and 0, a null result. The starting point is zero, indicating that we assume a 50:50 chance of a true effect. For each significant result, the log odds of it coming from a true effect versus a null effect is log(.8/.05) = 2.77. For a null result, the log odds is log (.2/.95) = −1.55. The selected set of studies in panel (a) concludes with a log odds greater than 3, indicating that the likelihood of a true effect is 20 times greater than a null effect. However, panel (b), which includes additional null results (labelled in grey), leads to the opposite conclusion.

Since the paper by Simmons et al. (2011) , there has been a dramatic increase in replication studies. As a result, a number of well-established phenomena in psychology have come into question. Often it is difficult to be certain whether the original reports were false positives, whether the replication was flawed, or whether the effect of interest is only evident under specific conditions—see, for example, Hobson and Bishop (2016) on mu suppression in response to observed actions; Sripada, Kesller, and Jonides (2016) on ego depletion; Lehtonen et al. (2018) on an advantage in cognitive control for bilinguals; O’Donnell et al. (2018) on the professor-priming effect; and Oostenbroek et al. (2016) on neonatal imitation. What is clear is that the size, robustness, and generalisability of many classic effects are lower than previously thought.

Selective reporting, through p -hacking and publication bias, is not the only blight on our science. A related problem is many editors place emphasis on reporting results in a way that “tells a good story,” even if that means retrofitting our hypothesis to the data, i.e., HARKing or “hypothesising after the results are known” ( Kerr, 1998 ). Oberauer and Lewandowsky (2019) drew parallels between HARKing and p -hacking: in HARKing, there is post hoc selection of hypotheses, rather than selection of results or an analytic method. They proposed that HARKing is most widely used in fields where theories are so underspecified that they can accommodate many hypotheses and where there is a lack of “disconfirmatory diagnosticity,” i.e., failure to support a prediction is uninformative.

A lack of statistical power is a further problem for psychology—one that has been recognised since 1969 , when Jacob Cohen exhorted psychologists not to waste time and effort doing experiments that had too few observations to show an effect of interest. In other fields, notably clinical trials and genetics, after a period where non-replicable results proliferated, underpowered studies died out quite rapidly when journals adopted stringent criteria for publication (e.g., Johnston, Lahey, & Matthys, 2013 ), and funders began to require power analysis in grant proposals. Psychology, however, has been slow to catch up.

It is not just experimental psychology that has these problems—studies attempting to link psychological traits and disorders to genetic and/or neurobiological variables are, if anything, subject to greater challenges. A striking example comes from a meta-analysis of links between the serotonin transporter gene, 5-HTTPLR, and depression. This postulated association has attracted huge research interest over the past 20 years, and the meta-analysis included 450 studies. Contrary to expectation, it concluded that there was no evidence of association. In a blog post summarising findings, Alexander (2019) wrote,

. . . what bothers me isn’t just that people said 5-HTTLPR mattered and it didn’t. It’s that we built whole imaginary edifices, whole castles in the air on top of this idea of 5-HTTLPR mattering. We “figured out” how 5-HTTLPR exerted its effects, what parts of the brain it was active in, what sorts of things it interacted with, how its effects were enhanced or suppressed by the effects of other imaginary depression genes. This isn’t just an explorer coming back from the Orient and claiming there are unicorns there. It’s the explorer describing the life cycle of unicorns, what unicorns eat, all the different subspecies of unicorn, which cuts of unicorn meat are tastiest, and a blow-by-blow account of a wrestling match between unicorns and Bigfoot.

It is no exaggeration to say that our field is at a crossroads ( Pashler & Wagenmakers, 2012 ), and the 5-HTTLPR story is just a warning sign that practices that lead to bad science are widespread. If we continue to take the well-trodden path, using traditional methods for cooking data and asterisk hunting, we are in danger of losing attention, respect, and funding.

Much has been written about how we might tackle the so-called “replication crisis.” There have been four lines of attack. First, there have been calls for greater openness and transparency ( Nosek et al., 2015 ). Second, a case has been made for better training in methods (e.g., Rousselet, Pernet, & Wilcox, 2017 ). Third, it has been argued we need to change the way research has been conducted to incorporate pre-registration of research protocols, preferably in the format of Registered Reports, which are peer-reviewed prior to data collection ( Chambers, 2019 ). Fourth, it is recognised that for too long, the incentive structure of research has prioritised innovative, groundbreaking results over methodological quality. Indeed, Smaldino and McElreath (2016) suggested that one can model the success of scientists in a field as an evolutionary process, where prestigious publications lead to survival, leaving those whose work is less exciting to wither away and leave science. The common thread to these efforts is that they locate the mechanisms of bad science at the systemic level, in ways in which cultures and institutions reinforce norms and distribute resources. The solutions are, therefore, aimed at correcting these shortcomings by creating systems that make good behaviour easier and more rewarding and make poor behaviour more costly.

My view, however, is that institutional shortcomings are only part of the story: to improve scientific research, we also need to understand the mechanisms that maintain bad practices in individual humans. Bad science is usually done because somebody mistook it for good science. Understanding why individual scientists mistake bad science for good, and helping them to resist these errors, is a necessary component of the movement to improve psychology. I will argue that we need to understand how cognitive constraints lead to faulty reasoning if we are to get science back on course and persuade those who set the incentives to reform. Fortunately, as psychologists, we are uniquely well positioned to tackle this issue.

Experimental psychology has a rich tradition of studying human reasoning and decision-making, documenting the flaws and foibles that lead us to selectively process some types of information, make judgements on the basis of incomplete evidence, and sometimes behave in ways that seem frankly irrational. This line of work has had significant application to economics, politics, business studies, and law, but, with some notable exceptions (e.g., Hossenfelder, 2018 ; Mahoney, 1976 ), it has seldom been considered when studying the behaviour of research scientists. In what follows, I consider how our knowledge of human cognition can make sense of problematic scientific practices, and I propose ways we might use this information to find solutions.

Cognitive constraints that affect how psychological science is done

Table 1 lists four characteristics of human cognition that I focus on: I refer to these as “constraints” because they limit how we process, understand, or remember information, but it is important to note that they include some biases that can be beneficial in many contexts. The first constraint is confirmation bias. As Hahn and Harris (2014) noted, a range of definitions of “confirmation bias” exist—here, I will define it as the tendency to seek out evidence that supports our position. A further set of constraints has to do with understanding of probability. A lack of an intuitive grasp of probability contributes to both neglect of statistical power in study design and p -hacking in data analysis. Third, there is an asymmetry in moral reasoning that can lead us to treat errors of omission as less culpable than errors of commission, even when their consequences are equally serious ( Haidt & Baron, 1996 ). The final constraint featured in Bartlett’s (1932) work: reliance on cognitive schemata to fill in unstated information, leading to “reconstructive remembering,” which imbues memories with meaning while filtering out details that do not fit preconceptions.

Different types of cognitive constraints.

In what follows, I illustrate how these constraints assume particular importance at different stages of the research process, as shown in Table 2 .

Cognitive constraints that operate at different stages of the research process.

HARKing: hypothesising after the results are known.

Bias in experimental design

Confirmation bias and the failure to consider alternative explanations.

Scientific discovery involves several phases: the researcher needs to (a) assemble evidence, (b) look for meaningful patterns and regularities in the data, (c) formulate a hypothesis, and (d) test it empirically by gathering informative new data. Steps (a)–(c) may be designated as exploratory and step (d) as hypothesis testing or confirmatory ( Wagenmakers, Wetzels, Borsboom, van der Mass, & Kievit, 2012 ). Importantly, the same experiment cannot be used to both formulate and confirm a hypothesis. In practice, however, the distinction between the two types of experiment is often blurred.

Our ability to see patterns in data is vital at the exploratory stage of research: indeed, seeing something that nobody else has observed is a pinnacle of scientific achievement. Nevertheless, new ideas are often slow to be accepted, precisely because they do not fit the views of the time. One such example is described by Zilles and Amunts (2010) : Brodmann’s cytoarchitectonic map of the brain, described in 1909. This has stood the test of time and is still used over 100 years later, but for several decades, it was questioned by those who could not see the fine distinctions made by Brodmann. Indeed, criticisms of poor reproducibility and lack of objectivity were levelled against him.

Brodmann’s case illustrates that we need to be cautious about dismissing findings that depend on special expertise or unique insight of the observer. However, there are plenty of other instances in the history of science where invalid ideas persisted, especially if proposed by an influential or charismatic figure. Entire edifices of pseudoscience have endured because we are very bad at discarding theories that do not work; as Bartlett (1932) would predict, new information that is consistent with the theory will strengthen its representation in our minds, but inconsistent information will be ignored. Examples from the history of science include the rete mirabile , a mass of intertwined arteries that is found in sheep but wrongly included in anatomical drawings of humans for over 1,000 years because of the significance attributed to this structure by Galen ( Bataille et al., 2007 ); the planet Vulcan, predicted by Newton’s laws and seen by many astronomers until its existence was disproved by Einstein’s discoveries ( Levenson, 2015 ); and N-rays, non-existent rays seen by at least 40 people and analysed in 3,090 papers by 100 scientists between 1903 and 1906 ( Nye, 1980 ).

Popper’s (1934/ 1959 ) goal was to find ways to distinguish science from pseudoscience, and his contribution to philosophy of science was to emphasise that we should be bold in developing ideas but ruthless in attempts to falsify them. In an early attempt to test scientists’ grasp of Popperian logic, Mahoney (1976) administered a classic task developed by Wason (1960) to 84 scientists (physicists, biologists, psychologists, and sociologists). In this deceptively simple task, people are shown four cards and told that each card has a number on one side and a patch of colour on the other side. The cards are placed to show number 3, number 8, red, and blue, respectively (see Figure 2 ). The task is to identify which cards need to be turned over to test the hypothesis that if an even number appears on one side, then the opposite side is red. The subject can pick any number of cards. The correct response is to name the two cards that could disconfirm the hypothesis—the number 8 and the blue card. Fewer than 10% of the scientists tested by Mahoney identified both critical cards, more often selecting the number 8 and the red card.

Wason’s (1960) task: The subject is told, “Each card has a number on one side and a patch of colour on the other. You are asked to test the hypothesis that—for these 4 cards—if an even number appears on one side, then the opposite side is red. Which card(s) would you turn over to test the hypothesis?”

Although this study was taken as evidence of unscientific reasoning by scientists, that conclusion has since been challenged by those who have criticised both Popperian logic, in general, and the Wason selection task, in particular, as providing an unrealistic test of human rationality. For a start, the Wason task uses a deterministic hypothesis that can be disproved by a single piece of evidence. This is not a realistic model of biological or behavioural sciences, where we seldom deal with deterministic phenomena. Consider the claim that smoking causes lung cancer. Most of us accept that this is so, even though we know there are people who smoke and who do not get lung cancer and people who get lung cancer but never smoked. When dealing with probabilistic phenomena, a Bayesian approach makes more sense, whereby we consider the accumulated evidence to determine the relative likelihood of one hypothesis over another (as illustrated in Figure 1 ). Theories are judged as more or less probable, rather than true or false. Oaksford and Chater (1994) showed that, from a Bayesian perspective, typical selections made on the Wason task would be rational in contexts where the antecedent and consequent of the hypothesis (an even number and red colour) were both rare. Subsequently, Perfors and Navarro (2009) concluded that in situations where rules are relevant only for a minority of entities, then confirmation bias is an efficient strategy.

This kind of analysis has shifted the focus to discussions about how far, and under what circumstances, people are rational decision-makers. However, it misses a key point about scientific reasoning, which is that it involves an active process of deciding which evidence to gather, rather than merely a passive evaluation of existing evidence. It seems reasonable to conclude that, when presented with a particular set of evidence, people generally make decisions that are rational when evaluated against Bayesian standards. However, history suggests that we are less good at identifying which new evidence needs to be gathered to evaluate a theory. In particular, people appear to have a tendency to accept a hypothesis on the basis of “good enough” evidence, rather than actively seeking evidence for alternative explanations. Indeed, an early study by Doherty, Mynatt, Tweney, and Schiavo (1979) found that, when given an opportunity to select evidence to help decide which of two hypotheses was true (in a task where a fictitious pot had to be assigned as originating from one of the two islands that differed in characteristic features), people seemed unable to identify which information would be diagnostic and tended, instead, to select information that could neither confirm nor disconfirm their hypothesis.

Perhaps the strongest evidence for our poor ability to consider alternative explanations comes from the history of the development of clinical trials. Although James Lind is credited with doing the first trials for treatment of scurvy in 1747, it was only in 1948 that the randomised controlled trial became the gold standard for evaluating medical interventions ( Vallier & Timmerman, 2008 ). The need for controls is not obvious, and people who are not trained in this methodology will often judge whether a treatment is effective on the basis of a comparison on an outcome measure between a pre-treatment baseline and a post-treatment evaluation. The logic is that if a group of patients given the treatment does not improve, the treatment did not work. If they do show meaningful gains, then it did work. And we can even embellish this comparison with a test of statistical significance. This reasoning can be seen as entirely rational, and this can explain why so many people are willing to accept that alternative medicine is effective.

The problem with this approach is that the pre–post intervention comparison allows important confounds to creep in. For instance, early years practitioners argue that we should identify language problems in toddlers so that we can intervene early. They find that if 18-month-old late talkers are given intervention, only a minority still have language problems at 2 years and, therefore, conclude the intervention was effective. However, if an untreated control group is studied over the same period, we find very similar rates of improvement ( Wake et al., 2011 )—presumably due to factors such a spontaneous resolution of problems or regression to the mean, which will lead to systematic bias in outcomes. Researchers need training to recognise causes of bias and to take steps to overcome them: thinking about possible alternative explanations of an observed phenomenon does not come naturally, especially when the preliminary evidence looks strong.

Intervention studies provide the clearest evidence of what I term “premature entrenchment” of a theory: some other examples are summarised in Table 3 . Note that these examples do not involve poor replicability, quite the opposite. They are all cases where an effect, typically an association between variables, is reliably observed, and researchers then converge on accepting the most obvious causal explanation, without considering lines of evidence that might point to alternative possibilities.

Premature entrenchment: examples where the most obvious explanation for an observed association is accepted for many years, without considering alternative explanations that could be tested with different evidence.

fMRI: functional magnetic resonance imaging.

Premature entrenchment may be regarded as evidence that humans adopt Bayesian reasoning: we form a prior belief about what is the case and then require considerably more evidence to overturn that belief than to support it. This would explain why, when presented with virtually identical studies that either provided support for or evidence against astrology, psychologists were more critical of the latter ( Goodstein & Brazis, 1970 ). The authors of that study expressed concern about the “double standard” shown by biased psychologists who made unusually harsh demands of research in borderline areas, but from a Bayesian perspective, it is reasonable to use prior knowledge so that extraordinary claims require extraordinary evidence. Bayesian reasoning is useful in many situations: it allows us to act decisively on the basis of our long-term experience, rather than being swayed by each new incoming piece of data. However, it can be disastrous if we converge on a solution too readily on the basis of incomplete or inaccurate information. This will be exacerbated by publication bias, which distorts the evidential landscape.

For many years, the only methods available to counteract the tendency for premature entrenchment were exhortations to be self-critical (e.g., Feynman, 1974 ) and peer review. The problem with peer review is that it typically comes too late to be useful, after research is completed. In the final section of this article, I will consider some alternative approaches that bring in external appraisal of experimental designs at an earlier stage in the research process.

Misunderstanding of probability leading to underpowered studies

Some 17 years after Cohen’s seminal work on statistical power, Newcombe (1987) wrote,

Small studies continue to be carried out with little more than a blind hope of showing the desired effect. Nevertheless, papers based on such work are submitted for publication, especially if the results turn out to be statistically significant. (p. 657)

In clinical medicine, things have changed, and the importance of adequate statistical power is widely recognised among those conducting clinical trials. But in psychology, the “blind hope” has persisted, and we have to ask ourselves why this is.

My evidence here is anecdotal, but the impression is that many psychologists simply do not believe advice about statistical power, perhaps because there are so many underpowered studies published in the literature. When a statistician is consulted about sample size for a study, he or she will ask the researcher to estimate the anticipated effect size. This usually leads to a sample size estimate that is far higher than the researcher anticipated or finds feasible, leading to a series of responses not unlike the first four of the five stages of grief: denial, anger, bargaining, and depression. The final stage, acceptance, may, however, not be reached.

Of course, there are situations where small sample sizes are perfectly adequate: the key issue is how large the effect of interest is in relation to the variance. In some fields, such as psychophysics, you may not even need statistics—the famous “interocular trauma” test (referring to a result so obvious and clear-cut that it hits you between the eyes) may suffice. Indeed, in such cases, recruitment of a large sample would just be wasteful.

There are, however, numerous instances in psychology where people have habitually used sample sizes that are too small to reliably detect an effect of interest: see, for instance, the analysis by Poldrack et al. (2017) of well-known effects in functional magnetic resonance imaging (fMRI) or Oakes (2017) on looking-time experiments in infants. Quite often, a line of research is started when a large effect is seen in a small sample, but over time, it becomes clear that this is a case of “winner’s curse,” a false positive that is published precisely because it looks impressive but then fails to replicate when much larger sample sizes are used. There are some recent examples from studies looking at neurobiological or genetic correlates of individual differences, where large-scale studies have failed to support previously published associations that had appeared to be solid (e.g., De Kovel & Francks, 2019 , on genetics of handedness; Traut et al., 2018 , on cerebellar volume in autism; Uddén et al., 2019 , on genetic correlates of fMRI language-based activation).

A clue to the persistence of underpowered psychology studies comes from early work by Tversky and Kahneman (1971 , 1974 ). They studied a phenomenon that they termed “belief in the law of small numbers,” an exaggerated confidence in the validity of conclusions based on small samples, and showed that even those with science training tended to have strong intuitions about random sampling that were simply wrong. They illustrated this with the following problem:

A certain town is served by two hospitals. In the larger hospital about 45 babies are born each day, and in the smaller hospital about 15 babies are born each day. As you know, about 50% of all babies are boys. However, the exact percentage varies from day to day. Sometimes it may be higher than 50%, sometimes lower. For a period of 1 year, each hospital recorded the days on which more than 60% of the babies born were boys. Which hospital do you think recorded more such days? 1. The large hospital 2. The small hospital 3. About the same (that is, within 5% of each other)

Most people selected Option 3, whereas, as illustrated in Figure 3 , Option 2 is the correct answer—with only 15 births per day, the day-to-day variation in the proportion of boys will be much higher than with 45 births per day, and hence, more days will have more than 60% boys. One reason why our intuitions deceive us is because the sample size does not affect the average percentage of male births in the long run: this will be 50%, regardless of the hospital size. But sample size has a dramatic impact on the variability in the proportion of male births from day to day. More formally, if you have a big and small sample drawn from the same population, the expected estimate of the mean will be the same, but the standard error of that estimate will be greater for the small sample.

Simulated data showing proportions of males born in a small hospital with 15 births per day versus a large hospital with 45 births per day. The small hospital has more days where more than 60% of births are boys (points above red line).

Statistical power depends on the effect size, which, for a simple comparison of two means, can be computed as the difference in means divided by the pooled standard deviation. It follows that power is crucially dependent on the proportion of variance in observations that is associated with an effect of interest, relative to background noise. Where variance is high, it is much harder to detect the effect, and hence, small samples are often underpowered. Increasing the sample size is not the only way to improve power: other options include improving the precision of measurement, using more effective manipulations, or adopting statistical approaches to control noise ( Lazic, 2018 ). But in many situations, increasing the sample size is the preferred approach to enhance statistical power to detect an effect.

Bias in data analysis: p -hacking

P -hacking can take various forms, but they all involve a process of selective analysis. Suppose some researchers hypothesise that there is an association between executive function and implicit learning in a serial reaction time task, and they test this in a study using four measures of executive function. Even if there is only one established way of scoring each task, they have four correlations; this means that the probability that none of the correlations is significant at the .05 level is .95 4 —i.e., .815—and conversely, the probability that at least one is significant is .185. This probability can be massaged to even higher levels if the experimenters look at the data and then select an analytic approach that maximises the association: maybe by dropping outliers, by creating a new scoring method, combining measures in composites, and so on. Alternatively, the experimenters may notice that the strength of the correlation varies with the age or sex of participants and so subdivide the sample to coax at least a subset of data into significance. The key thing about p -hacking is that at the end of the process, the researchers selectively report the result that “worked,” with the implication that the p -value can be interpreted at face value. But it cannot: probability is meaningless if not defined in terms of a particular analytic context. P -hacking appears to be common in psychology ( John, Loewenstein, & Prelec, 2012 ). I argue here that this is because it arises from a conjunction of two cognitive constraints: failure to understand probability, coupled with a view that omission of information when reporting results is not a serious misdemeanour.

Failure to understand probability

In an influential career guide, published by the American Psychological Association, Bem (2004) explicitly recommended going against the “conventional view” of the research process, as this might lead us to miss exciting new findings. Instead readers were encouraged to

become intimately familiar with . . . the data. Examine them from every angle. Analyze the sexes separately. Make up new composite indexes. If a datum suggests a new hypothesis, try to find additional evidence for it elsewhere in the data. If you see dim traces of interesting patterns, try to reorganize the data to bring them into bolder relief. If there are participants you don’t like, or trials, observers, or interviewers who gave you anomalous results, drop them (temporarily). Go on a fishing expedition for something—anything—interesting. (p. 2)

For those who were concerned this might be inappropriate, Bem offered reassurance. Everything is fine because what you are doing is exploring your data. Indeed, he implied that anyone who follows the “conventional view” would be destined to do boring research that nobody will want to publish.

Of course, Bem (2004) was correct to say that we need exploratory research. The problem comes when exploratory research is repackaged as if it were hypothesis testing, with the hypothesis invented after observing the data (HARKing), and the paper embellished with p -values that are bound to be misleading because they were p -hacked from numerous possible values, rather than derived from testing an a priori hypothesis. If results from exploratory studies were routinely replicated, prior to publication, we would not have a problem, but they are not. So why did the American Psychological Association think it appropriate to publish Bem’s views as advice to young researchers? We can find some clues in the book overview, which explains that there is a distinction between the “formal” rules that students are taught and the “implicit” rules that are applied in everyday life, concluding that “This book provides invaluable guidance that will help new academics plan, play, and ultimately win the academic career game.” Note that the stated goal is not to do excellent research: it is to have “a lasting and vibrant career.” It seems, then, that there is recognition here that if you do things in the “conventional” way, your career will suffer. It is clear from Bem’s framing of his argument that he was aware that his advice was not “conventional,” but he did not think it was unethical—indeed, he implied it would be unfair on young researchers to do things conventionally as that will prevent them making exciting discoveries that will enable them to get published and rise up the academic hierarchy. While it is tempting to lament the corruption of a system that treats an academic career as a game, it is more important to consider why so many people genuinely believe that p -hacking is a valid, and indeed creative, approach to doing research.

The use of null-hypothesis significance testing has attracted a lot of criticism, with repeated suggestions over the years that p -values be banned. I favour the more nuanced view expressed by Lakens (2019) , who suggests that p -values have a place in science, provided they are correctly understood and used to address specific questions. There is no doubt, however, that many people do misunderstand the p -value. There are many varieties of misunderstanding, but perhaps the most common is to interpret the p -value as a measure of strength of evidence that can be attached to a given result, regardless of the context. It is easy to see how this misunderstanding arises: if we hold the sample size constant, then for a single comparison, there will be a linear relationship between the p -value and the effect size. However, whereas an effect size remains the same, regardless of the analytic context, a p -value is crucially context-dependent.

Suppose in the fictitious study of executive function described above, the researchers have 20 participants and four measures of executive function (A–D) that correlate with implicit learning with r values of .21, .47, .07, and −.01. The statistics package tells us that the corresponding two-tailed p -values are .374, .037, .769, and .966. A naive researcher may rejoice at having achieved significance with the second correlation. However, as noted above, the probability that at least one correlation of the four will have an associated p -value of less than .05 is 18%, not 5%. If we want to identify correlations that are unlikely under the null hypothesis, then we need to correct the alpha level (e.g., by doing a Bonferroni correction to adjust by the number of tests, i.e., .05/4 = .0125). At this point, the researchers see their significant result snatched from their grasp. This creates a strong temptation to just drop the three non-significant tests and not report them. Alternatively, one sometimes sees papers that report the original p -value but then state that it “did not survive” Bonferroni correction, but they, nevertheless, exhume it and interpret the uncorrected value. Researchers acting this way may not think that they are doing anything inappropriate, other than going against advice of pedantic statisticians, especially given Bem’s (2004) advice to follow the “implicit” rather than “formal” rules of research. However, this is simply wrong: as illustrated above, a p -value can only be interpreted in relation to the context in which it is computed.

One way of explaining the notion of p -hacking is to use the old-fashioned method of games of chance. I find this scenario helpful: we have a magician who claims he can use supernatural powers to deal a poker hand of “three of a kind” from an unbiased deck of cards. This type of hand will occur in around 1 of 50 draws from an unbiased deck. He points you to a man who, to his amazement, finds that his hand contains three of a kind. However, you then discover he actually tried his stunt with 50 people, and this man was the only one who got three of a kind. You are rightly disgruntled. This is analogous to p -hacking. The three-of-a-kind hand is real enough, but its unusualness, and hence its value as evidence of the supernatural, depends on the context of how many tests were done. The probability that needs to be computed here is not the probability of one specific result but rather the probability that specific result would come up at least once in 50 trials.

Asymmetry of sins of omission and commission

According to Greenwald (1975) “[I]t is a truly gross ethical violation for a researcher to suppress reporting of difficult-to-explain or embarrassing data to present a neat and attractive package to a journal editor” (p. 19).

However, this view is not universal.

Greenwald’s focus was on publication bias, i.e., failure to report an entire study, but the point he made about “prejudice” against null results also applies to cases of p -hacking where only “significant” results are reported, whereas others go unmentioned. It is easy to see why scientists might play down the inappropriateness of p -hacking, when it is so important to generate “significant” findings in a world with a strong prejudice against null results. But I suspect another reason why people tend to underrate the seriousness of p -hacking is because it involves an error of omission (failing to report the full context of a p -value), rather than an error of commission (making up data).

In studies of morality judgement, errors of omission are generally regarded as less culpable than errors of commission (see, e.g., Haidt & Baron, 1996 ). Furthermore, p -hacking may be seen to involve a particularly subtle kind of dishonesty because the statistics and their associated p -values are provided by the output of statistics software. They are mathematically correct when testing a specific, prespecified hypothesis: the problem is that, without the appropriate context, they imply stronger evidence than is justified. This is akin to what Rogers, Zeckhauser, Gino, Norton, and Schweitzer (2017) have termed “paltering,” i.e., the use of truthful statements to mislead, a topic they studied in the context of negotiations. An example was given of a person trying to sell a car that had twice needed a mechanic to fix it. Suppose the potential purchaser directly asks “Has the car ever had problems?” An error of commission is to deny the problems, but a paltering answer would be “This car drives very smoothly and is very responsive. Just last week it started up with no problems when the temperature was −5 degrees Fahrenheit.” Rogers et al. showed that negotiators were more willing to palter than to lie, although potential purchasers regarded paltering as only marginally less immoral than lying.

Regardless of the habitual behaviour of researchers, the general public does not find p -hacking acceptable. Pickett and Roche (2018) did an M-Turk experiment in which a community sample was asked to judge the morality of various scenarios, including this one:

A medical researcher is writing an article testing a new drug for high blood pressure. When she analyzes the data with either method A or B, the drug has zero effect on blood pressure, but when she uses method C, the drug seems to reduce blood pressure. She only reports the results of method C, which are the results that she wants to see.

Seventy-one percent of respondents thought this behaviour was immoral, 73% thought the researcher should receive a funding ban, and 63% thought the researcher should be fired.

Nevertheless, although selective reporting was generally deemed immoral, data fabrication was judged more harshly, confirming that in this context, as in those studied by Haidt and Baron (1996) , sins of commission are taken more seriously than errors of omission.

If we look at the consequences of a specific act of p -hacking, it can potentially be more serious than an act of data fabrication: this is most obvious in medical contexts, where suppression of trial results, either by omitting findings from within a study or by failing to publish studies with null results, can provide a badly distorted basis for clinical decision-making. In their simulations of evidence cumulation, Nissen et al. (2016) showed how p -hacking could compound the impact of publication bias and accelerate the premature “canonization” of theories; the alpha level that researchers assume applies to experimental results is distorted by p -hacking, and the expected rate of false positives is actually much higher. Furthermore, p -hacking is virtually undetectable because the data that are presented are real, but the necessary context for their interpretation is missing. This makes it harder to correct the scientific record.

Bias in writing up a study

Most writing on the “replication crisis” focuses on aspects of experimental design and observations, data analysis, and scientific reporting. The resumé of literature that is found in the introduction to empirical papers, as well as in literature review articles, is given less scrutiny. I will make the case that biased literature reviews are universal and have a major role in sustaining poor reproducibility because they lead to entrenchment of false theories, which are then used as the basis for further research.

It is common to see biased literature reviews that put a disproportionate focus on findings that are consistent with the author’s position. Researchers who know an area well may be aware of this, especially if their own work is omitted, but in general, cherry-picking of evidence is hard to detect. I will use a specific paper published in 2013 to illustrate my point, but I will not name the authors, as it would be invidious to single them out when the kinds of bias in their literature review are ubiquitous. In their paper, my attention was drawn to the following statement in the introduction:

Regardless of etiology, cerebellar neuropathology commonly occurs in autistic individuals. Cerebellar hypoplasia and reduced cerebellar Purkinje cell numbers are the most consistent neuropathologies linked to autism. … MRI studies report that autistic children have smaller cerebellar vermal volume in comparison to typically developing children.

I was surprised to read this because a few years ago, I had attended a meeting on neuroanatomical studies of autism and had come away with the impression that there were few consistent findings. I did a quick search for an up-to-date review, which turned up a meta-analysis ( Traut et al., 2018 ), that included 16 MRI studies published between 1997 and 2010, five of which reported larger cerebellar size in autism and one of which found smaller cerebellar size. In the article I was reading, one paper had been cited to support the MRI statement, but it referred to a study where the absolute size of the vermis did not differ from typically developing children but was relatively small in the autistic participants, after the overall (larger) size of the cerebellum had been controlled for.

Other papers cited to support the claims of cerebellar neuropathology included a couple of early post mortem neuroanatomical studies, as well as two reviews. The first of these ( DiCicco-Bloom et al., 2006 ) summarised presentations from a conference and supported the claims made by the authors. The other one, however ( Palmen, van Engeland, Hof, & Schmitz, 2004 ), expressed more uncertainty and noted a lack of correspondence between early neuroanatomical studies and subsequent MRI findings, concluding,

Although some consistent results emerge, the majority of the neuropathological data remain equivocal. This may be due to lack of statistical power, resulting from small sample sizes and from the heterogeneity of the disorder itself, to the inability to control for potential confounding variables such as gender, mental retardation, epilepsy and medication status, and, importantly, to the lack of consistent design in histopathological quantitative studies of autism published to date.

In sum, a confident statement “cerebellar neuropathology commonly occurs in autistic individuals,” accompanied by a set of references, converged to give the impression that there is consensus that the cerebellum is involved in autism. However, when we drill down, we find that the evidence is uncertain, with discrepancies between neuropathological studies and MRI and methodological concerns about the former. Meanwhile, this study forms part of a large body of research in which genetically modified mice with cerebellar dysfunction are used as an animal model of autism. My impression is that few of the researchers using these mouse models appreciate that the claim of cerebellar abnormality in autism is controversial among those working with humans because each paper builds on the prior literature. There is entrenchment of error, for two reasons. First, many researchers will take at face value the summary of previous work in a peer-reviewed paper, without going back to original cited sources. Second, even if a researcher is careful and scholarly and does read the cited work, they are unlikely to find relevant studies that were not included in the literature review.

It is easy to take an example like this and bemoan the lack of rigour in scientific writing, but this is to discount cognitive biases that make it inevitable that, unless we adopt specific safeguards against this, cherry-picking of evidence will be the norm. Three biases lead us in this direction: confirmation bias, moral asymmetry, and reliance on schemata.

Confirmation bias: cherry-picking prior literature

A personal example may serve to illustrate the way confirmation bias can operate subconsciously. I am interested in genetic effects on children’s language problems, and I was in the habit of citing three relevant twin studies when I gave talks on this topic. All these obtained similar results, namely that there was a strong genetic component to developmental language disorders, as evidenced by much higher concordance for disorder in pairs of monozygotic versus dizygotic twins. In 2005 , however, Hayiou-Thomas, Oliver, and Plomin published a twin study with very different findings, with low twin/co-twin concordance, regardless of zygosity. It was only when I came to write a review of this area and I checked the literature that I realised I had failed to mention the 2005 study in talks for a year or two, even though I had collaborated with the authors and was well aware of the findings. I had formed a clear view on heritability of language disorders, and so I had difficulty remembering results that did not agree. Subsequently, I realised we should try to understand why this study obtained different results and found a plausible explanation ( Bishop & Hayiou-Thomas, 2008 ). But I only went back for a further critical look at the study because I needed to make sense of the conflicting results. It is inevitable that we behave this way as we try to find generalisable results from a body of work, but it creates an asymmetry of attention and focus between work that we readily accept, because it fits, and work that is either forgotten or looked at more critically, because it does not.

A particularly rich analysis of citation bias comes from a case study by Greenberg (2009) , who took as his starting point papers concerned with claims that a protein, β amyloid, was involved in causing a specific form of muscle disease. Greenberg classified papers according to whether they were positive, negative, or neutral about this claim and carried out a network analysis to identify influential papers (those with many citations). He found that papers that were critical of the claim received far fewer citations than those that supported it, and this was not explained by lower quality. Animal model studies were almost exclusively justified by selective citation of positive studies. Consistent with the idea of “reconstructive remembering,” he also found instances where cited content was distorted, as well as cases where influential review papers amplified citation bias by focusing attention only on positive work. The net result was an information (perhaps better termed a disinformation) cascade that would lead to a lack of awareness of critical data, which never gets recognised. In effect, when we have agents that adopt Bayesian reasoning, if they are presented with distorted information, this creates a positive feedback loop that leads to increasing bias in the prior. Viewed this way, we can start to see how omission of relevant citations is not a minor peccadillo but a serious contributor to entrenchment of error. Further evidence of the cumulative impact of citation bias is shown in Figure 4 , which uses studies of intervention for depression. Because studies in this area are registered, it is possible to track the fate of unpublished as well as published studies. The researchers showed that studies with null results are far less likely to be published than those with positive findings, but even if the former are published, there is a bias against citing them.

The cumulative impact of reporting and citation biases on the evidence base for antidepressants. (a) Displays the initial, complete cohort of trials that were recorded in a registry, while (b) through (e) show the cumulative effect of biases. Each circle indicates a trial, while the colour indicates whether results were positive or negative or were reported to give a misleadingly positive impression(spin). Circles connected by a grey line indicate trials from the same publication. The progression from (a) to (b) shows that nearly all the positive trials but only half of those with null results were published, and reporting of null studies showed (c) bias or (d) spin in what was reported. In (e), the size of the circle indicates the (relative) number of citations received by that category of studies.

Source. Reprinted with permission from De Vries et al. (2018) .

While describing such cases of citation bias, it is worth pausing to consider one of the best-known examples of distorted thinking: experimenter bias. This is similar to confirmation bias, but rather than involving selective attention to specific aspects of a situation that fits with our preconceptions, it has a more active character, whereby the experimenter can unwittingly influence the outcome of a study. The best-known research on this topic was the original Rosenthal and Fode (1963) study, where students were informed that the rats they were studying were “maze-bright” or “maze-dull,” when in fact they did not differ. Nevertheless, the “maze-bright” group learned better, suggesting that the experimenter would try harder to train an animal thought to have potential. A related study by Rosenthal and Jacobson (1963) claimed that if teachers were told that a test had revealed that specific pupils were “ready to bloom,” they would do better on an IQ test administered at the end of the year, even though the children so designated were selected at random.

Both these studies are widely cited. It is less well known that work on experimenter bias was subjected to a scathing critique by Barber and Silver (1968) , entitled “Fact, fiction and the experimenter bias effect,” in which it was noted that work in this area suffered from poor methodological quality, in particular p -hacking. Barber and Silver did not deny that experimenter bias could affect results, but they concluded that these effects were far less common and smaller in magnitude than those implied by Rosenthal’s early work. Subsequently, Barber (1976) developed this critique further in his book Pitfalls in Human Research. Yet Rosenthal’s work is more highly cited and better remembered than that of Barber.

Rosenthal’s work provides a cautionary tale: although confirmation bias helps explain distorted patterns of citation, the evidence for maladaptive cognitive biases has been exaggerated. Furthermore, studies on confirmation bias often use artificial experiments, divorced from real life, and the criteria for deciding that reasoning is erroneous are often poorly justified ( Hahn & Harris, 2014 ). In future, it would be worthwhile doing more naturalistic explorations of people’s memory for studies that do and do not support a position when summarising scientific literature.

On a related point, in using confirmation bias as an explanation for persistence of weak theories, there is a danger that I am falling into exactly the trap that I am describing. For instance, I was delighted to find Greenberg’s (2009) paper, as it chimed very well with my experiences when reading papers about cerebellar deficits in autism. But would I have described and cited it here if it had shown no difference between citations for papers that did and did not support the β amyloid claim? Almost certainly not. Am I going to read all literature on citation bias to find out how common it is? That strategy would soon become impossible if I tried to do it for every idea I touch upon in this article.

Moral asymmetry between errors of omission and commission

The second bias that fortifies the distortions in a literature review is the asymmetry of moral judgement that I referred to when discussing p -hacking. To my knowledge, paltering has not been studied in the context of literature reviews, but my impression is that selective presentation of results that fit, while failing to mention important contextual factors (e.g., the vermis in those with autism is smaller but only when you have covaried for the total cerebellar size), is common. How far this is deliberate or due to reconstructive remembering, however, is impossible to establish.

It would also be of interest to conduct studies on people’s attitudes to the acceptability of cherry-picking of literature versus paltering (misleadingly selective reporting) or invention of a study. I would anticipate that most would regard cherry-picking as fairly innocuous, for several reasons: first, it could be an unintended omission; second, the consequences of omitting material from a review may be seen as less severe than introducing misinformation; and third, selective citation of papers that fit a narrative can have a positive benefit in terms of readability. There are also pragmatic concerns: some journals limit the word count for an introduction or reference list so that full citation of all relevant work is not possible and, finally, sanctioning people for harmful omissions would create apparently unlimited obligations ( Haidt & Baron, 1996 ). Quite simply, there is far too much literature for even the most diligent scholar to read.

Nevertheless, consequences of omission can be severe. The above examples of research on the serotonin transporter gene in depression, or cerebellar abnormality in autism, emphasise how failure to cite earlier null results can lead to a misplaced sense of confidence in a phenomenon, which is wasteful in time and money when others attempt to build on it. And the more we encounter a claim, the more likely it is to be judged as true, regardless of actual accuracy (see Pennycook, Cannon, & Rand, 2018 , for a topical example). As Ingelfinger (1976) put it, “faulty or inappropriate references . . . like weeds, tend to reproduce themselves and so permit even the weakest of allegations to acquire, with repeated citation, the guise of factuality” (p. 1076).

Reliance on schemata

Our brains cannot conceivably process all the information around us: we have to find a way to select what is important to function and survive. This involves a search for meaningful patterns, which once established, allow us to focus on what is relevant and ignore the rest. Scientific discovery may be seen as an elevated version of pattern discovery: we see the height of scientific achievement as discovering regularities in nature that allow us to make better predictions about how the world behaves and to create new technologies and interventions from the basic principles we have discovered.

Scientific progress is not a simple process of weighing up competing pieces of evidence in relation to a theory. Rather than simply choosing between one hypothesis and another, we try to understand a problem in terms of a schema. Bartlett (1932) was one of the first psychologists to study how our preconceptions, or schemata, create distortions in perception and memory. He introduced the idea of “reconstructive remembering,” demonstrating how people’s memory of a narrative changed over time in specific ways, to become more coherent and aligned with pre-existing schemata.

Bartlett’s (1932) work on reconstructive remembering can explain why we not only tend to ignore inconsistent evidence ( Duyx, Urlings, Swaen, Bouter, & Zeegers, 2017 ) but also are prone to distort the evidence that we do include ( Vicente & Brewer, 1993 ). If we put together the combined influence of confirmation bias and reconstructive remembering, it suggests that narrative literature reviews have a high probability of being inaccurate: both types of bias will lead to a picture of research converging on a compelling story, when the reality may be far less tidy ( Katz, 2013 ).

I have focused so far on bias in citing prior literature, but schemata also influence how researchers go about writing up results. If we just were to present a set of facts that did not cohere, our work would be difficult to understand and remember. As Chalmers, Hedges, and Cooper (2002) noted, this point was made in 1885 by Lord Raleigh in a presidential address to the British Association for the Advancement of Science:

If, as is sometimes supposed, science consisted in nothing but the laborious accumulation of facts, it would soon come to a standstill, crushed, as it were, under its own weight. The suggestion of a new idea, or the detection of a law, supersedes much that has previously been a burden on the memory, and by introducing order and coherence facilitates the retention of the remainder in an available form. ( Rayleigh, 1885 , p. 20)

Indeed, when we write up our research, we are exhorted to “tell a story,” which achieves the “order and coherence” that Rayleigh described. Since his time, ample literature on narrative comprehension has confirmed that people fill in gaps in unstated information and find texts easier to comprehend and memorise when they fit a familiar narrative structure ( Bower & Morrow, 1990 ; Van den Broek, 1994 ).

This resonates with Dawkins’ ( 1976 ) criteria for a meme, i.e., an idea that persists by being transmitted from person to person. Memes need to be easy to remember, understand, and communicate, and so narrative accounts make far better memes than dry lists of facts. From this perspective, narrative serves a useful function in providing a scaffolding that facilitates communication. However, while this is generally a useful, and indeed essential, aspect of human cognition, in scientific communication, it can lead to propagation of false information. Bartlett (1932) noted that remembering is hardly ever really exact, “and it is not at all important that it should be so.” He was thinking of the beneficial aspects of schemata, in allowing us to avoid information overload and to focus on what is meaningful. However, as Dawkins emphasised, survival of a meme does not depend on it being useful or true. An idea such as the claim that vaccination causes autism is a very effective meme, but it has led to resurgence of diseases that were close to being eradicated.

In communicating scientific results, we need to strike a fine balance between presenting a precis of findings that is easily communicated and moving towards an increase in knowledge. I would argue the pendulum may have swung too far in the direction of encouraging researchers to tell good narratives. Not just media outlets, but also many journal editors and reviewers, encourage authors to tell simple stories that are easy to understand, and those who can produce these may be rewarded with funding and promotion.

The clearest illustration of narrative supplanting accurate reporting comes from the widespread use of HARKing, which was encouraged by Bem (2004) when he wrote,

There are two possible articles you can write: (a) the article you planned to write when you designed your study or (b) the article that makes the most sense now that you have seen the results. They are rarely the same, and the correct answer is (b).

Of course, formulating a hypothesis on the basis of observed data is a key part of the scientific process. However, as noted above, it is not acceptable to use the same data to both formulate and test the hypothesis—replication in a new sample is needed to avoid being misled by the play of chance and littering literature with false positives ( Lazic, 2016 ; Wagenmakers et al., 2012 ).

Kerr (1998) considered why HARKing is a successful strategy and pointed out that it allowed the researcher to construct an account of an experiment that fits a good story script:

Positing a theory serves as an effective “initiating event.” It gives certain events significance and justifies the investigators’ subsequent purposeful activities directed at the goal of testing the hypotheses. And, when one HARKs, a “happy ending” (i.e., confirmation) is guaranteed. (p. 203)

In this regard, Bem’s advice makes perfect sense: “A journal article tells a straightforward tale of a circumscribed problem in search of a solution. It is not a novel with subplots, flashbacks, and literary allusions, but a short story with a single linear narrative line.”

We have, then, a serious tension in scientific writing. We are expected to be scholarly and honest, to report all our data and analyses and not to hide inconvenient truths. At the same time, if we want people to understand and remember our work, we should tell a coherent story from which unnecessary details have been expunged and where we cut out any part of the narrative that distracts from the main conclusions.

Kerr (1998) was clear that HARKing has serious costs. As well as translating type I errors into hard-to-eradicate theory, he noted that it presents a distorted view of science as a process which is far less difficult and unpredictable than is really the case. We never learn what did not work because inconvenient results are suppressed. For early career researchers, it can lead to cynicism when they learn that the rosy picture portrayed in the literature was achieved only by misrepresentation.

Overcoming cognitive constraints to do better science

One thing that is clear from this overview is that we have known about cognitive constraints for decades, yet they continue to affect scientific research. Finding ways to mitigate the impact of these constraints should be a high priority for experimental psychologists. Here, I draw together some general approaches that might be used to devise an agenda for research improvement. Many of these ideas have been suggested before but without much consideration of cognitive constraints that may affect their implementation. Some methods, such as training, attempt to overcome the constraints directly in individuals: others involve making structural changes to how science is done to counteract our human tendency towards unscientific thinking. None of these provides a total solution: rather, the goal is to tweak the dials that dictate how people think and behave, to move us closer to better scientific practices.

It is often suggested that better training is needed to improve replicability of scientific results, yet the focus tends to be on formal instruction in experimental design and statistics. Less attention has been given to engendering a more intuitive understanding of probability, or counteracting cognitive biases, though there are exceptions, such as the course by Steel, Liermann, and Guttorp (2018) , which starts with a consideration of “How the wiring of the human brain leads to incorrect conclusions from data.” One way of inducing a more intuitive sense of statistics and p -values is by using data simulations. Simulation is not routinely incorporated in statistics training, but free statistical software now makes this within the grasp of all ( Tintle et al., 2015 ). This is a powerful way to experience how easy it is to get a “significant” p -value when running multiple tests. Students are often surprised when they generate repeated runs of a correlation matrix of random numbers with, say, five variables and find at least one “significant” correlation in about one in four runs. Once you understand that there is a difference between the probability associated with getting a specific result on a single test, predicted in advance, versus the probability of that result coming up at least once in a multitude of tests, then the dangers of p -hacking become easier to grasp.

Data simulation could also help overcome the misplaced “belief in the law of small numbers” ( Tversky & Kahneman, 1974 ). By generating datasets with a known effect size, and then taking samples from these and subjecting them to statistical test, the student can learn to appreciate just how easy it is to miss a true effect (type II error) if the study is underpowered.

There is small literature evaluating attempts to specifically inoculate people against certain types of cognitive bias. For instance, Morewedge et al. (2015) developed instructional videos and computer games designed to reduce a series of cognitive biases, including confirmation bias, and found these to be effective over the longer term. Typically, however, such interventions focus on hypothetical scenarios outside the scope of experimental psychology. They might improve scientific quality of research projects if adjusted to make them relevant to conducting and appraising experiments.

Triangulation of methods in study design

I noted above that for science to progress, we need to overcome a tendency to settle on the first theory that seems “good enough” to account for observations. Any method that forces the researcher to actively search for alternative explanations is, therefore, likely to stimulate better research.

The notion of triangulation ( Munafò & Davey Smith, 2018 ) was developed in the field of epidemiology, where reliance is primarily on observational data, and experimental manipulation is not feasible. Inferring causality from correlational data is hazardous, but it is possible to adopt a strategic approach of combining complementary approaches to analysis, each of which has different assumptions, strengths, and weaknesses. Epidemiology progresses when different explanations for correlational data are explicitly identified and evaluated, and converging evidence is obtained ( Lawlor, Tilling, & Davey Smith, 2016 ). This approach could be extended to other disciplines, by explicitly requiring researchers to use at least two different methods with different potential biases when evaluating a specific hypothesis.

A “culture of criticism”

Smith (2006) described peer review as “a flawed process, full of easily identified defects with little evidence that it works” (p. 182). Yet peer review provides one way of forcing researchers to recognise when they are so focused on a favoured theory that they are unable to break away. Hossenfelder (2018) has argued that the field of particle physics has stagnated because of a reluctance to abandon theories that are deemed “beautiful.” We are accustomed to regarding physicists as superior to psychologists in terms of theoretical and methodological sophistication. In general, they place far less emphasis than we do on statistical criteria for evidence, and where they do use statistics, they understand probability theory and adopt very stringent levels of significance. Nevertheless, according to Hossenfelder, they are subject to cognitive and social biases that make them reluctant to discard theories. She concludes her book with an Appendix on “What you can do to help,” and as well as advocating better understanding of cognitive biases, she recommends some cultural changes to address these. These include building “a culture of criticism.” In principle, we already have this—talks and seminars should provide a forum for research to be challenged—but in practice, critiquing another’s work is often seen as clashing with social conventions of being supportive to others, especially when it is conducted in public.

Recently, two other approaches have been developed, with the potential to make a “culture of criticism” more useful and more socially acceptable. Registered Reports ( Chambers, 2019 ) is an approach that was devised to prevent publication bias, p -hacking, and HARKing. This format moves the peer review process to a point before data collection so that results cannot influence editorial decisions. An unexpected positive consequence is that peer review comes at a point when it can be acted upon to improve the experimental design. Where reviewers of Registered Reports ask “how could we disprove the hypothesis?” and “what other explanations should we consider?” this can generate more informative experiments.

A related idea is borrowed from business practices and is known as the “pre mortem” approach ( Klein, 2007 ). Project developers gather together and are asked to imagine that a proposed project has gone ahead and failed. They are then encouraged to write down reasons why this has happened, allowing people to voice misgivings that they may have been reluctant to state openly, so they can be addressed before the project has begun. It would be worth evaluating the effectiveness of pre-mortems for scientific projects. We could strengthen this approach by incorporating ideas from Bang and Frith (2017) , who noted that group decision-making is most likely to be effective when the group is diverse and people can express their views anonymously. With both Registered Reports and the study pre-mortem, reviewers can have a role as critical friends who can encourage researchers to identify ways to improve a project before it is conducted. This can be a more positive experience for the reviewer, who may otherwise have no option but to recommend rejection of a study with flawed methodology.

Counteracting cherry-picking of literature

Turning to cherry-picking of prior literature, the established solution is the systematic review, where clear criteria are laid out in advance so that a comprehensive search can be made of all relevant studies ( Siddaway, Wood, & Hedges, 2019 ). The systematic review is only as good as the data that go into it, however, and if a field suffers from substantial publication bias and/or p -hacking, then, rather than tackling error entrenchment, it may add to it. With the most scrupulous search strategy, relevant papers with null results can be missed because positive results are mentioned in titles and abstracts of papers, whereas null results are not ( Lazic, 2016 , p. 15). This can mean that, if a study is looking at many possible associations (e.g., with brain regions or with genes), studies that considered a specific association but failed to find support for it will be systematically disregarded. This may explain why it seems to take 30 or 40 years for some erroneous entrenched theories to be abandoned. The situation may improve with increasing availability of open data. Provided data are adequately documented and accessible, the problem of missing relevant studies may be reduced.

Ultimately, the problem of biased reviews may not be soluble just by changing people’s citation habits. Journal editors and reviewers could insist that abstracts follow a structured format and report all variables that were tested, not just those that gave significant results. A more radical approach by funders may be needed to disrupt this wasteful cycle. When a research team applies to test a new idea, they could first be required to (a) conduct a systematic review (unless one has been recently done) and (b) replicate the original findings on which the work is based: this is the opposite to what happens currently, where novelty and originality are major criteria for funding. In addition, it could be made mandatory for any newly funded research idea to be investigated by at least two independent laboratories and using at least two different approaches (triangulation). All these measures would drastically slow down science and may be unfeasible where research needs highly specialised equipment, facilities, or skills that are specific to one laboratory. Nevertheless, slower science may be preferable to the current system where there are so many examples of false leads being pursued for decades, with consequent waste of resources.

Reconciling storytelling with honesty

Perhaps the hardest problem is how to reconcile our need for narrative with a “warts and all” account of research. Consider this advice from Bem (2004) —which I suspect many journal editors would endorse:

Contrary to the conventional wisdom, science does not care how clever or clairvoyant you were at guessing your results ahead of time. Scientific integrity does not require you to lead your readers through all your wrongheaded hunches only to show—voila!—they were wrongheaded. A journal article should not be a personal history of your stillborn thoughts . . . Your overriding purpose is to tell the world what you have learned from your study. If your results suggest a compelling framework for their presentation, adopt it and make the most instructive findings your centerpiece . . . Think of your dataset as a jewel. Your task is to cut and polish it, to select the facets to highlight, and to craft the best setting for it.

As Kerr (1998) pointed out, HARKing gives a misleading impression of what was found, which can be particularly damaging for students, who on reading literature may form the impression that it is normal for scientists to have their predictions confirmed and think of themselves as incompetent when their own experiments do not work out that way. One of the goals of pre-registration is to ensure that researchers do not omit inconvenient facts when writing up a study—or if they do, at least make it possible to see that this has been done. In the field of clinical medicine, impressive progress has been made in methodology, with registration now a requirement for clinical trials ( International Committee of Medical Journal Editors, 2019 ). Yet, Goldacre et al. (2019) found that even when a trial was registered, it was common for researchers to change the primary outcome measure without explanation, and it has been similarly noted that pre-registrations in psychology are often too ambiguous to preclude p -hacking ( Veldkamp et al., 2018 ). Registered Reports ( Chambers, 2019 ) adopt stricter standards that should prevent HARKing, but the author may struggle to maintain a strong narrative because messy reality makes a less compelling story than a set of results subjected to Bem’s (2004) cutting and polishing process.

Rewarding credible research practices

A final set of recommendations has to do with changing the culture so that incentives are aligned with efforts to counteract unhelpful cognitive constraints, and researchers are rewarded for doing reproducible, replicable research, rather than for grant income or publications in high-impact journals ( Forstmeier, Wagenmakers, & Parker, 2016 ; Pulverer, 2015 ). There is already evidence that funders are concerned to address problems with credibility of biomedical research ( Academy of Medical Sciences, 2015 ), and rigour and reproducibility are increasingly mentioned in grant guidelines (e.g., https://grants.nih.gov/policy/reproducibility/index.htm ). One funder, Cancer Research UK, is innovating by incorporating Registered Reports in a two-stage funding model ( Munafò, 2017 ). We now need publishers and institutions to follow suit and ensure that researchers are not disadvantaged by adopting a self-critical mind-set and engaging in practices of open and reproducible science ( Poldrack, 2019 ).

Acknowledgments

My thanks to Kate Nation, Matt Jaquiery, Joe Chislett, Laura Fortunato, Uta Frith, Stefan Lewandowsky, and Karalyn Patterson for invaluable comments on an early draft of this manuscript.

Declaration of conflicting interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The author is supported by a Principal Research Fellowship from the Wellcome Trust (programme grant no. 082498) and European Research Council advanced grant no. 694189.

• The 25 Most Influential Psychological Experiments in History

While each year thousands and thousands of studies are completed in the many specialty areas of psychology, there are a handful that, over the years, have had a lasting impact in the psychological community as a whole. Some of these were dutifully conducted, keeping within the confines of ethical and practical guidelines. Others pushed the boundaries of human behavior during their psychological experiments and created controversies that still linger to this day. And still others were not designed to be true psychological experiments, but ended up as beacons to the psychological community in proving or disproving theories.

This is a list of the 25 most influential psychological experiments still being taught to psychology students of today.

1. A Class Divided

Study conducted by: jane elliott.

Study Conducted in 1968 in an Iowa classroom

Experiment Details: Jane Elliott’s famous experiment was inspired by the assassination of Dr. Martin Luther King Jr. and the inspirational life that he led. The third grade teacher developed an exercise, or better yet, a psychological experiment, to help her Caucasian students understand the effects of racism and prejudice.

Elliott divided her class into two separate groups: blue-eyed students and brown-eyed students. On the first day, she labeled the blue-eyed group as the superior group and from that point forward they had extra privileges, leaving the brown-eyed children to represent the minority group. She discouraged the groups from interacting and singled out individual students to stress the negative characteristics of the children in the minority group. What this exercise showed was that the children’s behavior changed almost instantaneously. The group of blue-eyed students performed better academically and even began bullying their brown-eyed classmates. The brown-eyed group experienced lower self-confidence and worse academic performance. The next day, she reversed the roles of the two groups and the blue-eyed students became the minority group.

At the end of the experiment, the children were so relieved that they were reported to have embraced one another and agreed that people should not be judged based on outward appearances. This exercise has since been repeated many times with similar outcomes.

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2. Asch Conformity Study

Study conducted by: dr. solomon asch.

Study Conducted in 1951 at Swarthmore College

Experiment Details: Dr. Solomon Asch conducted a groundbreaking study that was designed to evaluate a person’s likelihood to conform to a standard when there is pressure to do so.

A group of participants were shown pictures with lines of various lengths and were then asked a simple question: Which line is longest? The tricky part of this study was that in each group only one person was a true participant. The others were actors with a script. Most of the actors were instructed to give the wrong answer. Strangely, the one true participant almost always agreed with the majority, even though they knew they were giving the wrong answer.

The results of this study are important when we study social interactions among individuals in groups. This study is a famous example of the temptation many of us experience to conform to a standard during group situations and it showed that people often care more about being the same as others than they do about being right. It is still recognized as one of the most influential psychological experiments for understanding human behavior.

3. Bobo Doll Experiment

Study conducted by: dr. alburt bandura.

Study Conducted between 1961-1963 at Stanford University

In his groundbreaking study he separated participants into three groups:

• one was exposed to a video of an adult showing aggressive behavior towards a Bobo doll
• another was exposed to video of a passive adult playing with the Bobo doll
• the third formed a control group

Children watched their assigned video and then were sent to a room with the same doll they had seen in the video (with the exception of those in the control group). What the researcher found was that children exposed to the aggressive model were more likely to exhibit aggressive behavior towards the doll themselves. The other groups showed little imitative aggressive behavior. For those children exposed to the aggressive model, the number of derivative physical aggressions shown by the boys was 38.2 and 12.7 for the girls.

The study also showed that boys exhibited more aggression when exposed to aggressive male models than boys exposed to aggressive female models. When exposed to aggressive male models, the number of aggressive instances exhibited by boys averaged 104. This is compared to 48.4 aggressive instances exhibited by boys who were exposed to aggressive female models.

While the results for the girls show similar findings, the results were less drastic. When exposed to aggressive female models, the number of aggressive instances exhibited by girls averaged 57.7. This is compared to 36.3 aggressive instances exhibited by girls who were exposed to aggressive male models. The results concerning gender differences strongly supported Bandura’s secondary prediction that children will be more strongly influenced by same-sex models. The Bobo Doll Experiment showed a groundbreaking way to study human behavior and it’s influences.

4. Car Crash Experiment

Study conducted by: elizabeth loftus and john palmer.

Study Conducted in 1974 at The University of California in Irvine

The participants watched slides of a car accident and were asked to describe what had happened as if they were eyewitnesses to the scene. The participants were put into two groups and each group was questioned using different wording such as “how fast was the car driving at the time of impact?” versus “how fast was the car going when it smashed into the other car?” The experimenters found that the use of different verbs affected the participants’ memories of the accident, showing that memory can be easily distorted.

This research suggests that memory can be easily manipulated by questioning technique. This means that information gathered after the event can merge with original memory causing incorrect recall or reconstructive memory. The addition of false details to a memory of an event is now referred to as confabulation. This concept has very important implications for the questions used in police interviews of eyewitnesses.

5. Cognitive Dissonance Experiment

Study conducted by: leon festinger and james carlsmith.

Study Conducted in 1957 at Stanford University

Experiment Details: The concept of cognitive dissonance refers to a situation involving conflicting:

This conflict produces an inherent feeling of discomfort leading to a change in one of the attitudes, beliefs or behaviors to minimize or eliminate the discomfort and restore balance.

Cognitive dissonance was first investigated by Leon Festinger, after an observational study of a cult that believed that the earth was going to be destroyed by a flood. Out of this study was born an intriguing experiment conducted by Festinger and Carlsmith where participants were asked to perform a series of dull tasks (such as turning pegs in a peg board for an hour). Participant’s initial attitudes toward this task were highly negative.

They were then paid either $1 or $20 to tell a participant waiting in the lobby that the tasks were really interesting. Almost all of the participants agreed to walk into the waiting room and persuade the next participant that the boring experiment would be fun. When the participants were later asked to evaluate the experiment, the participants who were paid only $1 rated the tedious task as more fun and enjoyable than the participants who were paid $20 to lie.

Being paid only $1 is not sufficient incentive for lying and so those who were paid $1 experienced dissonance. They could only overcome that cognitive dissonance by coming to believe that the tasks really were interesting and enjoyable. Being paid $20 provides a reason for turning pegs and there is therefore no dissonance.

6. Fantz’s Looking Chamber

Study conducted by: robert l. fantz.

Study Conducted in 1961 at the University of Illinois

Experiment Details: The study conducted by Robert L. Fantz is among the simplest, yet most important in the field of infant development and vision. In 1961, when this experiment was conducted, there very few ways to study what was going on in the mind of an infant. Fantz realized that the best way was to simply watch the actions and reactions of infants. He understood the fundamental factor that if there is something of interest near humans, they generally look at it.

To test this concept, Fantz set up a display board with two pictures attached. On one was a bulls-eye. On the other was the sketch of a human face. This board was hung in a chamber where a baby could lie safely underneath and see both images. Then, from behind the board, invisible to the baby, he peeked through a hole to watch what the baby looked at. This study showed that a two-month old baby looked twice as much at the human face as it did at the bulls-eye. This suggests that human babies have some powers of pattern and form selection. Before this experiment it was thought that babies looked out onto a chaotic world of which they could make little sense.

7. Hawthorne Effect

Study conducted by: henry a. landsberger.

Study Conducted in 1955 at Hawthorne Works in Chicago, Illinois

Landsberger performed the study by analyzing data from experiments conducted between 1924 and 1932, by Elton Mayo, at the Hawthorne Works near Chicago. The company had commissioned studies to evaluate whether the level of light in a building changed the productivity of the workers. What Mayo found was that the level of light made no difference in productivity. The workers increased their output whenever the amount of light was switched from a low level to a high level, or vice versa.

The researchers noticed a tendency that the workers’ level of efficiency increased when any variable was manipulated. The study showed that the output changed simply because the workers were aware that they were under observation. The conclusion was that the workers felt important because they were pleased to be singled out. They increased productivity as a result. Being singled out was the factor dictating increased productivity, not the changing lighting levels, or any of the other factors that they experimented upon.

The Hawthorne Effect has become one of the hardest inbuilt biases to eliminate or factor into the design of any experiment in psychology and beyond.

8. Kitty Genovese Case

Study conducted by: new york police force.

Study Conducted in 1964 in New York City

Experiment Details: The murder case of Kitty Genovese was never intended to be a psychological experiment, however it ended up having serious implications for the field.

According to a New York Times article, almost 40 neighbors witnessed Kitty Genovese being savagely attacked and murdered in Queens, New York in 1964. Not one neighbor called the police for help. Some reports state that the attacker briefly left the scene and later returned to “finish off” his victim. It was later uncovered that many of these facts were exaggerated. (There were more likely only a dozen witnesses and records show that some calls to police were made).

What this case later become famous for is the “Bystander Effect,” which states that the more bystanders that are present in a social situation, the less likely it is that anyone will step in and help. This effect has led to changes in medicine, psychology and many other areas. One famous example is the way CPR is taught to new learners. All students in CPR courses learn that they must assign one bystander the job of alerting authorities which minimizes the chances of no one calling for assistance.

9. Learned Helplessness Experiment

Study conducted by: martin seligman.

Study Conducted in 1967 at the University of Pennsylvania

Seligman’s experiment involved the ringing of a bell and then the administration of a light shock to a dog. After a number of pairings, the dog reacted to the shock even before it happened. As soon as the dog heard the bell, he reacted as though he’d already been shocked.

During the course of this study something unexpected happened. Each dog was placed in a large crate that was divided down the middle with a low fence. The dog could see and jump over the fence easily. The floor on one side of the fence was electrified, but not on the other side of the fence. Seligman placed each dog on the electrified side and administered a light shock. He expected the dog to jump to the non-shocking side of the fence. In an unexpected turn, the dogs simply laid down.

The hypothesis was that as the dogs learned from the first part of the experiment that there was nothing they could do to avoid the shocks, they gave up in the second part of the experiment. To prove this hypothesis the experimenters brought in a new set of animals and found that dogs with no history in the experiment would jump over the fence.

This condition was described as learned helplessness. A human or animal does not attempt to get out of a negative situation because the past has taught them that they are helpless.

10. Little Albert Experiment

Study conducted by: john b. watson and rosalie rayner.

Study Conducted in 1920 at Johns Hopkins University

The experiment began by placing a white rat in front of the infant, who initially had no fear of the animal. Watson then produced a loud sound by striking a steel bar with a hammer every time little Albert was presented with the rat. After several pairings (the noise and the presentation of the white rat), the boy began to cry and exhibit signs of fear every time the rat appeared in the room. Watson also created similar conditioned reflexes with other common animals and objects (rabbits, Santa beard, etc.) until Albert feared them all.

This study proved that classical conditioning works on humans. One of its most important implications is that adult fears are often connected to early childhood experiences.

11. Magical Number Seven

Study conducted by: george a. miller.

Study Conducted in 1956 at Princeton University

Experiment Details:   Frequently referred to as “ Miller’s Law,” the Magical Number Seven experiment purports that the number of objects an average human can hold in working memory is 7 ± 2. This means that the human memory capacity typically includes strings of words or concepts ranging from 5-9. This information on the limits to the capacity for processing information became one of the most highly cited papers in psychology.

The Magical Number Seven Experiment was published in 1956 by cognitive psychologist George A. Miller of Princeton University’s Department of Psychology in Psychological Review .  In the article, Miller discussed a concurrence between the limits of one-dimensional absolute judgment and the limits of short-term memory.

In a one-dimensional absolute-judgment task, a person is presented with a number of stimuli that vary on one dimension (such as 10 different tones varying only in pitch). The person responds to each stimulus with a corresponding response (learned before).

Performance is almost perfect up to five or six different stimuli but declines as the number of different stimuli is increased. This means that a human’s maximum performance on one-dimensional absolute judgment can be described as an information store with the maximum capacity of approximately 2 to 3 bits of information There is the ability to distinguish between four and eight alternatives.

12. Pavlov’s Dog Experiment

Study conducted by: ivan pavlov.

Study Conducted in the 1890s at the Military Medical Academy in St. Petersburg, Russia

Pavlov began with the simple idea that there are some things that a dog does not need to learn. He observed that dogs do not learn to salivate when they see food. This reflex is “hard wired” into the dog. This is an unconditioned response (a stimulus-response connection that required no learning).

Pavlov outlined that there are unconditioned responses in the animal by presenting a dog with a bowl of food and then measuring its salivary secretions. In the experiment, Pavlov used a bell as his neutral stimulus. Whenever he gave food to his dogs, he also rang a bell. After a number of repeats of this procedure, he tried the bell on its own. What he found was that the bell on its own now caused an increase in salivation. The dog had learned to associate the bell and the food. This learning created a new behavior. The dog salivated when he heard the bell. Because this response was learned (or conditioned), it is called a conditioned response. The neutral stimulus has become a conditioned stimulus.

This theory came to be known as classical conditioning.

13. Robbers Cave Experiment

Study conducted by: muzafer and carolyn sherif.

Study Conducted in 1954 at the University of Oklahoma

Experiment Details: This experiment, which studied group conflict, is considered by most to be outside the lines of what is considered ethically sound.

In 1954 researchers at the University of Oklahoma assigned 22 eleven- and twelve-year-old boys from similar backgrounds into two groups. The two groups were taken to separate areas of a summer camp facility where they were able to bond as social units. The groups were housed in separate cabins and neither group knew of the other’s existence for an entire week. The boys bonded with their cabin mates during that time. Once the two groups were allowed to have contact, they showed definite signs of prejudice and hostility toward each other even though they had only been given a very short time to develop their social group. To increase the conflict between the groups, the experimenters had them compete against each other in a series of activities. This created even more hostility and eventually the groups refused to eat in the same room. The final phase of the experiment involved turning the rival groups into friends. The fun activities the experimenters had planned like shooting firecrackers and watching movies did not initially work, so they created teamwork exercises where the two groups were forced to collaborate. At the end of the experiment, the boys decided to ride the same bus home, demonstrating that conflict can be resolved and prejudice overcome through cooperation.

Many critics have compared this study to Golding’s Lord of the Flies novel as a classic example of prejudice and conflict resolution.

14. Ross’ False Consensus Effect Study

Study conducted by: lee ross.

Study Conducted in 1977 at Stanford University

Experiment Details: In 1977, a social psychology professor at Stanford University named Lee Ross conducted an experiment that, in lay terms, focuses on how people can incorrectly conclude that others think the same way they do, or form a “false consensus” about the beliefs and preferences of others. Ross conducted the study in order to outline how the “false consensus effect” functions in humans.

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In the first part of the study, participants were asked to read about situations in which a conflict occurred and then were told two alternative ways of responding to the situation. They were asked to do three things:

• Guess which option other people would choose
• Say which option they themselves would choose
• Describe the attributes of the person who would likely choose each of the two options

What the study showed was that most of the subjects believed that other people would do the same as them, regardless of which of the two responses they actually chose themselves. This phenomenon is referred to as the false consensus effect, where an individual thinks that other people think the same way they do when they may not. The second observation coming from this important study is that when participants were asked to describe the attributes of the people who will likely make the choice opposite of their own, they made bold and sometimes negative predictions about the personalities of those who did not share their choice.

15. The Schacter and Singer Experiment on Emotion

Study conducted by: stanley schachter and jerome e. singer.

Study Conducted in 1962 at Columbia University

Experiment Details: In 1962 Schachter and Singer conducted a ground breaking experiment to prove their theory of emotion.

In the study, a group of 184 male participants were injected with epinephrine, a hormone that induces arousal including increased heartbeat, trembling, and rapid breathing. The research participants were told that they were being injected with a new medication to test their eyesight. The first group of participants was informed the possible side effects that the injection might cause while the second group of participants were not. The participants were then placed in a room with someone they thought was another participant, but was actually a confederate in the experiment. The confederate acted in one of two ways: euphoric or angry. Participants who had not been informed about the effects of the injection were more likely to feel either happier or angrier than those who had been informed.

What Schachter and Singer were trying to understand was the ways in which cognition or thoughts influence human emotion. Their study illustrates the importance of how people interpret their physiological states, which form an important component of your emotions. Though their cognitive theory of emotional arousal dominated the field for two decades, it has been criticized for two main reasons: the size of the effect seen in the experiment was not that significant and other researchers had difficulties repeating the experiment.

16. Selective Attention / Invisible Gorilla Experiment

Study conducted by: daniel simons and christopher chabris.

Study Conducted in 1999 at Harvard University

Experiment Details: In 1999 Simons and Chabris conducted their famous awareness test at Harvard University.

Participants in the study were asked to watch a video and count how many passes occurred between basketball players on the white team. The video moves at a moderate pace and keeping track of the passes is a relatively easy task. What most people fail to notice amidst their counting is that in the middle of the test, a man in a gorilla suit walked onto the court and stood in the center before walking off-screen.

The study found that the majority of the subjects did not notice the gorilla at all, proving that humans often overestimate their ability to effectively multi-task. What the study set out to prove is that when people are asked to attend to one task, they focus so strongly on that element that they may miss other important details.

17. Stanford Prison Study

Study conducted by philip zimbardo.

Study Conducted in 1971 at Stanford University

The Stanford Prison Experiment was designed to study behavior of “normal” individuals when assigned a role of prisoner or guard. College students were recruited to participate. They were assigned roles of “guard” or “inmate.”  Zimbardo played the role of the warden. The basement of the psychology building was the set of the prison. Great care was taken to make it look and feel as realistic as possible.

The prison guards were told to run a prison for two weeks. They were told not to physically harm any of the inmates during the study. After a few days, the prison guards became very abusive verbally towards the inmates. Many of the prisoners became submissive to those in authority roles. The Stanford Prison Experiment inevitably had to be cancelled because some of the participants displayed troubling signs of breaking down mentally.

Although the experiment was conducted very unethically, many psychologists believe that the findings showed how much human behavior is situational. People will conform to certain roles if the conditions are right. The Stanford Prison Experiment remains one of the most famous psychology experiments of all time.

18. Stanley Milgram Experiment

Study conducted by stanley milgram.

Study Conducted in 1961 at Stanford University

Experiment Details: This 1961 study was conducted by Yale University psychologist Stanley Milgram. It was designed to measure people’s willingness to obey authority figures when instructed to perform acts that conflicted with their morals. The study was based on the premise that humans will inherently take direction from authority figures from very early in life.

Participants were told they were participating in a study on memory. They were asked to watch another person (an actor) do a memory test. They were instructed to press a button that gave an electric shock each time the person got a wrong answer. (The actor did not actually receive the shocks, but pretended they did).

Participants were told to play the role of “teacher” and administer electric shocks to “the learner,” every time they answered a question incorrectly. The experimenters asked the participants to keep increasing the shocks. Most of them obeyed even though the individual completing the memory test appeared to be in great pain. Despite these protests, many participants continued the experiment when the authority figure urged them to. They increased the voltage after each wrong answer until some eventually administered what would be lethal electric shocks.

This experiment showed that humans are conditioned to obey authority and will usually do so even if it goes against their natural morals or common sense.

19. Surrogate Mother Experiment

Study conducted by: harry harlow.

Study Conducted from 1957-1963 at the University of Wisconsin

Experiment Details: In a series of controversial experiments during the late 1950s and early 1960s, Harry Harlow studied the importance of a mother’s love for healthy childhood development.

In order to do this he separated infant rhesus monkeys from their mothers a few hours after birth and left them to be raised by two “surrogate mothers.” One of the surrogates was made of wire with an attached bottle for food. The other was made of soft terrycloth but lacked food. The researcher found that the baby monkeys spent much more time with the cloth mother than the wire mother, thereby proving that affection plays a greater role than sustenance when it comes to childhood development. They also found that the monkeys that spent more time cuddling the soft mother grew up to healthier.

This experiment showed that love, as demonstrated by physical body contact, is a more important aspect of the parent-child bond than the provision of basic needs. These findings also had implications in the attachment between fathers and their infants when the mother is the source of nourishment.

20. The Good Samaritan Experiment

Study conducted by: john darley and daniel batson.

Study Conducted in 1973 at The Princeton Theological Seminary (Researchers were from Princeton University)

Experiment Details: In 1973, an experiment was created by John Darley and Daniel Batson, to investigate the potential causes that underlie altruistic behavior. The researchers set out three hypotheses they wanted to test:

• People thinking about religion and higher principles would be no more inclined to show helping behavior than laymen.
• People in a rush would be much less likely to show helping behavior.
• People who are religious for personal gain would be less likely to help than people who are religious because they want to gain some spiritual and personal insights into the meaning of life.

Student participants were given some religious teaching and instruction. They were then were told to travel from one building to the next. Between the two buildings was a man lying injured and appearing to be in dire need of assistance. The first variable being tested was the degree of urgency impressed upon the subjects, with some being told not to rush and others being informed that speed was of the essence.

The results of the experiment were intriguing, with the haste of the subject proving to be the overriding factor. When the subject was in no hurry, nearly two-thirds of people stopped to lend assistance. When the subject was in a rush, this dropped to one in ten.

People who were on the way to deliver a speech about helping others were nearly twice as likely to help as those delivering other sermons,. This showed that the thoughts of the individual were a factor in determining helping behavior. Religious beliefs did not appear to make much difference on the results. Being religious for personal gain, or as part of a spiritual quest, did not appear to make much of an impact on the amount of helping behavior shown.

21. The Halo Effect Experiment

Study conducted by: richard e. nisbett and timothy decamp wilson.

Study Conducted in 1977 at the University of Michigan

Experiment Details: The Halo Effect states that people generally assume that people who are physically attractive are more likely to:

• be intelligent
• be friendly
• display good judgment

To prove their theory, Nisbett and DeCamp Wilson created a study to prove that people have little awareness of the nature of the Halo Effect. They’re not aware that it influences:

• their personal judgments
• the production of a more complex social behavior

In the experiment, college students were the research participants. They were asked to evaluate a psychology instructor as they view him in a videotaped interview. The students were randomly assigned to one of two groups. Each group was shown one of two different interviews with the same instructor. The instructor is a native French-speaking Belgian who spoke English with a noticeable accent. In the first video, the instructor presented himself as someone:

• respectful of his students’ intelligence and motives
• flexible in his approach to teaching
• enthusiastic about his subject matter

In the second interview, he presented himself as much more unlikable. He was cold and distrustful toward the students and was quite rigid in his teaching style.

After watching the videos, the subjects were asked to rate the lecturer on:

• physical appearance

His mannerisms and accent were kept the same in both versions of videos. The subjects were asked to rate the professor on an 8-point scale ranging from “like extremely” to “dislike extremely.” Subjects were also told that the researchers were interested in knowing “how much their liking for the teacher influenced the ratings they just made.” Other subjects were asked to identify how much the characteristics they just rated influenced their liking of the teacher.

After responding to the questionnaire, the respondents were puzzled about their reactions to the videotapes and to the questionnaire items. The students had no idea why they gave one lecturer higher ratings. Most said that how much they liked the lecturer had not affected their evaluation of his individual characteristics at all.

The interesting thing about this study is that people can understand the phenomenon, but they are unaware when it is occurring. Without realizing it, humans make judgments. Even when it is pointed out, they may still deny that it is a product of the halo effect phenomenon.

22. The Marshmallow Test

Study conducted by: walter mischel.

Study Conducted in 1972 at Stanford University

In his 1972 Marshmallow Experiment, children ages four to six were taken into a room where a marshmallow was placed in front of them on a table. Before leaving each of the children alone in the room, the experimenter informed them that they would receive a second marshmallow if the first one was still on the table after they returned in 15 minutes. The examiner recorded how long each child resisted eating the marshmallow and noted whether it correlated with the child’s success in adulthood. A small number of the 600 children ate the marshmallow immediately and one-third delayed gratification long enough to receive the second marshmallow.

In follow-up studies, Mischel found that those who deferred gratification were significantly more competent and received higher SAT scores than their peers. This characteristic likely remains with a person for life. While this study seems simplistic, the findings outline some of the foundational differences in individual traits that can predict success.

23. The Monster Study

Study conducted by: wendell johnson.

Study Conducted in 1939 at the University of Iowa

Experiment Details: The Monster Study received this negative title due to the unethical methods that were used to determine the effects of positive and negative speech therapy on children.

Wendell Johnson of the University of Iowa selected 22 orphaned children, some with stutters and some without. The children were in two groups. The group of children with stutters was placed in positive speech therapy, where they were praised for their fluency. The non-stutterers were placed in negative speech therapy, where they were disparaged for every mistake in grammar that they made.

As a result of the experiment, some of the children who received negative speech therapy suffered psychological effects and retained speech problems for the rest of their lives. They were examples of the significance of positive reinforcement in education.

The initial goal of the study was to investigate positive and negative speech therapy. However, the implication spanned much further into methods of teaching for young children.

24. Violinist at the Metro Experiment

Study conducted by: staff at the washington post.

Study Conducted in 2007 at a Washington D.C. Metro Train Station

During the study, pedestrians rushed by without realizing that the musician playing at the entrance to the metro stop was Grammy-winning musician, Joshua Bell. Two days before playing in the subway, he sold out at a theater in Boston where the seats average $100. He played one of the most intricate pieces ever written with a violin worth 3.5 million dollars. In the 45 minutes the musician played his violin, only 6 people stopped and stayed for a while. Around 20 gave him money, but continued to walk their normal pace. He collected $32.

The study and the subsequent article organized by the Washington Post was part of a social experiment looking at:

• the priorities of people

Gene Weingarten wrote about the social experiment: “In a banal setting at an inconvenient time, would beauty transcend?” Later he won a Pulitzer Prize for his story. Some of the questions the article addresses are:

• Do we perceive beauty?
• Do we stop to appreciate it?
• Do we recognize the talent in an unexpected context?

As it turns out, many of us are not nearly as perceptive to our environment as we might like to think.

25. Visual Cliff Experiment

Study conducted by: eleanor gibson and richard walk.

Study Conducted in 1959 at Cornell University

Experiment Details: In 1959, psychologists Eleanor Gibson and Richard Walk set out to study depth perception in infants. They wanted to know if depth perception is a learned behavior or if it is something that we are born with. To study this, Gibson and Walk conducted the visual cliff experiment.

They studied 36 infants between the ages of six and 14 months, all of whom could crawl. The infants were placed one at a time on a visual cliff. A visual cliff was created using a large glass table that was raised about a foot off the floor. Half of the glass table had a checker pattern underneath in order to create the appearance of a ‘shallow side.’

In order to create a ‘deep side,’ a checker pattern was created on the floor; this side is the visual cliff. The placement of the checker pattern on the floor creates the illusion of a sudden drop-off. Researchers placed a foot-wide centerboard between the shallow side and the deep side. Gibson and Walk found the following:

• Nine of the infants did not move off the centerboard.
• All of the 27 infants who did move crossed into the shallow side when their mothers called them from the shallow side.
• Three of the infants crawled off the visual cliff toward their mother when called from the deep side.
• When called from the deep side, the remaining 24 children either crawled to the shallow side or cried because they could not cross the visual cliff and make it to their mother.

What this study helped demonstrate is that depth perception is likely an inborn train in humans.

Among these experiments and psychological tests, we see boundaries pushed and theories taking on a life of their own. It is through the endless stream of psychological experimentation that we can see simple hypotheses become guiding theories for those in this field. The greater field of psychology became a formal field of experimental study in 1879, when Wilhelm Wundt established the first laboratory dedicated solely to psychological research in Leipzig, Germany. Wundt was the first person to refer to himself as a psychologist. Since 1879, psychology has grown into a massive collection of:

• methods of practice

It’s also a specialty area in the field of healthcare. None of this would have been possible without these and many other important psychological experiments that have stood the test of time.

• 20 Most Unethical Experiments in Psychology
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• 10 Things to Know About the Psychology of Psychotherapy

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After earning a Bachelor of Arts in Psychology from Rutgers University and then a Master of Science in Clinical and Forensic Psychology from Drexel University, Kristen began a career as a therapist at two prisons in Philadelphia. At the same time she volunteered as a rape crisis counselor, also in Philadelphia. After a few years in the field she accepted a teaching position at a local college where she currently teaches online psychology courses. Kristen began writing in college and still enjoys her work as a writer, editor, professor and mother.

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12 The Global Rise of Experimental Psychology

Vladimir mikhailovich bekhterev (1857–1927).

Vladimir Bekhterev was an incredibly versatile and successful Russian scientist in the 19th and early 20th centuries, whose contributions to his various fields of expertise made him a highly renowned scientist during his lifetime. Bekhterev was proficient in numerous scientific fields, namely neurophysiology, psychiatry, and experimental psychology.

Bekhterev was born in a small Russian village, to a clerk father and mother who encouraged schooling (Bekhterev, 1928, as cited in Lerner et al., 2005). He studied at the Military Medical Academy in St. Petersburg, receiving his medical doctorate in 1881, and working there as an associate professor until 1884, when he travelled to France and Germany to study neurology (Lerner et al., 2005). While in Germany, Bekhterev went to Leipzig to study neuroanatomy with Paul Flechsig and experimental psychology with Wilhelm Wundt (Lerner et al., 2005). When he returned to Russia in 1885, Bekhterev was appointed Professor and Chair of Psychiatry at the University of Kazan, where he established the first experimental psychology laboratory in Russia. In 1893, he returned to the Military Medical Academy in St. Petersburg as a Professor of Psychiatry and Chair of Mental and Neurological Diseases. In the same year, he published his book Conduction Paths in the Spinal Cord and Brain , which gained him international recognition for his unparalleled knowledge of the brain. Bekhterev was remarkably influential in the field of neurology due to his discoveries of novel brain structures (e.g., the superior vestibular nucleus) and being the first to describe certain diseases (e.g., Ankylosing spondylitis).

One of Bekhterev’s most significant contributions to experimental psychology was his “objective psychology”, which he later renamed “psychoreflexology”. This new psychological program situated the study of mental processes within a biological perspective. Bekhterev argued that the objective observation of neuropsychological processes, or “reflexes”, should be the focus of psychology (de Freitas Araujo, 2014). This definition of psychology shifted the focus away from the study of subjective or conscious processes (the subject matter and aim of Wundt’s experimental psychology) and toward an objective, experimental psychology. Over time, he extended the scope of his psychological program to encompass several domains, including genetics, education, pathology, and social psychology. Two prominent books written by Bekhterev on this subject were Objective Psychology , published in 1907, and General Principles of Human Reflexology , published in 1917. In addition to his previously mentioned accomplishments, Bekhterev founded the Society of Neurologists and Psychiatrists in 1892, the first Russian journal on nervous disease, the Neurology Bulletin , in 1892, the journal Review of Psychiatry Neurology and Experimental Psychology in 1896, and the Psychoneurological Institute in St. Petersburg in 1907 (Lerner et al., 2005).

Bekhterev’s influence in the fields of neurology, psychiatry, and experimental psychology is ever-lasting, despite the suppression of his work following his death in 1927. Bekhterev died under mysterious circumstances while attending the First Congress of Neurologists and Psychiatrists of Soviet Russia in Moscow (Lerner et al., 2005). The suspicious circumstances of Bekhterev’s death lead to speculation that he was poisoned by Russian authorities after examining Joseph Stalin and making an undesirable comment about Stalin’s mental state to his colleagues. Following Bekhterev’s untimely death, his works were removed from Soviet literature until Stalin’s death almost 30 years later. Nevertheless, Vladimir Bekhterev’s legacy has survived by way of his many neurological accomplishments and contributions to the establishment of experimental psychology in Russia.

Cavanaugh, R.  (2019, January). A brilliant career. A fatal error. Russian Life, 62 , 58–61.

de Freitas Araujo, S. (2014). The emergence and development of Bekhterev’s psychoreflexology in relation to Wundt’s experimental psychology. Journal of the History of the Behavioral Sciences, 50 , 189–210. https://doi.org/10.1002/jhbs.21653

Lerner, V., Margolin, J., & Witztum, E. (2005). Vladimir Bekhterev: His life, his work and the mystery of his death. History of Psychiatry, 16 , 217–227. https://doi.org/10.1177/0957154×05049611

Vladimir Mikhaylovich Bekhterev  (1857-1927). (2020, January 6). ACNR | Paper & Online Neurology Journal. https://www.acnr.co.uk/2020/01/vladimir-mikhaylovich-bekhterev-1857-1927/’

John Wallace Baird (1869–1919)

John Wallace Baird was a notable Canadian experimental psychologist and journal editor, as well as the first Canadian psychologist to serve as the president of the American Psychological Association (APA).

Born in Motherwell, Ontario, Baird was impaired with poor eyesight, hindering the rate of his progression through elementary and secondary school (Lahham & Green, 2012). Nevertheless, in 1893, Baird attended the University of Toronto, which had r(less than five years prior been equipped with an experimental psychology laboratory by James Mark Baldwin (Lahham & Green, 2012). Interestingly, it has been noted that Baird was a relatively average student throughout his undergraduate studies when considering his professional prominence in North American psychology during his career (Lahham & Green, 2012). Despite this, Baird earned his bachelor’s degree in 1897, with his thesis on abnormal colour vision, and remained at the University of Toronto as a laboratory assistant (Lahham & Green, 2012). Baird then left to study under Wilhelm Wundt in Leipzig, Germany. He studied under Wundt for just under a year before relocating to the United States and eventually beginning a fellowship position under E.B Titchener at Cornell University (Lahham & Green, 2012). There, he completed his Ph.D. in 1902 with a dissertation on depth perception (Lahham & Green, 2012). Baird remained at Cornell as a research assistant, during which he devoted his time solely to his vision research, culminating in the publication of The color sensitivity of the peripheral retina in 1905 (Lahham & Green, 2012). After leaving Cornell, Baird was appointed as an instructor at John Hopkins University (1904–1906), instructor and then Assistant Professor at the University of Illinois (1907–1909), and finally, director of the experimental psychology laboratory at Clark University (1910) (Lahham & Green, 2012).

The remaining nine years of Baird’s career saw a decline in research output, but his influence on experimental psychology during this period was far from inappreciable. In addition to the administrative responsibilities of running the psychological laboratory at Clark, Baird also taught a variety of introductory and advanced psychology courses, served editorial positions for two academic journals, and began publishing a yearly review of research on “memory, imagination, learning, and higher mental processes” (Lahham & Green, 2012). Moreover, in 1913, he translated Ernst Meumann’s Psychology of Learning from German and co-founded the Journal of Applied Psychology with G. Stanley Hall and Ludwig R. Geissler in 1917 (Lahham & Green, 2012). The following year, he was appointed President of the APA, during which time he also served as Vice-Chair of the National Research Council’s Psychological Committee (Lahham & Green, 2012). The purpose of this committee was to develop a rehabilitation program for disabled soldiers returning from WWI. Additionally, Baird had been selected many years earlier to become President of Clark University and Clark College in 1920 (Lahham & Green, 2012). However, as a result of his ongoing medical condition, Baird was hospitalized and passed away in February of 1919.

Despite his untimely passing, it is clear that Baird was held in high regard in the field of psychology in the United States. Throughout his career, he served editorial positions for the American Journal of Psychology , Psychological Bulletin , Journal of Educational Psychology , and the Journal of Applied Psychology , which he co-founded (Lahham & Green, 2012). Moreover, he attained membership in Titchener’s group of “Experimentalists”, the American Association for the Advancement of Science, and the American Academy of Arts and Sciences. Unfortunately, Baird’s impact on the field of psychology was shortly overshadowed by the rise of behaviourism, given his alignment with Titchener and the method of introspection (Lahham & Green, 2012). Nonetheless, Baird achieved immense success in American psychology, especially for a Canadian psychologist, and is thus a prominent figure in the history of Canadian psychology.

Lahham, D., & Green, C. D. (2013). John Wallace Baird: The First Canadian president of the American Psychological Association. Canadian Psychology/Psychologie Canadienne, 54 , 124–132. doi:10.1037/a0026286

Titchener, E. B. (1919). John Wallace Baird. Science, 49 , 393–394. doi:10.1126/science.49.1269.393

Contributors

• Kristen Arnold

Joseph Wolpe (1915-1997)

Joseph Wolpe was a South African psychologist and founder of the famous therapeutic technique, systematic desensitization.

Joseph Wolpe was born in Johannesburg, South Africa, into a family that valued education (O’Donohue et al., 2001). He grew up a studious child and became interested in the sciences as he entered high school (O’Donohue et al., 2001). Wolpe began his formal education by studying medicine at the University of Witwatersrand (Berger, 2005). Wolpe’s experiences volunteering as a military doctor during WWII moved him towards research in “war neurosis”, or what is now termed post-traumatic stress disorder (PTSD)(O’Donohue et al., 2001). He found the previous treatments for PTSD to be unsatisfactory and set out to find a treatment rooted in behaviourism that could help with anxiety and phobia-based disorders. Finally, Wolfe founded the first form of behaviour therapy, systematic desensitization, in which the individual is exposed to the thing they fear at various levels of intensity, however, the fear is not paired with negative consequences. For example, an individual who fears snakes may at first be shown a photo of a snake, then presented a snake in a terrarium, and lastly, the individual may be asked to touch a snake. Over time, the individual is able to build confidence against their fear and eventually overcome it. Systematic desensitization had high success rates for treating individuals, and this method is still used today.

In 1956, Berger went to Stanford to work at the Center for Advanced Studies in Behavioural Sciences, eventually moving permanently to the United States in 1960 (Salkovskis, 1998). In 1965, he began working in the department of behavioural sciences at Temple University, establishing a behavioural therapy unit (Salkovskis, 1989). Moreover, he was one of the founders of the Association for the Advancement of Behaviour Therapy in the 1960s and the Journal of Behaviour Therapy and Experimental Psychiatry in 1970. One of Wolpe’s students, Arnold Lazarus (1932–2013), published his dissertation on the application of systematic desensitization in groups in 1961 and was the first to use the term “behaviour therapy” in the literature.

Wolfe proved to the field that empirical methods can be used to develop therapeutic treatments, and established himself as a leading psychological innovator (Berger, 2005). His work on systematic desensitization, which he developed through combining knowledge from several branches of psychology, such as psychotherapy and behaviourism, demonstrates the importance of interdisciplinary research and collaboration for the progress of psychology.

Berger, V. (2005). Psychologists: Joseph Wolpe | PsychologistAnywhereAnytime.com . Psychologistanywhereanytime.com. http://psychologistanywhereanytime.com/famous_psychologist_and_psychologists/psychologist_famous_joseph_wolpe.htm

O’Donohue, W. T., Henderson, D. A., Hayes, S. C., Fisher, J. E., & Hayes, L. J. (2001). A history of the behavioral therapies : founders’ personal histories . Context Press.

Salkovskis, P. (1998). Changing the face of psychotherapy and common sense: Joseph Wolpe, 20 April 1915 – 4 December 1997. Behavioural and Cognitive Psychotherapy, 26 , 189–191. https://doi.org/10.1017/s1352465898000216

• Anmol Thind

Revisiting the History of Psychology Copyright © by Ali Hashemi and Amber Morrison. All Rights Reserved.

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Gustav Fechner

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• University of York - Biography of Gustav Theodor Fechner

Gustav Fechner (born April 19, 1801, Gross Särchen, near Muskau, Lusatia [Germany]—died November 18, 1887, Leipzig , Germany) was a German physicist and philosopher who was a key figure in the founding of psychophysics , the science concerned with quantitative relations between sensations and the stimuli producing them.

Although he was educated in biological science, Fechner turned to mathematics and physics . In 1834 he was appointed professor of physics at the University of Leipzig . His health broke down several years later; his partial blindness and painful sensitivity to light in all likelihood developed as a result of his gazing at the Sun during the study of visual afterimages (1839–40).

Pensioned modestly by the university in 1844, he began delving more deeply into philosophy and conceived of a highly animistic universe with God as its soul. He discussed his idea of a universal consciousness at length in a work containing his plan of psychophysics, Zend-Avesta: oder über die Dinge des Himmels und des Jenseits (1851; Zend-Avesta: On the Things of Heaven and the Hereafter ).

Fechner’s Elemente der Psychophysik, 2 vol. (1860; Elements of Psychophysics ), established his lasting importance in psychology . In this work he postulated that mind and body, though appearing to be separate entities, are actually different sides of one reality. He also developed experimental procedures, still useful in experimental psychology , for measuring sensations in relation to the physical magnitude of stimuli . Most important, he devised an equation to express the theory of the just-noticeable difference, advanced earlier by Ernst Heinrich Weber . This theory concerns the sensory ability to discriminate when two stimuli ( e.g., two weights) are just noticeably different from each other. Later research has shown, however, that Fechner’s equation is applicable within the midrange of stimulus intensity and then holds only approximately true.

From about 1865 he delved into experimental aesthetics and sought to determine by actual measurements which shapes and dimensions are most aesthetically pleasing.

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Classic Psychology Experiments

The history of psychology is filled with fascinating studies and classic psychology experiments that helped change the way we think about ourselves and human behavior. Sometimes the results of these experiments were so surprising they challenged conventional wisdom about the human mind and actions. In other cases, these experiments were also quite controversial.

Some of the most famous examples include Milgram's obedience experiment and Zimbardo's prison experiment. Explore some of these classic psychology experiments to learn more about some of the best-known research in psychology history.

Harlow’s Rhesus Monkey Experiments

In a series of controversial experiments conducted in the late 1950s and early 1960s, psychologist Harry Harlow demonstrated the powerful effects of love on normal development. By showing the devastating effects of deprivation on young rhesus monkeys , Harlow revealed the importance of love for healthy childhood development.

His experiments were often unethical and shockingly cruel, yet they uncovered fundamental truths that have heavily influenced our understanding of child development.

In one famous version of the experiments, infant monkeys were separated from their mothers immediately after birth and placed in an environment where they had access to either a wire monkey "mother" or a version of the faux-mother covered in a soft-terry cloth. While the wire mother provided food, the cloth mother provided only softness and comfort.

Harlow found that while the infant monkeys would go to the wire mother for food, they vastly preferred the company of the soft and comforting cloth mother. The study demonstrated that maternal bonds   were about much more than simply providing nourishment and that comfort and security played a major role in the formation of attachments .

Pavlov’s Classical Conditioning Experiments

The concept of classical conditioning is studied by every entry-level psychology student, so it may be surprising to learn that the man who first noted this phenomenon was not a psychologist at all. Pavlov was actually studying the digestive systems of dogs when he noticed that his subjects began to salivate whenever they saw his lab assistant.

What he soon discovered through his experiments was that certain responses (drooling) could be conditioned by associating a previously neutral stimulus (metronome or buzzer) with a stimulus that naturally and automatically triggers a response (food). Pavlov's experiments with dogs established classical conditioning.

The Asch Conformity Experiments

Researchers have long been interested in the degree to which people follow or rebel against social norms. During the 1950s, psychologist Solomon Asch conducted a series of experiments designed to demonstrate the powers of conformity in groups.  

The study revealed that people are surprisingly susceptible to going along with the group, even when they know the group is wrong.​ In Asch's studies, students were told that they were taking a vision test and were asked to identify which of three lines was the same length as a target line.

When asked alone, the students were highly accurate in their assessments. In other trials, confederate participants intentionally picked the incorrect line. As a result, many of the real participants gave the same answer as the other students, demonstrating how conformity could be both a powerful and subtle influence on human behavior.

Skinner's Operant Conditioning Experiments

Skinner studied how behavior can be reinforced to be repeated or weakened to be extinguished. He designed the Skinner Box where an animal, often a rodent, would be given a food pellet or an electric shock. A rat would learn that pressing a level delivered a food pellet. Or the rat would learn to press the lever in order to halt electric shocks.

Then, the animal may learn to associate a light or sound with being able to get the reward or halt negative stimuli by pressing the lever. Furthermore, he studied whether continuous, fixed ratio, fixed interval , variable ratio, and variable interval reinforcement led to faster response or learning.

Milgram’s Obedience Experiments

In Milgram's experiment , participants were asked to deliver electrical shocks to a "learner" whenever an incorrect answer was given. In reality, the learner was actually a confederate in the experiment who pretended to be shocked. The purpose of the experiment was to determine how far people were willing to go in order to obey the commands of an authority figure.

Milgram  found that 65% of participants were willing to deliver the maximum level of shocks   despite the fact that the learner seemed to be in serious distress or even unconscious.

Why This Experiment Is Notable

Milgram's experiment is one of the most controversial in psychology history. Many participants experienced considerable distress as a result of their participation and in many cases were never debriefed after the conclusion of the experiment. The experiment played a role in the development of ethical guidelines for the use of human participants in psychology experiments.

The Stanford Prison Experiment

Philip Zimbardo's famous experiment cast regular students in the roles of prisoners and prison guards. While the study was originally slated to last 2 weeks, it had to be halted after just 6 days because the guards became abusive and the prisoners began to show signs of extreme stress and anxiety.

Zimbardo's famous study was referred to after the abuses in Abu Ghraib came to light. Many experts believe that such group behaviors are heavily influenced by the power of the situation and the behavioral expectations placed on people cast in different roles.

It is worth noting criticisms of Zimbardo's experiment, however. While the general recollection of the experiment is that the guards became excessively abusive on their own as a natural response to their role, the reality is that they were explicitly instructed to mistreat the prisoners, potentially detracting from the conclusions of the study.

Van rosmalen L, Van der veer R, Van der horst FCP. The nature of love: Harlow, Bowlby and Bettelheim on affectionless mothers. Hist Psychiatry. 2020. doi:10.1177/0957154X19898997

Gantt WH . Ivan Pavlov . Encyclopaedia Brittanica .

Jeon, HL. The environmental factor within the Solomon Asch Line Test . International Journal of Social Science and Humanity. 2014;4(4):264-268. doi:10.7763/IJSSH.2014.V4.360 

Koren M. B.F. Skinner: The man who taught pigeons to play ping-pong and rats to pull levers . Smithsonian Magazine .

B.F. Skinner Foundation. A brief survey of operant behavior .

Gonzalez-franco M, Slater M, Birney ME, Swapp D, Haslam SA, Reicher SD. Participant concerns for the Learner in a Virtual Reality replication of the Milgram obedience study. PLoS ONE. 2018;13(12):e0209704. doi:10.1371/journal.pone.0209704

Zimbardo PG. Philip G. Zimbardo on his career and the Stanford Prison Experiment's 40th anniversary. Interview by Scott Drury, Scott A. Hutchens, Duane E. Shuttlesworth, and Carole L. White. Hist Psychol. 2012;15(2):161-170. doi:10.1037/a0025884

Le texier T. Debunking the Stanford Prison Experiment. Am Psychol. 2019;74(7):823-839. doi:10.1037/amp0000401

Perry G. Deception and illusion in Milgram's accounts of the Obedience Experiments . Theoretical & Applied Ethics . 2013;2(2):79-92.

Specter M. Drool: How Everyone Gets Pavlov Wrong . The New Yorker. 2014; November 24.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

CONCEPTUAL ANALYSIS article

The practice of experimental psychology: an inevitably postmodern endeavor.

• Department of Psychology, University of Regensburg, Regensburg, Germany

The aim of psychology is to understand the human mind and behavior. In contemporary psychology, the method of choice to accomplish this incredibly complex endeavor is the experiment. This dominance has shaped the whole discipline from the self-concept as an empirical science and its very epistemological and theoretical foundations, via research practice and the scientific discourse to teaching. Experimental psychology is grounded in the scientific method and positivism, and these principles, which are characteristic for modern thinking, are still upheld. Despite this apparently stalwart adherence to modern principles, experimental psychology exhibits a number of aspects which can best be described as facets of postmodern thinking although they are hardly acknowledged as such. Many psychologists take pride in being “real natural scientists” because they conduct experiments, but it is particularly difficult for psychologists to evade certain elements of postmodern thinking in view of the specific nature of their subject matter. Postmodernism as a philosophy emerged in the 20th century as a response to the perceived inadequacy of the modern approach and as a means to understand the complexities, ambiguities, and contradictions of the times. Therefore, postmodernism offers both valuable insights into the very nature of experimental psychology and fruitful ideas on improving experimental practice to better reflect the complexities and ambiguities of human mind and behavior. Analyzing experimental psychology along postmodern lines begins by discussing the implications of transferring the scientific method from fields with rather narrowly defined phenomena—the natural sciences—to a much broader and more heterogeneous class of complex phenomena, namely the human mind and behavior. This ostensibly modern experimental approach is, however, per se riddled with postmodern elements: (re-)creating phenomena in an experimental setting, including the hermeneutic processes of generating hypotheses and interpreting results, is no carbon copy of “reality” but rather an active construction which reflects irrevocably the pre-existing ideas of the investigator. These aspects, analyzed by using postmodern concepts like hyperreality and simulacra, did not seep in gradually but have been present since the very inception of experimental psychology, and they are necessarily inherent in its philosophy of science. We illustrate this theoretical analysis with the help of two examples, namely experiments on free will and visual working memory. The postmodern perspective reveals some pitfalls in the practice of experimental psychology. Furthermore, we suggest that accepting the inherently fuzzy nature of theoretical constructs in psychology and thinking more along postmodern lines would actually clarify many theoretical problems in experimental psychology.

Introduction

Postmodernism is, in essence, an attempt to achieve greater clarity in our perception, thinking, and behavior by scrutinizing their larger contexts and preconditions, based on the inextricably intertwined levels of both the individual and the society. Psychology also studies the human mind and behavior, which indicates that psychology should dovetail with postmodern approaches. In the 1990s and early 2000s, several attempts were made to introduce postmodern thought as potentially very fruitful ideas into general academic psychology ( Jager, 1991 ; Kvale, 1992 ; Holzman and Morss, 2000 ; Holzman, 2006 ). However, overall they were met with little response.

Postmodern thoughts have been taken up by several fringe areas of academic psychology, e.g., psychoanalysis ( Leffert, 2007 ; Jiménez, 2015 ; but see Holt, 2005 ), some forms of therapy and counseling ( Ramey and Grubb, 2009 ; Hansen, 2015 ), humanistic ( Krippner, 2001 ), feminist and gender ( Hare-Mustin and Marecek, 1988 ; Sinacore and Enns, 2005 ), or cultural psychology ( Gemignani and Peña, 2007 ).

However, there is resistance against suggestions to incorporate postmodern ideas into the methodology and the self-perception of psychology as academic—and scientific!—discipline. In fact, postmodern approaches are often rejected vehemently, sometimes even very vocally. For instance, Gergen (2001) argued that the “core tenets” of postmodernism are not at odds with those of scientific psychology but rather that they can enrich the discipline by opening up new possibilities. His suggestions were met with reservation and were even outright rejected on the following grounds: postmodernism, “like anthrax of the intellect, if allowed [our italics] into mainstream psychology, […] will poison the field” ( Locke, 2002 , 458), that it “wishes to return psychology to a prescientific subset of philosophy” ( Kruger, 2002 , 456), and that psychology “needs fewer theoretical and philosophical orientations, not more” ( Hofmann, 2002 , 462; see also Gergen ’s, 2001 , replies to the less biased and more informed commentaries on his article).

In the following years, and continuing the so-called science wars of the 1990s ( Segerstråle, 2000 ), several other attacks were launched against a perceived rise or even dominance of postmodern thought in psychology. Held(2007 ; see also the rebuttal by Martin and Sugarman, 2009 ) argued that anything postmodern would undermine rationality and destroy academic psychology. Similarly, postmodernism was identified—together with “radical environmentalism” and “pseudoscience” among other things—as a “key threat to scientific psychology” ( Lilienfeld, 2010 , 282), or as “inimical to progress in the psychology of science” ( Capaldi and Proctor, 2013 , 331). The following advice was given to psychologists: “We [psychologists] should also push back against the pernicious creep of these untested concepts into our field” ( Tarescavage, 2020 , 4). Furthermore, the term “postmodern” is even employed as an all-purpose invective in a popular scientific book by psychologist Steven Pinker (2018) .

Therefore, it seems that science and experimental psychology on the one hand and postmodern thinking on the other are irreconcilable opposites. However, following Gergen (2001) and Holtz (2020) , we argue that this dichotomy is only superficial because postmodernism is often misunderstood. A closer look reveals that experimental psychology contains many postmodern elements. Even more, there is reason to assume that a postmodern perspective may be beneficial for academic psychology: First, the practice of experimental psychology would be improved by integrating postmodern thinking because it reveals a side of the human psyche for which experimental psychology is mostly blind. Second, the postmodern perspective can tell us much about the epistemological and social background of experimental psychology and how this affects our understanding of the human psyche.

A Postmodern Perspective on Experimental Psychology

Experimental psychology and the modern scientific worldview.

It lies within the nature of humans to try to find out more about themselves and their world, but the so-called Scientific Revolution of the early modern period marks the beginning of a new era in this search for knowledge. The Scientific Revolution, which has led to impressive achievements in the natural sciences and the explanation of the physical world (e.g., Olby et al., 1991 ; Henry, 1997 ; Cohen, 2015 ; Osterlind, 2019 ), is based on the following principle: to “measure what can be measured and make measurable what cannot be measured.” This famous appeal—falsely attributed to Galileo Galilei but actually from the 19th century ( Kleinert, 2009 )—illustrates the two fundamental principles of modern science: First, the concept of “measurement” encompasses the idea that phenomena can be quantified, i.e., expressed numerically. Second, the concept of “causal connections” pertains to the idea that consistent, non-random relationships can be established between measurable phenomena. Quantification allows that relationships between phenomena can be expressed, calculated, and predicted in precise mathematical and numerical terms.

However, there are two important issues to be aware of. First, while it is not difficult to measure “evident” aspects, such as mass and distance, more complex phenomena cannot be measured easily. In such cases, it is therefore necessary to find ways of making these “elusive” phenomena measurable. This can often only be achieved by reducing complex phenomena to their simpler—and measurable!—elements. For instance, in order to measure memory ability precisely, possible effects of individual preexisting knowledge which introduce random variance and thus impreciseness have to be eliminated. Indeed, due to this reason, in many memory experiments, meaningless syllables are used as study material.

Second, it is not difficult to scientifically prove a causal relationship between a factor and an outcome if the relationship is simple, that is, if there is only one single factor directly influencing the outcome. In such a case, showing that a manipulation of the factor causes a change in the outcome is clear evidence for a causal relationship because there are no other factors which may influence the outcome as well. However, in situations where many factors influence an outcome in a complex, interactive way, proving a causal relationship is much more difficult. To prove the causal effect of one factor in such a situation the effects of all other factors—called confounding factors from the perspective of the factor of interest—have to be eliminated so that a change in the outcome can be truly attributed to a causal effect of the factor of interest. However, this has an important implication: The investigator has to divide the factors present in a given situation into interesting versus non-interesting factors with respect to the current context of the experiment. Consequently, while experiments reveal something about local causal relationships, they do not necessarily provide hints about the net effect of all causal factors present in the given situation.

The adoption of the principles of modern science has also changed psychology. Although the beginnings of psychology—as the study of the psyche —date back to antiquity, psychology as an academic discipline was established in the mid to late 19th century. This enterprise was also inspired by the success of the natural sciences, and psychology was explicitly modeled after this example by Wilhelm Wundt—the “father of experimental psychology”—although he emphasized the close ties to the humanities as well. The experiment quickly became the method of choice. There were other, more hermeneutic approaches during this formative phase of modern psychology, such as psychoanalysis or introspection according to the Würzburg School, but their impact on academic psychology was limited. Behaviorism emerged as a direct reaction against these perceived unscientific approaches, and its proponents emphasized the scientific character of their “new philosophy of psychology.” It is crucial to note that in doing so they also emphasized the importance of the experiment and the necessity of quantifying directly observable behavior in psychological research. Behaviorism quickly became a very influential paradigm which shaped academic psychology. Gestalt psychologists, whose worldview is radically different from behaviorism, also relied on experiments in their research. Cognitive psychology, which followed, complemented, and partly superseded behaviorism, relies heavily on the experiment as a means to gain insight into mental processes, although other methods such as modeling are employed as well. Interestingly, there is a fundamental difference between psychoanalysis and humanistic psychology, which do not rely on the experiment, and the other above-mentioned approaches as the former focus on the psychic functioning of individuals, whereas the latter focus more on global laws of psychic functioning across individuals. This is reflected in the fact that psychological laws in experimental psychology are established on the arithmetic means across examined participants—a difference we will elaborate on later in more detail. Today, psychology is the scientific —in the sense of empirical-quantitative—study of the human mind and behavior, and the experiment is often considered the gold standard in psychological research (e.g., Mandler, 2007 ; Goodwin, 2015 ; Leahey, 2017 ).

The experiment is closely associated with the so-called scientific method ( Haig, 2014 ; Nola and Sankey, 2014 ) and the epistemological tenets philosophy of positivism—in the sense as Martin (2003) ; Michell (2003) , and Teo (2018) explain—which sometimes exhibit characteristics of naïve empiricism. Roughly speaking, the former consists of observing, formulating hypotheses, and testing these hypotheses in experiments. The latter postulates that knowledge is based on sensory experience, that it is testable, independent of the investigator and therefore objective as it accurately depicts the world as it is. This means that in principle all of reality can not only be measured but eventually be entirely explained by science. This worldview is attacked by postmodern thinkers who contend that the world is far more complex and that the modern scientific approach cannot explain all of reality and its phenomena.

The Postmodern Worldview

Postmodern thinking (e.g., Bertens, 1995 ; Sim, 2011 ; Aylesworth, 2015 ) has gained momentum since the 1980s, and although neither the term “postmodernism” nor associated approaches can be defined in a unanimous or precise way, they are characterized by several intertwined concepts, attitudes, and aims. The most basic trait is a general skepticism and the willingness to question literally everything from the ground up—even going so far as to question not only the foundation of any idea, but also the question itself. This includes the own context, the chosen premises, thinking, and the use of language. Postmodernism therefore has a lot in common with science’s curiosity to understand the world: the skeptical attitude paired with the desire to discover how things really are.

Postmodern investigations often start by looking at the language and the broader context of certain phenomena due to the fact that language is the medium in which many of our mental activities—which subsequently influence our behavior—take place. Thus, the way we talk reveals something about how and why we think and act. Additionally, we communicate about phenomena using language, which in turn means that this discourse influences the way we think about or see those phenomena. Moreover, this discourse is embedded in a larger social and historical context, which also reflects back on the use of language and therefore on our perception and interpretation of certain phenomena.

Generally speaking, postmodern investigations aim at detecting and explaining how the individual is affected by societal influences and their underlying, often hidden ideas, structures, or mechanisms. As these influences are often fuzzy, contradictory, and dependent on their context, the individual is subject to a multitude of different causalities, and this already complex interplay is further complicated by the personal history, motivations, aims, or ways of thinking of the individual. Postmodernism attempts to understand all of this complexity as it is in its entirety.

The postmodern approaches have revealed three major general tendencies which characterize the contemporary world: First, societies and the human experience since the 20th century have displayed less coherence and conversely a greater diversity than the centuries before in virtually all areas, e.g., worldviews, modes of thinking, societal structures, or individual behavior. Second, this observation leads postmodern thinkers to the conclusion that the grand narratives which dominated the preceding centuries and shaped whole societies by providing frames of references have lost—at least partially—their supremacy and validity. Examples are religious dogmas, nationalism, industrialization, the notion of linear progress—and modern science because it works according to certain fundamental principles. Third, the fact that different but equally valid perspectives, especially on social phenomena or even whole worldviews, are possible and can coexist obviously affects the concepts of “truth,” “reality,” and “reason” in such a way that these concepts lose their immutable, absolute, and universal or global character, simply because they are expressions and reflections of a certain era, society, or worldview.

At this point, however, it is necessary to clarify a common misconception: Interpreting truth, reality, or reason as relative, subjective, and context-dependent—as opposed to absolute, objective, and context-independent—does naturally neither mean that anything can be arbitrarily labeled as true, real, or reasonable, nor, vice versa, that something cannot be true, real, or reasonable. For example, the often-quoted assumption that postmodernism apparently even denies the existence of gravity or its effects as everything can be interpreted arbitrarily or states that we cannot elucidate these phenomena with adequate accuracy because everything is open to any interpretation ( Sokal, 1996 ), completely misses the point.

First, postmodernism is usually not concerned with the laws of physics and the inanimate world as such but rather focuses on the world of human experience. However, the phenomenon itself, e.g., gravity, is not the same as our scientific knowledge of phenomena—our chosen areas of research, methodological paradigms, data, theories, and explanations—or our perception of phenomena, which are both the results of human activities. Therefore, the social context influences our scientific knowledge, and in that sense scientific knowledge is a social construction ( Hodge, 1999 ).

Second, phenomena from human experience, although probably more dependent on the social context than physical phenomena, cannot be interpreted arbitrarily either. The individual context—such as the personal history, motivations, aims, or worldviews—determines whether a certain behavior makes sense for a certain individual in a certain situation. As there are almost unlimited possible backgrounds, this might seem completely random or arbitrary from an overall perspective. But from the perspective of an individual the phenomenon in question may be explained entirely by a theory for a specific—and not universal—context.

As described above, the postmodern meta-perspective directly deals with human experience and is therefore especially relevant for psychology. Moreover, any discipline—including the knowledge it generates—will certainly benefit from understanding its own (social) mechanisms and implications. We will show below that postmodern thinking not only elucidates the broader context of psychology as an academic discipline but rather that experimental psychology exhibits a number of aspects which can best be described as facets of postmodern thinking although they are not acknowledged as such.

The Postmodern Context of Experimental Psychology

Paradoxically, postmodern elements have been present since the very beginning of experimental psychology although postmodernism gained momentum only decades later. One of the characteristics of postmodernism is the transplantation of certain elements from their original context to new contexts, e.g., the popularity of “Eastern” philosophies and practices in contemporary “Western” societies. These different elements are often juxtaposed and combined to create something new, e.g., new “westernized” forms of yoga ( Shearer, 2020 ).

Similarly, the founders of modern academic psychology took up the scientific method, which was originally developed in the context of the natural sciences, and transplanted it to the study of the human psyche in the hope to repeat the success of the natural sciences. By contrast, methods developed specifically in the context of psychology such as psychoanalysis ( Wax, 1995 ) or introspection according to the Würzburg School ( Hackert and Weger, 2018 ) have gained much less ground in academic psychology. The way we understand both the psyche and psychology has been shaped to a great extent by the transfer of the principles of modern science, namely quantitative measurement and experimental methods, although it is not evident per se that this is the best approach to elucidate mental and behavioral phenomena. Applying the methods of the natural sciences to a new and different context, namely to phenomena pertaining to the human psyche , is a truly postmodern endeavor because it juxtaposes two quite distinct areas and merges them into something new—experimental psychology.

The postmodern character of experimental psychology becomes evident on two levels: First, the subject matter—the human psyche —exhibits a postmodern character since mental and behavioral phenomena are highly dependent on the idiosyncratic contexts of the involved individuals, which makes it impossible to establish unambiguous general laws to describe them. Second, experimental psychology itself displays substantial postmodern traits because both its method and the knowledge it produces—although seemingly objective and rooted in the modern scientific worldview—inevitably contain postmodern elements, as will be shown below.

The Experiment as Simulacrum

The term “simulacrum” basically means “copy,” often in the sense of “inferior copy” or “phantasm/illusion.” However, in postmodern usage “simulacrum” has acquired a more nuanced and concrete meaning. “Simulacrum” is a key term in the work of postmodern philosopher Jean Baudrillard, who arguably presented the most elaborate theory on simulacra (1981/1994). According to Baudrillard, a simulacrum “is the reflection of a profound [‘real’] reality” (16/6). Simulacra, however, are more than identical carbon copies because they gain a life of their own and become “real” in the sense of becoming an own entity. For example, the personality a pop star shows on stage is not “real” in the sense that it is their “normal,” off-stage personality, but it is certainly “real” in the sense that it is perceived by the audience even if they are aware that it might be an “artificial” personality. Two identical cars can also be “different” for one might be used as a means of transportation while the other might be a status symbol. Even an honest video documentation of a certain event is not simply a copy of the events that took place because it lies within the medium video that only certain sections can be recorded from a certain perspective. Additionally, the playback happens in other contexts as the original event, which may also alter the perception of the viewer.

The post-structuralist—an approach closely associated with postmodernism—philosopher Roland Barthes pointed out another important aspect of simulacra. He contended that in order to understand something—an “object” in Barthes’ terminology—we necessarily create simulacra because we “ reconstruct [our italics] an ‘object’ in such a way as to manifest thereby the rules of functioning [⋯] of this object” ( Barthes, 1963 , 213/214). In other words, when we investigate an object—any phenomenon, either material, mental, or social—we have to perceive it first. This means that we must have some kind of mental representation of the phenomenon/object—and it is crucial to note that this representation is not the same thing as the “real” object itself. All our mental operations are therefore not performed on the “real” object but on mental representations of the object. We decompose a phenomenon in order to understand it, that is, we try to identify its components. In doing so, we effect a change in the object because our phenomenon is no longer the original phenomenon “as it is” for we are performing a mental operation on it, thereby transforming the original phenomenon. Identifying components may be simple, e.g., dividing a tree into roots, trunk, branches, and leaves may seem obvious or even “natural” but it is nevertheless us as investigators who create this structure—the tree itself is probably not aware of it. Now that we have established this structure, we are able to say that the tree consists of several components and name these components. Thus, we have introduced “new” elements into our understanding of the tree. This is the important point, even though the elements, i.e., the branches and leaves themselves “as they are,” have naturally always been “present.” Our understanding of “tree” has therefore changed completely because a tree is now something which is composed of several elements. In that sense, we have changed the original phenomenon by adding something—and this has all happened in our thinking and not in the tree itself. It is also possible to find different structures and different components for the tree, e.g., the brown and the green, which shows that we construct this knowledge.

Next, we can investigate the components to see how they interact with and relate to each other and to the whole system. Also, we can work out their functions and determine the conditions under which a certain event will occur. We can even expand the scope of our investigation and examine the tree in the context of its ecosystem. But no matter what we do or how sophisticated our investigation becomes, everything said above remains true here, too, because neither all these actions listed above nor the knowledge we gain from them are the object itself. Rather, we have added something to the object and the more we know about our object, the more knowledge we have constructed. This addition is what science—gaining knowledge—is all about. Or in the words of Roland Barthes: “the simulacrum is intellect added to object, and this addition has an anthropological value, in that it is man himself, his history, his situation, his freedom and the very resistance which nature offers to his mind” (1963/1972, 214/215).

In principle, this holds truth regarding all scientific investigations. But the more complex phenomena are, the more effort and personal contribution is required on behalf of the investigator to come up with structures, theories, or explanations. Paraphrasing Barthes: When dealing with complex phenomena, more intellect must be added to the object, which means in turn that there are more possibilities for different approaches and perspectives, that is, the constructive element becomes larger. As discussed previously, this does not mean that investigative and interpretative processes are arbitrary. But it is clear from this train of thought that “objectivity” or “truth” in a “positivist,” naïve empiricist “realist,” or absolute sense are not attainable. Nevertheless, we argue here that this is not a drawback, as many critics of postmodernism contend (see above), but rather an advantage because it allows more accurate scientific investigations of true-to-life phenomena, which are typically complex in the case of psychology.

The concepts of simulacra by Baudrillard and Barthes can be combined to provide a description of the experiment in psychology. Accordingly, our understanding of the concept of the “simulacrum” entails that scientific processes—indeed all investigative processes—necessarily need to duplicate the object of their investigation in order to understand it. In doing so, constructive elements are necessarily introduced. These elements are of a varying nature, which means that investigations of one and the same phenomenon may differ from each other and different investigations may find out different things about the phenomenon in question. These investigations then become entities on their own—in the Baudrillardian sense—and therefore simulacra.

In a groundbreaking article on “the meaning and limits of exact science” physicist Max Planck stated that “[a]n experiment is a question which science poses to nature, and a measurement is the recording of nature’s answer” ( Planck, 1949 , 325). The act of “asking a question” implies that the person asking the question has at least a general idea of what the answer might look like ( Heidegger, 1953 , §2). For example: When asking someone for their name, we obviously do not know what they are called, but we assume that they have a name and we also have an idea of how the concept “name” works. Otherwise we could not even conceive, let alone formulate, and pose our question. This highlights how a certain degree of knowledge and understanding of a concept is necessary so that we are able to ask questions about it. Likewise, we need to have a principal idea or assumption of possible mechanisms if we want to find out how more complex phenomena function. It is—at least at the beginning—irrelevant whether these ideas are factually correct or entirely wrong, for without them we would be unable to approach our subject matter in the first place.

The context of the investigator—their general worldview, their previous knowledge and understanding, and their social situation—obviously plays an important part in the process of forming a question which can be asked in the current research context. Although this context may be analyzed along postmodern lines in order to find out how it affects research, production of knowledge, and—when the knowledge is applied—possible (social) consequences, there is a much more profound implication pertaining to the very nature of the experiment as a means to gain knowledge.

Irrespective of whether it is a simple experiment in physics such as Galileo Galilei’s or an experiment on a complex phenomenon from social or cognitive psychology, the experiment is a situation which is specifically designed to answer a certain type of questions, usually causal relationships, such as: “Does A causally affect B?” Excluding the extremely complex discussion on the nature of causality and causation (e.g., Armstrong, 1997 ; Pearl, 2009 ; Paul and Hall, 2013 ), it is crucial to note that we need the experiment as a tool to answer this question. Although we may theorize about a phenomenon and infer causal relationships simply by observing, we cannot—at least according to the prevailing understanding of causality in the sciences—prove causal relationships without the experiment.

The basic idea of the experiment is to create conditions which differ in only one single factor which is suspected as a causal factor for an effect. The influence of all other potential causal relationships is kept identical because they are considered as confounding factors which are irrelevant from the perspective of the research question of the current experiment. Then, if a difference is found in the outcome between the experimental conditions, this is considered as proof that the aspect in question exerts indeed a causal effect. This procedure and the logic behind it are not difficult to understand. However, a closer look reveals that this is actually far from simple or obvious.

To begin with, an experiment is nothing which occurs “naturally” but a situation created for a specific purpose, i.e., an “artificial” situation, because other causal factors exerting influence in “real” life outside the laboratory are deliberately excluded and considered as “confounding” factors. This in itself shows that the experiment contains a substantial postmodern element because instead of creating something it rather re- creates it. This re-creation is of course based on phenomena from the “profound” reality—in the Baudrillardian sense—since the explicit aim is to find out something about this profound reality and not to create something new or something else. However, as stated above, this re-creation must contain constructive elements reflecting the presuppositions, conceptual-theoretical assumptions, and aims of the investigator. By focusing on one factor and by reducing the complexity of the profound reality, the practical operationalization and realization thus reflect both the underlying conceptual structure and the anticipated outcome as they are specifically designed to test for the suspected but hidden or obscured causal relationships.

At this point, another element becomes relevant, namely the all-important role of language, which is emphasized in postmodern thinking (e.g., Harris, 2005 ). Without going into the intricacies of semiotics, there is an explanatory gap ( Chalmers, 2005 )—to borrow a phrase from philosophy of mind—between the phenomenon on the one hand and the linguistic and/or mental representation of it on the other. This relationship is far from clear and it is therefore problematic to assume that our linguistic or mental representations—our words and the concepts they designate—are identical with the phenomena themselves. Although we cannot, at least according to our present knowledge and understanding, fully bridge this gap, it is essential to be aware of it in order to avoid some pitfalls, as will be shown in the examples below.

Even a seemingly simple word like “tree”—to take up once more our previous example—refers to a tangible phenomenon because there are trees “out there.” However, they come in all shapes and sizes, there are different kinds of trees, and every single one of them may be labeled as “tree.” Furthermore, trees are composed of different parts, and the leaf—although part of the tree—has its own word, i.e., linguistic and mental representation. Although the leaf is part of the tree—at least according to our concepts—it is unclear whether “tree” also somehow encompasses “leaf.” The same holds true for the molecular, atomic, or even subatomic levels, where there “is” no tree. Excluding the extremely complex ontological implications of this problem, it has become clear that we are referring to a certain level of granularity when using the word “tree.” The level of granularity reflects the context, aims, and concepts of the investigator, e.g., an investigation of the rain forest as an ecosystem will ignore the subatomic level.

How does this concern experimental psychology? Psychology studies intangible phenomena, namely mental and behavioral processes, such as cognition, memory, learning, motivation, emotion, perception, consciousness, etc. It is important to note that these terms designate theoretical constructs as, for example, memory cannot be observed directly. We may provide the subjects of an experiment a set of words to learn and observe later how many words they reproduce correctly. A theoretical construct therefore describes such relationships between stimulus and behavior, and we may draw conclusions from this observable data about memory. But neither the observable behavior of the subject, the resulting data, nor our conclusions are identical with memory itself.

This train of thought demonstrates the postmodern character of experimental psychology because we construct our knowledge. But there is more to it than that: Even by trying to define a theoretical construct as exactly as possible—e.g., memory as “the process of maintaining information over time” ( Matlin, 2012 , 505) or “the means by which we retain and draw on our past experiences to use this information in the present” ( Sternberg and Sternberg, 2011 , 187)—the explanatory gap between representation and phenomenon cannot be bridged. Rather, it becomes even more complicated because theoretical constructs are composed of other theoretical constructs, which results in some kind of self-referential circularity where constructs are defined by other constructs which refer to further constructs. In the definitions above, for instance, hardly any key term is self-evident and unambiguous for there are different interpretations of the constructs “process,” “maintaining,” “information,” “means,” “retain,” “draw on,” “experiences,” and “use” according to their respective contexts. Only the temporal expressions “over time,” “past,” and “present” are probably less ambiguous here because they are employed as non-technical, everyday terms. However, the definitions above are certainly not entirely incomprehensible—in fact, they are rather easy to understand in everyday language—and it is quite clear what the authors intend to express . The italics indicate constructive elements, which demonstrates that attempts to give a precise definition in the language of science result in fuzziness and self-reference.

Based on a story by Jorge Luis Borges, Baudrillard (1981) found an illustrative allegory: a map so precise that it portrays everything in perfect detail—but therefore inevitably so large that it shrouds the entire territory it depicts. Similarly, Taleb (2007) coined the term “ludic fallacy” for mistaking the model/map—in our context: experiments in psychology—for the reality/territory, that is, a mental or behavioral phenomenon. Similar to the functionality of a seemingly “imprecise” map which contains only the relevant landmarks so the user may find their way, the fuzziness of language poses no problems in everyday communication. So why is it a problem in experimental psychology? Since the nature of theoretical constructs in psychology lies precisely in their very fuzziness, the aim of reaching a high degree of granularity and precision in experimental psychology seems to be unattainable (see the various failed attempts to create “perfect” languages which might depict literally everything “perfectly,” e.g., Carapezza and D’Agostino, 2010 ).

Without speculating about ontic or epistemic implications, it is necessary to be aware of the explanatory gap and to refrain from identifying the experiment and the underlying operationalization with the theoretical construct. Otherwise, this gap is “filled” unintentionally and uncontrollably if the results of an experiment are taken as valid proof for a certain theoretical construct, which is actually fuzzy and potentially operationalizable in a variety of ways. If this is not acknowledged, words, such as “memory,” become merely symbols devoid of concrete meaning, much like a glass bead game—or in postmodern terminology: a hyperreality.

Experiments and Hyperreality

“Hyperreality” is another key term in the work of Jean Baudrillard (1981) and it denotes a concept closely related to the simulacrum. Accordingly, in modern society the simulacra are ubiquitous and they form a system of interconnected simulacra which refer to each other rather than to the real, thereby possibly hiding or replacing the real. Consequently, the simulacra become real in their own right and form a “more real” reality, namely the hyperreality. One may or may not accept Baudrillard’s conception, especially the all-embracing social and societal implications, but the core concept of “hyperreality” is nevertheless a fruitful tool to analyze experimental psychology. We have already seen that the experiment displays many characteristics of a simulacrum, so it is not surprising that the concept of hyperreality is applicable here as well, although in a slightly different interpretation than Baudrillard’s.

The hyperreal character of the experiment can be discussed on two levels: the experiment itself and the discourse wherein it is embedded.

On the level of the experiment itself, two curious observations must be taken into account. First, and in contrast to the natural sciences where the investigator is human and the subject matter (mostly) non-human and usually inanimate, in psychology both the investigator and the subject matter are human. This means that the subjects of the experiment, being autonomous persons, are not malleable or completely controllable by the investigator because they bring their own background, history, worldview, expectations, and motivations. They interpret the situation—the experiment—and act accordingly, but not necessarily in the way the investigator had planned or anticipated ( Smedslund, 2016 ). Therefore, the subjects create their own versions of the experiment, or, in postmodern terminology, a variety of simulacra, which may be more or less compatible with the framework of the investigator. This holds true for all subjects of an experiment, which means that the experiment as a whole may also be interpreted as an aggregation of interconnected simulacra—a hyperreality.

The hyperreal character becomes even more evident because what contributes in the end to the interpretation of the results of the experiment are not the actual performances and results of the individual subjects as they were intended by them but rather how their performances and results are handled, seen, and interpreted by the investigator. Even if the investigator tries to be as faithful as possible and aims at an exact and unbiased measurement—i.e., an exact copy—there are inevitably constructive elements which introduce uncertainty into the experiment. Investigators can never be certain what the subjects were actually doing and thinking so they must necessarily work with interpretations. Or in postmodern terms: Because the actual performances and results of the subjects are not directly available the investigators must deal with simulacra. These simulacra become the investigators’ reality and thus any further treatment—statistical analyses, interpretations, or discussions—becomes a hyperreality, that is, a set of interconnected simulacra which have become “real.”

On the level of the discourse wherein the experiment is embedded, another curious aspect also demonstrates the hyperreal character of experimental psychology. Psychology is, according to the standard definition, the scientific study of mental and behavioral processes of the individual (e.g., Gerrig, 2012 ). This definition contains two actually contradictory elements. On the one hand, the focus is on processes of the individual. On the other hand, the—scientific—method to elucidate these processes does not look at individuals per se but aggregates their individual experiences and transforms them into a “standard” experience. The results from experiments, our knowledge of the human psyche, reflect psychological functioning at the level of the mean across individuals. And even if we assume that the mean is only an estimator and not an exact description or prediction, the question remains open how de-individualized observations are related to the experience of an individual. A general mechanism, a law—which was discovered by abstracting from a multitude of individual experiences—is then ( re -)imposed in the opposite direction back onto the individual. In other words, a simulacrum—namely, the result of an experiment—is viewed and treated as reality, thus becoming hyperreal. Additionally, and simply because it is considered universally true, this postulated law acquires thereby a certain validity and “truth”—often irrespective of its actual, factual, or “profound” truth—on its own. Therefore, it can become impossible to distinguish between “profound” and “simulacral” truth, which is the hallmark of hyperreality.

Measuring the Capacity of the Visual Working Memory

Vision is an important sensory modality and there is extensive research on this area ( Hutmacher, 2019 ). Much of our daily experience is shaped by seeing a rich and complex world around us, and it is therefore an interesting question how much visual information we can store and process. Based on the development of a seminal experimental paradigm, Luck and Vogel (1997) have shown that visual working memory has a storage capacity of about four items. This finding is reported in many textbooks (e.g., Baddeley, 2007 ; Parkin, 2013 ; Goldstein, 2015 ) and has almost become a truism in cognitive psychology.

The experimental paradigm developed by Luck and Vogel (1997) is a prime example of an experiment which closely adheres to the scientific principles outlined above. In order to make a very broad and fuzzy phenomenon measurable, simple abstract forms are employed as visual stimuli—such as colored squares, triangles, or lines, usually on a “neutral,” e.g., gray, background—which can be counted in order to measure the capacity of visual working memory. Reducing the exuberant diversity of the “outside visual world” to a few abstract geometric forms is an extremely artificial situation. The obvious contrast between simple geometrical forms and the rich panorama of the “real” visual world illustrates the pitfalls of controlling supposed confounding variables, namely the incontrollable variety of the “real” world and how we see it. Precisely by abstracting and by excluding potential confounding variables it is possible to count the items and to make the capacity of the visual working memory measurable. But in doing so the original phenomenon—seeing the whole world—is lost. In other words: A simulacrum has been created.

The establishment of the experimental paradigm by Luck and Vogel has led to much research and sparked an extensive discussion how the limitation to only four items might be explained (see the summaries by Brady et al., 2011 ; Luck and Vogel, 2013 ; Ma et al., 2014 ; Schurgin, 2018 ). However, critically, several studies have shown that the situation is different when real-world objects are used as visual stimuli rather than simple abstract forms, revealing that the capacity of the visual working memory is higher for real-world objects ( Endress and Potter, 2014 ; Brady et al., 2016 ; Schurgin et al., 2018 ; Robinson et al., 2020 ; also Schurgin and Brady, 2019 ). Such findings show that the discourse about the mechanisms behind the limitations of the visual working memory is mostly about an artificial phenomenon which has no counterpart in “reality”—the perfect example of a hyperreality.

This hyperreal character does not mean that the findings of Luck and Vogel (1997) or similar experiments employing artificial stimuli are irrelevant or not “true.” The results are true—but it is a local truth, only valid for the specific context of specific experiments, and not a global truth which applies to the visual working memory in general . That is, speaking about “visual working memory” based on the paradigm of Luck and Vogel is a mistake because it is actually about “visual working memory for simple abstract geometrical forms in front of a gray background.”

Free Will and Experimental Psychology

The term “free will” expresses the idea of having “a significant kind of control [italics in the original] over one’s actions” ( O’Connor and Franklin, 2018 , n.p.). This concept has occupied a central position in Western philosophy since antiquity because it has far-reaching consequences for our self-conception as humans and our position in the world, including questions of morality, responsibility, and the nature of legal systems (e.g., Beebee, 2013 ; McKenna and Pereboom, 2016 ; O’Connor and Franklin, 2018 ). Being a topic of general interest, it is not surprising that experimental psychologists have tried to investigate free will as well.

The most famous study was conducted by Libet et al. (1983) , and this experiment has quickly become a focal point in the extensive discourse on free will because it provides empirical data and a scientific investigation. Libet et al.’s experiment seems to show that the subjective impression when persons consciously decide to act is in fact preceded by objectively measurable but unconscious physical processes. This purportedly proves that our seemingly voluntary actions are actually predetermined by physical processes because the brain has unconsciously reached a decision already before the person becomes aware of it and that our conscious intentions are simply grafted onto it. Therefore, we do not have a free will, and consequently much of our social fabric is based on an illusion. Or so the story goes.

This description, although phrased somewhat pointedly, represents a typical line of thought in the discourse on free will (e.g., the prominent psychologists Gazzaniga, 2011 ; Wegner, 2017 ; see Kihlstrom, 2017 , for further examples).

Libet’s experiment sparked an extensive and highly controversial discussion: For some authors, it is a refutation or at least threat to various concepts of free will, or, conversely, an indicator or even proof for some kind of material determinism. By contrast, other authors deny that the experiment refutes or counts against free will. Furthermore, a third group—whose position we adopt for our further argumentation—denies that Libet’s findings are even relevant for this question at all (for summaries of this complex and extensive discussion and various positions including further references see Nahmias, 2010 ; Radder and Meynen, 2013 ; Schlosser, 2014 ; Fischborn, 2016 ; Lavazza, 2016 ; Schurger, 2017 ). Libet’s own position, although not entirely consistent, opposes most notions of free will ( Roskies, 2011 ; Seifert, 2011 ). Given this background, it is not surprising that there are also numerous further experimental studies on various aspects of this subject area (see the summaries by Saigle et al., 2018 ; Shepard, 2018 ; Brass et al., 2019 ).

However, we argue that this entire discourse is best understood along postmodern lines as hyperreality and that Libet’s experiment itself is a perfect example of a simulacrum. A closer look at the concrete procedure of the experiment shows that Libet actually asked his participants to move their hand or finger “at will” while their brain activity was monitored with an EEG. They were instructed to keep watch in an introspective manner for the moment when they felt the “urge” to move their hand and to record this moment by indicating the clock-position of a pointer. This is obviously a highly artificial situation where the broad and fuzzy concept of “free will” is abstracted and reduced to the movement of the finger, the only degree of freedom being the moment of the movement. The question whether this is an adequate operationalization of free will is of paramount importance, and there are many objections that Libet’s setup fails to measure free will at all (e.g., Mele, 2007 ; Roskies, 2011 ; Kihlstrom, 2017 ; Brass et al., 2019 ).

Before Libet, there was no indication that the decision when to move a finger might be relevant for the concept of free will and the associated discourse. The question whether we have control over our actions referred to completely different levels of granularity. Free will was discussed with respect to questions such as whether we are free to live our lives according to our wishes or whether we are responsible for our actions in social contexts (e.g., Beebee, 2013 ; McKenna and Pereboom, 2016 ; O’Connor and Franklin, 2018 ), and not whether we lift a finger now or two seconds later. Libet’s and others’ jumping from very specific situations to far-reaching conclusions about a very broad and fuzzy theoretical construct illustrates that an extremely wide chasm between two phenomena, namely moving the finger and free will, is bridged in one fell swoop.

In other words, Libet’s experiment is a simulacrum as it duplicates a phenomenon from our day-to-day experience—namely free will—but in doing so the operationalization alters and reduces the theoretical construct. The outcome is a questionable procedure whose relationship to the phenomenon is highly controversial. Furthermore, the fact that, despite its tenuous connection to free will, Libet’s experiment sparked an extensive discussion on this subject reveals the hyperreal nature of the entire discourse because what is being discussed is not the actual question—namely free will—but rather a simulacrum. Everything else—the arguments, counter-arguments, follow-up experiments, and their interpretations—built upon Libet’s experiment are basically commentaries to a simulacrum and not on the real phenomena. Therefore, a hyperreality is created where the discourse revolves around entirely artificial phenomena, but where the arguments in this discussion refer back to and affect the real as suggestions are made to alter the legal system and our ideas of responsibility—which, incidentally, is not a question of empirical science but of law, ethics, and philosophy.

All of the above is not meant to say that this whole discourse is meaningless or even gratuitous—on the contrary, our understanding of the subject matter has greatly increased. Although our knowledge of free will has hardly increased, we have gained much insight into the hermeneutics and methodology—and pitfalls!—of investigations of free will, possible consequences on the individual and societal level, and the workings of scientific discourses. And this is exactly what postmodernism is about.

As shown above, there are a number of postmodern elements in the practice of experimental psychology: The prominent role of language, the gap between the linguistic or mental representation and the phenomenon, the “addition of intellect to the object,” the simulacral character of the experiment itself in its attempt to re-create phenomena, which necessarily transforms the “real” phenomenon due to the requirements of the experiment, and finally the creation of a hyperreality if experiments are taken as the “real” phenomenon and the scientific discourse becomes an exchange of symbolic expressions referring to the simulacra created in experiments, replacing the real. All these aspects did not seep gradually into experimental psychology in the wake of postmodernism but have been present since the very inception of experimental psychology as they are necessarily inherent in its philosophy of science.

Given these inherent postmodern traits in experimental psychology, it is puzzling that there is so much resistance against a perceived “threat” of psychology’s scientificness. Although a detailed investigation of the reasons lies outside the scope of this analysis, we suspect there are two main causes: First, an insufficient knowledge of the history of science and understanding of philosophy of science may result in idealized concepts of a “pure” natural science. Second, lacking familiarity with basic tenets of postmodern approaches may lead to the assumption that postmodernism is just an idle game of arbitrary words. However, “science” and “postmodernism” and their respective epistemological concepts are not opposites ( Gergen, 2001 ; Holtz, 2020 ). This is especially true for psychology, which necessarily contains a social dimension because not only the investigators are humans but also the very subject matter itself.

The (over-)reliance on quantitative-experimental methods in psychology, often paired with a superficial understanding of the philosophy of science behind it, has been criticized, either from the theoretical point of view (e.g., Bergmann and Spence, 1941 ; Hearnshaw, 1941 ; Petrie, 1971 ; Law, 2004 ; Smedslund, 2016 ) or because the experimental approach has failed to produce reliable, valid, and relevant applicable knowledge in educational psychology ( Slavin, 2002 ). It is perhaps symptomatic that a textbook teaching the principles of science for psychologists does not contain even one example from experimental psychology but employs only examples from physics, plus Darwin’s theory of evolution ( Wilton and Harley, 2017 ).

On the other hand, the postmodern perspective on experimental psychology provides insight into some pitfalls, as illustrated by the examples above. On the level of the experiment, the methodological requirements imply the creation of an artificial situation, which opens up a gap between the phenomenon as it is in reality and as it is concretely operationalized in the experimental situation. This is not a problem per se as long as is it clear—and clearly communicated!—that the results of the experiment are only valid in a certain context. The problems begin if the movement of a finger is mistaken for free will. Similarly, being aware that local causalities do not explain complex phenomena such as mental and behavioral processes in their entirety also prevents (over-) generalization, especially if communicated appropriately. These limitations make it clear that the experiment should not be made into an absolute or seen as the only valid way of understanding the psyche and the world.

On the level of psychology as an academic discipline, any investigation must select the appropriate level of granularity and strike a balance between the methodological requirements and the general meaning of the theoretical concept in question to find out something about the “real” world. If the level of granularity is so fine that results cannot be tied back to broader theoretical constructs rather than providing a helpful understanding of our psychological functioning, academic psychology is in danger of becoming a self-referential hyperreality.

The postmodern character of experimental psychology also allows for a different view on the so-called replication crisis in psychology. Authors contending that there is no replication crisis often employ arguments which exhibit postmodern elements, such as the emphasis on specific local conditions in experiments which may explain different outcomes of replication studies ( Stroebe and Strack, 2014 ; Baumeister, 2019 ). In other words, they invoke the simulacral character of experiments. This explanation may be valid or not, but the replication crisis has shown the limits of a predominantly experimental approach in psychology.

Acknowledging the postmodern nature of experimental psychology and incorporating postmodern thinking explicitly into our research may offer a way out of this situation. Our subject matter—the psyche —is extremely complex, ambiguous, and often contradictory. And postmodern thinking has proven capable of successfully explaining such phenomena (e.g., Bertens, 1995 ; Sim, 2011 ; Aylesworth, 2015 ). Thus, paradoxically, by accepting and considering the inherently fuzzy nature of theoretical constructs, they often become much clearer ( Ronzitti, 2011 ). Therefore, thinking more along postmodern lines in psychology would actually sharpen the theoretical and conceptual basis of experimental psychology—all the more as experimental psychology has inevitably been a postmodern endeavor since its very beginning.

Author Contributions

RM, CK, and CL developed the idea for this article. RM drafted the manuscript. CK and CL provided feedback and suggestions. All authors approved the manuscript for submission.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Keywords : postmodernism, experimental psychology, experiment, methodology, philosophy of science

Citation: Mayrhofer R, Kuhbandner C and Lindner C (2021) The Practice of Experimental Psychology: An Inevitably Postmodern Endeavor. Front. Psychol. 11:612805. doi: 10.3389/fpsyg.2020.612805

Received: 30 September 2020; Accepted: 26 November 2020; Published: 12 January 2021.

Reviewed by:

Copyright © 2021 Mayrhofer, Kuhbandner and Lindner. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Roland Mayrhofer, [email protected]

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What is Experimental Psychology?

Bryn Farnsworth

Table of Contents

The mind is a complicated place. Fortunately, the scientific method is perfectly equipped to deal with complexity. If we put these two things together we have the field of experimental psychology, broadly defined as the scientific study of the mind. The word “experimental” in this context means that tests are administered to participants, outcomes are measured, and comparisons are made.

More formally, this means that a group of participants are exposed to a stimulus (or stimuli), and their behavior in response is recorded. This behavior is compared to some kind of control condition, which could be either a neutral stimulus, the absence of a stimulus, or against a control group (who maybe do nothing at all).

Experimental psychology is concerned with testing theories of human thoughts, feelings, actions, and beyond – any aspect of being human that involves the mind. This is a broad category that features many branches within it (e.g. behavioral psychology , cognitive psychology). Below, we will go through a brief history of experimental psychology, the aspects that characterize it, and outline research that has gone on to shape this field.

A Brief History of Experimental Psychology

As with anything, and perhaps particularly with scientific ideas, it’s difficult to pinpoint the exact moment in which a thought or approach was conceived. One of the best candidates with which to credit the emergence of experimental psychology with is Gustav Fechner who came to prominence in the 1830’s. After completing his Ph.D in biology at the University of Leipzig [1], and continuing his work as a professor, he made a significant breakthrough in the conception of mental states.

Scientists later wrote about Fechner’s breakthrough for understanding perception: “An increase in the intensity of a stimulus, Fechner argued, does not produce a one-to-one increase in the intensity of the sensation … For example, adding the sound of one bell to that of an already ringing bell produces a greater increase in sensation than adding one bell to 10 others already ringing. Therefore, the effects of stimulus intensities are not absolute but are relative to the amount of sensation that already exists.” [2]

This ultimately meant that mental perception is responsive to the material world – the mind doesn’t passively respond to a stimulus (if that was the case, there would be a linear relationship between the intensity of a stimulus and the actual perception of it), but is instead dynamically responsive to it. This conception ultimately shapes much of experimental psychology, and the grounding theory: that the response of the brain to the environment can be quantified .

Fechner went on to research within this area for many subsequent years, testing new ideas regarding human perception. Meanwhile, another German scientist working in Heidelberg to the West, began his work on the problem of multitasking, and created the next paradigm shift for experimental psychology. The scientist was Wilhem Wundt, who had followed the work of Gustav Fechner.

Wilhem Wundt is often credited with being “the father of experimental psychology” and is the founding point for many aspects of it. He began the first experimental psychology lab, scientific journal, and ultimately formalized the approach as a science. Wundt set in stone what Fechner had put on paper.

The next scientist to advance the field of experimental psychology was influenced directly by reading Fechner’s book “ Elements of Psychophysics ”. Hermann Ebbinghaus, once again a German scientist, carried out the first properly formalized research into memory and forgetting, by using long lists of (mostly) nonsense syllables (such as: “VAW”, “TEL”, “BOC”) and recording how long it took for people to forget them.

Experiments using this list, concerning learning and memory, would take up much of Ebbinghaus’ career, and help cement experimental psychology as a science. There are many other scientists’ whose contributions helped pave the way for the direction, approach, and success of experimental psychology (Hermann von Helmholtz, Ernst Weber, and Mary Whiton Calkins, to name just a few) – all played a part in creating the field as we know it today. The work that they did defined the field, providing it with characteristics that we’ll now go through below.

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What Defines Experimental Psychology?

Defining any scientific field is in itself no exact science – there are inevitably aspects that will be missed. However, experimental psychology features at least three central components that define it: empiricism, falsifiability, and determinism . These features are central to experimental psychology but also many other fields within science.

Empiricism refers to the collection of data that can support or refute a theory. In opposition to purely theoretical reasoning, empiricism is concerned with observations that can be tested. It is based on the idea that all knowledge stems from observations that can be perceived, and data surrounding them can be collected to form experiments.

Falsifiability is a foundational aspect of all contemporary scientific work. Karl Popper , a 20th century philosopher, formalized this concept – that for any theory to be scientific there must be a way to falsify it. Otherwise, ludicrous, but unprovable claims could be made with equal weight as the most rigorously tested theories.

For example, the Theory of Relativity is scientific, for example, because it is possible that evidence could emerge to disprove it. This means that it can be tested. An example of an unfalsifiable argument is that the earth is younger than it appears, but that it was created to appear older than it is – any evidence against this is dismissed within the argument itself, rendering it impossible to falsify, and therefore untestable.

Determinism refers to the notion that any event has a cause before it. Applied to mental states, this means that the brain responds to stimuli, and that these responses can ultimately be predicted, given the correct data.

These aspects of experimental psychology run throughout the research carried out within this field. There are thousands of articles featuring research that have been carried out within this vein – below we will go through just a few of the most influential and well-cited studies that have shaped this field, and look to the future of experimental psychology.

Classic Studies in Experimental Psychology

Little albert.

One of the most notorious studies within experimental psychology was also one of the foundational pieces of research for behaviorism. Popularly known as the study of “Little Albert”, this experiment, carried out in 1920, focused on whether a baby could be made to fear a stimulus through conditioning (conditioning refers to the association of a response to a stimulus) [3].

The psychologist, John B. Watson , devised an experiment in which a baby was exposed to an unconditioned stimulus (in this case, a white rat) at the same time as a fear-inducing stimulus (the loud, sudden sound of a hammer hitting a metal bar). The repetition of this loud noise paired with the appearance of the white rat eventually led to the white rat becoming a conditioned stimulus – inducing the fear response even without the sound of the hammer.

While the study was clearly problematic, and wouldn’t (and shouldn’t!) clear any ethical boards today, it was hugely influential for its time, showing how human emotional responses can be shaped intentionally by conditioning – a feat only carried out with animals prior to this [4].

Watson, later referred to by a previous professor of his as a person “who thought too highly of himself and was more interested in his own ideas than in people” [5], was later revered and reviled in equal measure [2]. While his approach has since been rightly questioned, the study was a breakthrough for the conception of human behavior .

Asch’s Conformity Experiment

Three decades following Watson’s infamous experiment, beliefs were studied rather than behavior. Research carried out by Solomon Asch in 1951 showed how the influence of group pressure could make people say what they didn’t believe.

The goal was to examine how social pressures “induce individuals to resist or to yield to group pressures when the latter are perceived to be contrary to fact” [6]. Participant’s were introduced to a group of seven people in which, unbeknownst to them, all other individuals were actors hired by Asch. The task was introduced as a perceptual test, in which the length of lines was to be compared.

Sets of lines were shown to the group of participants – three on one card, one on another (as in the image above). The apparent task was to compare the three lines and say which was most like the single line in length. The answers were plainly obvious, and in one-on-one testing, participants got a correct answer over 99% of the time. Yet in this group setting, in which each actor, one after the other, incorrectly said an incorrect line out loud, the answers of the participants would change.

On average, around 38% of the answers the participants gave were incorrect – a huge jump from the less than 1% reported in non-group settings. The study was hugely influential for showing how our actions can be impacted by the environment we are placed in, particularly when it comes to social factors.

The Invisible Gorilla

If you don’t know this research from the title already, then it’s best experienced by watching the video below, and counting the number of ball passes.

The research of course has little to do with throwing a ball around, but more to do with the likelihood of not seeing the person in a gorilla costume who appears in the middle of the screen for eight seconds. The research, carried out in 1999, investigated how our attentional resources can impact how we perceive the world [7]. The term “ inattentional blindness ” refers to the effective blindness of our perceptions when our attention is engaged in another task.

The study tested how attentional processing is distributed, suggesting that objects that are more relevant to the task are more likely to be seen than objects which simply have close spatial proximity (very roughly – something expected is more likely to be seen even if it’s further away, whereas something unexpected is less likely to be seen even if it’s close).

The research not only showed the effect of our perceptions on our experience, but also has real-world implications. A replication of this study was done using eye tracking to record the visual search of radiologists who were instructed to look for nodules on one of several X-rays of lungs [8]. As the researchers state “A gorilla, 48 times the size of the average nodule, was inserted in the last case that was presented . Eighty-three percent of the radiologists did not see the gorilla.”

The original study, and research that followed since, has been crucial for showing how our expectations about the environment can shape our perceptions. Modern research has built upon each of the ideas and studies that have been carried out across almost 200 years.

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The Future of Experimental Psychology

The majority of this article has been concerned with what experimental psychology is, where it comes from, and what it has achieved so far. An inevitable follow-up question to this is – where is it going?

While predictions are difficult to make, there are at least indications. The best place to look is to experts in the field. Schultz and Schultz refer to modern psychology “as the science of behavior and mental processes instead of only behavior, a science seeking to explain overt behavior and its relationship to mental processes.” [2].

The Association for Psychological Science (APS) asked for forecasts from several prominent psychology researchers ( original article available here ), and received some of the following responses.

Lauri Nummenmaa (Assistant professor, Aalto University, Finland) predicts a similar path to Schultz and Schultz, stating that “a major aim of the future psychological science would involve re-establishing the link between the brain and behavior”. While Modupe Akinola (Assistant professor, Columbia Business School) hopes “that advancements in technology will allow for more unobtrusive ways of measuring bodily responses”.

Kristen Lindquist (Assistant professor of psychology, University of North Carolina School of Medicine) centers in on emotional responses, saying that “We are just beginning to understand how a person’s expectations, knowledge, and prior experiences shape his or her emotions. Emotions play a role in every moment of waking life from decisions to memories to feelings, so understanding emotions will help us to understand the mind more generally.”

Tal Yarkoni (Director, Psychoinformatics Lab, University of Texas at Austin) provides a forthright assessment of what the future of experimental psychology has in store: “psychological scientists will have better data, better tools, and more reliable methods of aggregation and evaluation”.

Whatever the future of experimental psychology looks like, we at iMotions aim to keep providing all the tools needed to carry out rigorous experimental psychology research.

I hope you’ve enjoyed reading this introduction to experimental psychology. If you’d like to get an even closer look at the background and research within this field, then download our free guide to human behavior below.

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[1] Shiraev, E. (2015). A history of psychology . Thousand Oaks, CA: SAGE Publications.

[2] Schultz, D. P., & Schultz, S. E. (2011). A History of Modern Psychology . Cengage, Canada.

[3] Watson, J.B.; Rayner, R. (1920). “Conditioned emotional reactions”. Journal of Experimental Psychology . 3 (1): 1–14. doi:10.1037/h0069608.

[4] Pavlov, I. P. (1928). Lectures on conditioned reflexes . (Translated by W.H. Gantt) London: Allen and Unwin.

[5] Brewer, C. L. (1991). Perspectives on John B. Watson . In G. A. Kimble, M. Wertheimer, & C. White (Eds.), Portraits of pioneers in psychology (pp. 171–186). Washington, DC: American Psychological Association.

[6] Asch, S.E. (1951). Effects of group pressure on the modification and distortion of judgments . In H. Guetzkow (Ed.), Groups, leadership and men(pp. 177–190). Pittsburgh, PA:Carnegie Press.

[7] Simons, D. and Chabris, C. (1999). Gorillas in our midst: sustained inattentional blindness for dynamic events. Perception , 28(9), pp.1059-1074.

[8] Drew, T., Võ, M. L-H., Wolfe, J. M. (2013). The invisible gorilla strikes again: sustained inattentional blindness in expert observers. Psychological Science, 24 (9):1848–1853. doi: 10.1177/0956797613479386.

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How scientific is cognitive load theory research compared to the rest of educational psychology.

1. How Scientific Is Cognitive Load Theory Research Compared to the Rest of Educational Psychology?

1.1. overview, 1.2. causal conclusions and recommendations for practice, 1.3. the present review, 2.1. journal selection and search process, 2.2. coding and analysis, 3.1. research designs, 3.2. recommendations for practice, 4. discussion, 4.1. limitations and future directions, 4.2. conclusions, author contributions, conflicts of interest.

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Share and Cite

Martella, A.M.; Lawson, A.P.; Robinson, D.H. How Scientific Is Cognitive Load Theory Research Compared to the Rest of Educational Psychology? Educ. Sci. 2024 , 14 , 920. https://doi.org/10.3390/educsci14080920

Martella AM, Lawson AP, Robinson DH. How Scientific Is Cognitive Load Theory Research Compared to the Rest of Educational Psychology? Education Sciences . 2024; 14(8):920. https://doi.org/10.3390/educsci14080920

Martella, Amedee Marchand, Alyssa P. Lawson, and Daniel H. Robinson. 2024. "How Scientific Is Cognitive Load Theory Research Compared to the Rest of Educational Psychology?" Education Sciences 14, no. 8: 920. https://doi.org/10.3390/educsci14080920

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