case study of a local school that promotes active learning

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case study of a local school that promotes active learning

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Study shows students in ‘active learning’ classrooms learn more than they think

For decades, there has been evidence that classroom techniques designed to get students to participate in the learning process produces better educational outcomes at virtually all levels.

And a new Harvard study suggests it may be important to let students know it.

The study , published Sept. 4 in the Proceedings of the National Academy of Sciences, shows that, though students felt as if they learned more through traditional lectures, they actually learned more when taking part in classrooms that employed so-called active-learning strategies.

Lead author Louis Deslauriers , the director of science teaching and learning and senior physics preceptor, knew that students would learn more from active learning. He published a key study in Science in 2011 that showed just that. But many students and faculty remained hesitant to switch to it.

“Often, students seemed genuinely to prefer smooth-as-silk traditional lectures,” Deslauriers said. “We wanted to take them at their word. Perhaps they actually felt like they learned more from lectures than they did from active learning.”

In addition to Deslauriers, the study is authored by director of sciences education and physics lecturer Logan McCarty , senior preceptor in applied physics Kelly Miller, preceptor in physics Greg Kestin , and Kristina Callaghan, now a physics lecturer at the University of California, Merced.

The question of whether students’ perceptions of their learning matches with how well they’re actually learning is particularly important, Deslauriers said, because while students eventually see the value of active learning, initially it can feel frustrating.

“Deep learning is hard work. The effort involved in active learning can be misinterpreted as a sign of poor learning,” he said. “On the other hand, a superstar lecturer can explain things in such a way as to make students feel like they are learning more than they actually are.”

To understand that dichotomy, Deslauriers and his co-authors designed an experiment that would expose students in an introductory physics class to both traditional lectures and active learning.

For the first 11 weeks of the 15-week class, students were taught using standard methods by an experienced instructor. In the 12th week, half the class was randomly assigned to a classroom that used active learning, while the other half attended highly polished lectures. In a subsequent class, the two groups were reversed. Notably, both groups used identical class content and only active engagement with the material was toggled on and off.

Following each class, students were surveyed on how much they agreed or disagreed with statements such as “I feel like I learned a lot from this lecture” and “I wish all my physics courses were taught this way.” Students were also tested on how much they learned in the class with 12 multiple-choice questions.

When the results were tallied, the authors found that students felt as if they learned more from the lectures, but in fact scored higher on tests following the active learning sessions. “Actual learning and feeling of learning were strongly anticorrelated,” Deslauriers said, “as shown through the robust statistical analysis by co-author Kelly Miller, who is an expert in educational statistics and active learning.”

Those results, the study authors are quick to point out, shouldn’t be interpreted as suggesting students dislike active learning. In fact, many studies have shown students quickly warm to the idea, once they begin to see the results. “In all the courses at Harvard that we’ve transformed to active learning,” Deslauriers said, “the overall course evaluations went up.”

Co-author Kestin, who in addition to being a physicist is a video producer with PBS’ NOVA, said, “It can be tempting to engage the class simply by folding lectures into a compelling ‘story,’ especially when that’s what students seem to like. I show my students the data from this study on the first day of class to help them appreciate the importance of their own involvement in active learning.”

McCarty, who oversees curricular efforts across the sciences, hopes this study will encourage more of his colleagues to embrace active learning.

“We want to make sure that other instructors are thinking hard about the way they’re teaching,” he said. “In our classes, we start each topic by asking students to gather in small groups to solve some problems. While they work, we walk around the room to observe them and answer questions. Then we come together and give a short lecture targeted specifically at the misconceptions and struggles we saw during the problem-solving activity. So far we’ve transformed over a dozen classes to use this kind of active-learning approach. It’s extremely efficient — we can cover just as much material as we would using lectures.”

A pioneer in work on active learning, Balkanski Professor of Physics and Applied Physics Eric Mazur hailed the study as debunking long-held beliefs about how students learn.

“This work unambiguously debunks the illusion of learning from lectures,” he said. “It also explains why instructors and students cling to the belief that listening to lectures constitutes learning. I recommend every lecturer reads this article.”

Dean of Science Christopher Stubbs , Samuel C. Moncher Professor of Physics and of Astronomy, was an early convert. “When I first switched to teaching using active learning, some students resisted that change. This research confirms that faculty should persist and encourage active learning. Active engagement in every classroom, led by our incredible science faculty, should be the hallmark of residential undergraduate education at Harvard.”

Ultimately, Deslauriers said, the study shows that it’s important to ensure that neither instructors nor students are fooled into thinking that lectures are the best learning option. “Students might give fabulous evaluations to an amazing lecturer based on this feeling of learning, even though their actual learning isn’t optimal,” he said. “This could help to explain why study after study shows that student evaluations seem to be completely uncorrelated with actual learning.”

This research was supported with funding from the Harvard FAS Division of Science.

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USING THE CASE STUDY METHODOLOGY TO PROMOTE ACTIVE LEARNING

Published 2015
Law, Business, Education

14 References

Effective case study methodologies in the management of it courses, use of presage-pedagogy-process-product model to assess the effectiveness of case study methodology in achieving learning outcomes, demystifying instructional innovation: the case of teaching with case studies, teaching policy theory and its application to practice using long structured case studies: an approach that deeply engages undergraduate students, teaching grade 5 life science with a case study approach, policy mapping: a new framework for teaching policymaking and policy design through case studies, a complex case: using the case study method to explore uncertainty and ambiguity in undergraduate business education, online collaborative case study learning, an insider perspective on implementing the harvard case study method in business teaching., incorporating case studies into an undergraduate genetics course., related papers.

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Effective Teaching Strategies

How to Implement Active Learning Strategies and Activities Into Your Classroom

July 22, 2021
Faculty Focus

Most of us think we know what active learning is. The word engagement quickly comes to mind. Or, we describe what it isn’t: passive learning. Definitions also abound, the one proposed by Bonwell and Eison in an early (and now classic) active learning monograph is widely referenced: involving “students in doing things and thinking about the things they are doing” (p. 2).

Those are fine places to start, but as interest in active learning has grown—and with its value now firmly established empirically—what gets labeled as active learning continues to expand. Carr, Palmer, and Hagel recently wrote, “Active learning is a very broad concept that covers or is associated with a wide variety of learning strategies” (p. 173). This may include experiential learning; learning by doing (hands-on learning); applied learning; service learning; peer teaching (in various contexts); lab work; role plays; case-based learning; group work of various kinds; technology-based strategies such as simulations, games, clickers, and various smart phone applications; and classroom interaction, with participation and discussion probably being the most widely used of all active learning approaches. Beyond strategies are theories such as constructivism that have spun off collections of student-centered approaches that promote student autonomy, self-direction, and self-regulation of learning.

What we next need to know about active learning won’t be all that easy to figure out, but it’s time we moved from generic understandings to the specific details.

Active Learning Strategies

Active learning can be an intimidating concept for educators. Many educators have heard the term but struggle to understand the true meaning of active learning and/or integrate active learning strategies within their classroom. Essentially, active learning involves including students in what they are learning, and fostering an environment that encourages them to think on these matters. Student involvement and metacognition, or thinking about thinking, are fundamental to one’s ability to understand active learning. The following articles and resources dive into active learning strategies for higher education and how you can start implementing them into your own course.

Free articles

Active Learning That Distracts from Learning
Three Active Learning Strategies That Push Students Beyond Memorization
Three Active Learning Strategies You Can Do in 10 Minutes or Less
Deeper Thinking about Active Learning
Lecture vs. Active Learning: Reframing the Conversation
Active Learning: In Need of Deeper Exploration
More Evidence That Active Learning Trumps Lecturing
Course Redesign Finds Right Blend of Content Delivery and Active Learning
Active Learning: Changed Attitudes and Improved Performance
Students Share Their Thoughts on Active Learning
Implementing Active Learning and Student-Centered Pedagogy

Teaching Professor articles (requires paid subscription)

Low-Risk Strategies to Promote Active Learning in Large Classes
Active Learning: A Perspective from Cognitive Psychology
Understanding Student Resistance to Active Learning
Active Learning Wins

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Think-pair-share.

You may have already heard of the think-pair-share assessment. The think-pair-share classroom assessment technique asks students to take one minute and write a response to a question. Then asks students to share their thoughts with a classmate, and finally, has pairs of students share with the class as a whole. The following provides alternatives to think-pair-share assessments and provides ways on how your students will go from blank stares to true engagement by using this activity. This shift increases the likelihood that students will learn more and that faculty won’t encounter awkward silence when initiating a discussion.

Choosing the Best Approach for Small Group Work
Cooperative Learning Structures and Deep Learning
Class Discussion: From Blank Stares to True Engagement
Five Ways to Engage Students in an Online Learning Environment
Modifying Strategies

Active Learning Classroom

A lot of us would wholeheartedly agree that active learning works. We have some familiarity with the research that supports it, and we’ve seen its positive effects in our classrooms. Done well, it engages students and overcomes the passivity that lectures regularly produce. John Dewey was right; students learn by doing better than by listening. The following explores definitions of active learning, its intensity, how it’s delivered, and how you can purposefully implement active learning into the classroom. Whether you’re planning to implement active learning into a large class, small class, or online course, we’ll explore active learning activities and active engagement in all aspects.

Active Learning: Surmounting the Challenges in a Large Class
Keeping Introverts in Mind in Your Active Learning Classroom
Active-Learning Ideas for Large Classes: Simple to Complex
Does Active Learning Work?
Incorporating Active Learning into the Online Classroom
Lecture or Active Learning? When to Decide
An Active Learning Exploration: Two-Stage Exams

Active Learning versus Passive Learning

Some students just don’t seem all that interested in learning. Most faculty work hard to help students find the missing motivation. They try a wide range of active learning strategies, and those approaches are successful with a lot of students but not all students. So how do you get students to go from passive learning to active learning without the dreaded resistance? Perhaps teachers can’t respond successfully unless they are knowledgeable about the sources of resistance to learning. Part of this is resistance for understandable reasons. Active learning means more work for students. They aren’t getting a neat, comprehensive package of teacher-generated examples, but are having to come up with their own. They aren’t watching the teacher solve all the problems, but are being put into groups to collectively work on the problems. Passive learning is easier than active learning, but then passivity doesn’t always result in learning, especially learning that lasts and knowledge that can be applied.

Putting Students in the Driver’s Seat: Technology Projects to Decrease Passivity
Student Learning: Six Causes of Resistance
From Passive Viewing to Active Learning: Simple Techniques for Applying Active Learning Strategies to Online Course Videos
Why Students Resist Active Learning

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Active Learning in Primary Classrooms

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What do we mean by Active Learning?
How can you inspire children to engage fully in their learning?
How can you plan and organise a curriculum that ensures that children are actively involved in the learning process?

This brand new text not only explores and examines the concept of active learning, but demonstrates how every teacher, new or experienced, can translate theory into practice and reap the rewards of children actively engaged in their own learning in the classroom.

Central to the book is the series of extended case studies, through which the authors highlight examples of effective teaching and learning across the whole primary curriculum. They provide practical examples of planning, teaching and assessing to encourage, inspire and give confidence to teach in creative, integrated and exciting ways.

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Published: 15 March 2021

Instructor strategies to aid implementation of active learning: a systematic literature review

Kevin A. Nguyen 1 ,
Maura Borrego 2 ,
Cynthia J. Finelli ORCID: orcid.org/0000-0001-9148-1492 3 ,
Matt DeMonbrun 4 ,
Caroline Crockett 3 ,
Sneha Tharayil 2 ,
Prateek Shekhar 5 ,
Cynthia Waters 6 &
Robyn Rosenberg 7

International Journal of STEM Education volume 8 , Article number: 9 ( 2021 ) Cite this article

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Despite the evidence supporting the effectiveness of active learning in undergraduate STEM courses, the adoption of active learning has been slow. One barrier to adoption is instructors’ concerns about students’ affective and behavioral responses to active learning, especially student resistance. Numerous education researchers have documented their use of active learning in STEM classrooms. However, there is no research yet that systematically analyzes these studies for strategies to aid implementation of active learning and address students’ affective and behavioral responses. In this paper, we conduct a systematic literature review and identify 29 journal articles and conference papers that researched active learning, affective and behavioral student responses, and recommended at least one strategy for implementing active learning. In this paper, we ask: (1) What are the characteristics of studies that examine affective and behavioral outcomes of active learning and provide instructor strategies? (2) What instructor strategies to aid implementation of active learning do the authors of these studies provide?

In our review, we noted that most active learning activities involved in-class problem solving within a traditional lecture-based course ( N = 21). We found mostly positive affective and behavioral outcomes for students’ self-reports of learning, participation in the activities, and course satisfaction ( N = 23). From our analysis of the 29 studies, we identified eight strategies to aid implementation of active learning based on three categories. Explanation strategies included providing students with clarifications and reasons for using active learning. Facilitation strategies entailed working with students and ensuring that the activity functions as intended. Planning strategies involved working outside of the class to improve the active learning experience.

To increase the adoption of active learning and address students’ responses to active learning, this study provides strategies to support instructors. The eight strategies are listed with evidence from numerous studies within our review on affective and behavioral responses to active learning. Future work should examine instructor strategies and their connection with other affective outcomes, such as identity, interests, and emotions.

Introduction

Prior reviews have established the effectiveness of active learning in undergraduate science, technology, engineering, and math (STEM) courses (e.g., Freeman et al., 2014 ; Lund & Stains, 2015 ; Theobald et al., 2020 ). In this review, we define active learning as classroom-based activities designed to engage students in their learning through answering questions, solving problems, discussing content, or teaching others, individually or in groups (Prince & Felder, 2007 ; Smith, Sheppard, Johnson, & Johnson, 2005 ), and this definition is inclusive of research-based instructional strategies (RBIS, e.g., Dancy, Henderson, & Turpen, 2016 ) and evidence-based instructional practices (EBIPs, e.g., Stains & Vickrey, 2017 ). Past studies show that students perceive active learning as benefitting their learning (Machemer & Crawford, 2007 ; Patrick, Howell, & Wischusen, 2016 ) and increasing their self-efficacy (Stump, Husman, & Corby, 2014 ). Furthermore, the use of active learning in STEM fields has been linked to improvements in student retention and learning, particularly among students from some underrepresented groups (Chi & Wylie, 2014 ; Freeman et al., 2014 ; Prince, 2004 ).

Despite the overwhelming evidence in support of active learning (e.g., Freeman et al., 2014 ), prior research has found that traditional teaching methods such as lecturing are still the dominant mode of instruction in undergraduate STEM courses, and low adoption rates of active learning in undergraduate STEM courses remain a problem (Hora & Ferrare, 2013 ; Stains et al., 2018 ). There are several reasons for these low adoption rates. Some instructors feel unconvinced that the effort required to implement active learning is worthwhile, and as many as 75% of instructors who have attempted specific types of active learning abandon the practice altogether (Froyd, Borrego, Cutler, Henderson, & Prince, 2013 ).

When asked directly about the barriers to adopting active learning, instructors cite a common set of concerns including the lack of preparation or class time (Finelli, Daly, & Richardson, 2014 ; Froyd et al., 2013 ; Henderson & Dancy, 2007 ). Among these concerns, student resistance to active learning is a potential explanation for the low rates of instructor persistence with active learning, and this negative response to active learning has gained increased attention from the academic community (e.g., Owens et al., 2020 ). Of course, students can exhibit both positive and negative responses to active learning (Carlson & Winquist, 2011 ; Henderson, Khan, & Dancy, 2018 ; Oakley, Hanna, Kuzmyn, & Felder, 2007 ), but due to the barrier student resistance can present to instructors, we focus here on negative student responses. Student resistance to active learning may manifest, for example, as lack of student participation and engagement with in-class activities, declining attendance, or poor course evaluations and enrollments (Tolman, Kremling, & Tagg, 2016 ; Winkler & Rybnikova, 2019 ).

We define student resistance to active learning (SRAL) as a negative affective or behavioral student response to active learning (DeMonbrun et al., 2017 ; Weimer, 2002 ; Winkler & Rybnikova, 2019 ). The affective domain, as it relates to active learning, encompasses not only student satisfaction and perceptions of learning but also motivation-related constructs such as value, self-efficacy, and belonging. The behavioral domain relates to participation, putting forth a good effort, and attending class. The affective and behavioral domains differ from much of the prior research on active learning that centers measuring cognitive gains in student learning, and systematic reviews are readily available on this topic (e.g., Freeman et al., 2014 ; Theobald et al., 2020 ). Schmidt, Rosenberg, and Beymer ( 2018 ) explain the relationship between affective, cognitive, and behavioral domains, asserting all three types of engagement are necessary for science learning, and conclude that “students are unlikely to exert a high degree of behavioral engagement during science learning tasks if they do not also engage deeply with the content affectively and cognitively” (p. 35). Thus, SRAL and negative affective and behavioral student response is a critical but underexplored component of STEM learning.

Recent research on student affective and behavioral responses to active learning has uncovered mechanisms of student resistance. Deslauriers, McCarty, Miller, Callaghan, and Kestin’s ( 2019 ) interviews of physics students revealed that the additional effort required by the novel format of an interactive lecture was the primary source of student resistance. Owens et al. ( 2020 ) identified a similar source of student resistance, which was to their carefully designed biology active learning intervention. Students were concerned about the additional effort required and the unfamiliar student-centered format. Deslauriers et al. ( 2019 ) and Owens et al. ( 2020 ) go a step further in citing self-efficacy (Bandura, 1982 ), mindset (Dweck & Leggett, 1988 ), and student engagement (Kuh, 2005 ) literature to explain student resistance. Similarly, Shekhar et al.’s ( 2020 ) review framed negative student responses to active learning in terms of expectancy-value theory (Wigfield & Eccles, 2000 ); students reacted negatively when they did not find active learning useful or worth the time and effort, or when they did not feel competent enough to complete the activities. Shekhar et al. ( 2020 ) also applied expectancy violation theory from physics education research (Gaffney, Gaffney, & Beichner, 2010 ) to explain how students’ initial expectations of a traditional course produced discomfort during active learning activities. To address both theories of student resistance, Shekhar et al. ( 2020 ) suggested that instructors provide scaffolding (Vygotsky, 1978 ) and support for self-directed learning activities. So, while framing the research as SRAL is relatively new, ideas about working with students to actively engage them in their learning are not. Prior literature on active learning in STEM undergraduate settings includes clues and evidence about strategies instructors can employ to reduce SRAL, even if they are not necessarily framed by the authors as such.

Recent interest in student affective and behavioral responses to active learning, including SRAL, is a relatively new development. But, given the discipline-based educational research (DBER) knowledge base around RBIS and EBIP adoption, we need not to reinvent the wheel. In this paper, we conduct a system review. Systematic reviews are designed to methodically gather and synthesize results from multiple studies to provide a clear overview of a topic, presenting what is known and what is not known (Borrego, Foster, & Froyd, 2014 ). Such clarity informs decisions when designing or funding future research, interventions, and programs. Relevant studies for this paper are scattered across STEM disciplines and in DBER and general education venues, which include journals and conference proceedings. Quantitative, qualitative, and mixed methods approaches have been used to understand student affective and behavioral responses to active learning. Thus, a systematic review is appropriate for this topic given the long history of research on the development of RBIS, EBIPs, and active learning in STEM education; the distribution of primary studies across fields and formats; and the different methods taken to evaluate students’ affective and behavioral responses.

Specifically, we conducted a systematic review to address two interrelated research questions. (1) What are the characteristics of studies that examine affective and behavioral outcomes of active learning and provide instructor strategies ? (2) What instructor strategies to aid implementation of active learning do the authors of these studies provide ? These two questions are linked by our goal of sharing instructor strategies that can either reduce SRAL or encourage positive student affective and behavioral responses. Therefore, the instructor strategies in this review are only from studies that present empirical data of affective and behavioral student response to active learning. The strategies we identify in this review will not be surprising to highly experienced teaching and learning practitioners or researchers. However, this review does provide an important link between these strategies and student resistance, which remains one of the most feared barriers to instructor adoption of RBIS, EBIPs, and other forms of active learning.

Conceptual framework: instructor strategies to reduce resistance

Recent research has identified specific instructor strategies that correlate with reduced SRAL and positive student response in undergraduate STEM education (Finelli et al., 2018 ; Nguyen et al., 2017 ; Tharayil et al., 2018 ). For example, Deslauriers et al. ( 2019 ) suggested that physics students perceive the additional effort required by active learning to be evidence of less effective learning. To address this, the authors included a 20-min lecture about active learning in a subsequent course offering. By the end of that course, 65% of students reported increased enthusiasm for active learning, and 75% said the lecture intervention positively impacted their attitudes toward active learning. Explaining how active learning activities contribute to student learning is just one of many strategies instructors can employ to reduce SRAL (Tharayil et al., 2018 ).

DeMonbrun et al. ( 2017 ) provided a conceptual framework for differentiating instructor strategies which includes not only an explanation type of instructor strategies (e.g., Deslauriers et al., 2019 ; Tharayil et al., 2018 ) but also a facilitation type of instructor strategies. Explanation strategies involve describing the purpose (such as how the activity relates to students’ learning) and expectations of the activity to students. Typically, instructors use explanation strategies before the in-class activity has begun. Facilitation strategies include promoting engagement and keeping the activity running smoothly once the activity has already begun, and some specific strategies include walking around the classroom or directly encouraging students. We use the existing categories of explanation and facilitation as a conceptual framework to guide our analysis and systematic review.

As a conceptual framework, explanation and facilitation strategies describe ways to aid the implementation of RBIS, EBIP, and other types of active learning. In fact, the work on these types of instructor strategies is related to higher education faculty development, implementation, and institutional change research perspectives (e.g., Borrego, Cutler, Prince, Henderson, & Froyd, 2013 ; Henderson, Beach, & Finkelstein, 2011 ; Kezar, Gehrke, & Elrod, 2015 ). As such, the specific types of strategies reviewed here are geared to assist instructors in moving toward more student-centered teaching methods by addressing their concerns of student resistance.

SRAL is a particular negative form of affective or behavioral student response (DeMonbrun et al., 2017 ; Weimer, 2002 ; Winkler & Rybnikova, 2019 ). Affective and behavioral student responses are conceptualized at the reactionary level (Kirkpatrick, 1976 ) of outcomes, which consists of how students feel (affective) and how they conduct themselves within the course (behavioral). Although affective and behavioral student responses to active learning are less frequently reported than cognitive outcomes, prior research suggests a few conceptual constructs within these outcomes.

Affective outcomes consist of any students’ feelings, preferences, and satisfaction with the course. Affective outcomes also include students’ self-reports of whether they thought they learned more (or less) during active learning instruction. Some relevant affective outcomes include students’ perceived value or utility of active learning (Shekhar et al., 2020 ; Wigfield & Eccles, 2000 ), their positivity toward or enjoyment of the activities (DeMonbrun et al., 2017 ; Finelli et al., 2018 ), and their self-efficacy or confidence with doing the in-class activity (Bandura, 1982 ).

In contrast, students’ behavioral responses to active learning consist of their actions and practices during active learning. This includes students’ attendance in the class, their participation , engagement, and effort with the activity, and students’ distraction or off-task behavior (e.g., checking their phones, leaving to use the restroom) during the activity (DeMonbrun et al., 2017 ; Finelli et al., 2018 ; Winkler & Rybnikova, 2019 ).

We conceptualize negative or low scores in either affective or behavioral student outcomes as an indicator of SRAL (DeMonbrun et al., 2017 ; Nguyen et al., 2017 ). For example, a low score in reported course satisfaction would be an example of SRAL. This paper aims to synthesize instructor strategies to aid implementation of active learning from studies that either address SRAL and its negative or low scores or relate instructor strategies to positive or high scores. Therefore, we also conceptualize positive student affective and behavioral outcomes as the absence of SRAL. For easy categorization of this review then, we summarize studies’ affective and behavioral outcomes on active learning to either being positive , mostly positive , mixed/neutral , mostly negative , or negative .

We conducted a systematic literature review (Borrego et al., 2014 ; Gough, Oliver, & Thomas, 2017 ; Petticrew & Roberts, 2006 ) to identify primary research studies that describe active learning interventions in undergraduate STEM courses, recommend one or more strategies to aid implementation of active learning, and report student response outcomes to active learning.

A systematic review was warranted due to the popularity of active learning and the publication of numerous papers on the topic. Multiple STEM disciplines and research audiences have published journal articles and conference papers on the topic of active learning in the undergraduate STEM classroom. However, it was not immediately clear which studies addressed active learning, affective and behavioral student responses, and strategies to aid implementation of active learning. We used the systematic review process to efficiently gather results of multiple types of studies and create a clear overview of our topic.

Definitions

For clarity, we define several terms in this review. Researchers refer to us, the authors of this manuscript. Authors and instructors wrote the primary studies we reviewed, and we refer to these primary studies as “studies” consistently throughout. We use the term activity or activities to refer to the specific in-class active learning tasks assigned to students. Strategies refer to the instructor strategies used to aid implementation of active learning and address student resistance to active learning (SRAL). Student response includes affective and behavioral responses and outcomes related to active learning. SRAL is an acronym for student resistance to active learning, defined here as a negative affective or behavioral student response. Categories or category refer to a grouping of strategies to aid implementation of active learning, such as explanation or facilitation. Excerpts are quotes from studies, and these excerpts are used as codes and examples of specific strategies.

Study timeline, data collection, and sample selection

From 2015 to 2016, we worked with a research librarian to locate relevant studies and conduct a keyword search within six databases: two multidisciplinary databases (Web of Science and Academic Search Complete), two major engineering and technology indexes (Compendex and Inspec), and two popular education databases (Education Source and Education Resource Information Center). We created an inclusion criteria that listed both search strings and study requirements:

Studies must include an in-class active learning intervention. This does not include laboratory classes. The corresponding search string was:

“active learning” or “peer-to-peer” or “small group work” or “problem based learning” or “problem-based learning” or “problem-oriented learning” or “project-based learning” or “project based learning” or “peer instruction” or “inquiry learning” or “cooperative learning” or “collaborative learning” or “student response system” or “personal response system” or “just-in-time teaching” or “just in time teaching” or clickers

Studies must include empirical evidence addressing student response to the active learning intervention. The corresponding search string was:

“affective outcome” or “affective response” or “class evaluation” or “course evaluation” or “student attitudes” or “student behaviors” or “student evaluation” or “student feedback” or “student perception” or “student resistance” or “student response”

Studies must describe a STEM course, as defined by the topic of the course, rather than by the department of the course or the major of the students enrolled (e.g., a business class for mathematics majors would not be included, but a mathematics class for business majors would).

Studies must be conducted in undergraduate courses and must not include K-12, vocational, or graduate education.

Studies must be in English and published between 1990 and 2015 as journal articles or conference papers.

In addition to searching the six databases, we emailed solicitations to U.S. National Science Foundation Improving Undergraduate STEM Education (NSF IUSE) grantees. Between the database searches and email solicitation, we identified 2364 studies after removing duplicates. Most studies were from the database search, as we received just 92 studies from email solicitation (Fig. 1 ).

PRISMA screening overview styled after Liberati et al. ( 2009 ) and Passow and Passow ( 2017 )

Next, we followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for screening studies with our inclusion criteria (Borrego et al., 2014 ; Petticrew & Roberts, 2006 ). From 2016 to 2018, a team of seven researchers conducted two rounds of review in Refworks: the first round with only titles and abstracts and the second round with the entire full-text. In both rounds, two researchers independently decided whether each study should be retained based on our inclusion criteria listed above. At the abstract review stage, if there was a disagreement between independent coders, we decided to pass the study on to the full text screening round. We screened a total of 2364 abstracts, and only 746 studies passed the first round of title and abstract verification (see PRISMA flow chart on Fig. 1 ). If there was still a disagreement between independent coders at the full text screening round, then the seven researchers met and discussed the study, clarified the inclusion criteria as needed to resolve potential future disagreements, and when necessary, took a majority vote (4 out of the 7 researchers) on the inclusion of the study. Due to the high number of coders, it was unusual to reach full consensus with all 7 coders, so a majority vote was used to finalize the inclusion of certain studies. We resolved these disagreements on a rolling basis, and depending on the round (abstract or full text), we disagreed about 10–15% of the time on the inclusion of a study. In both the first and second round of screening, studies were often excluded because they did not gather novel empirical data or evidence (inclusion criteria #2) or were not in an undergraduate STEM course (inclusion criteria #3 and #4). Only 412 studies met all our final inclusion criteria.

Coding procedure

From 2017 to 2018, a team of five researchers then coded these 412 studies for detailed information. To quickly gather information about all 412 studies and to answer the first part of our research question (What are the characteristics of studies that examine affective and behavioral outcomes of active learning and provide instructor strategies?), we developed an online coding form using Google Forms and Google Sheets. The five researchers piloted and refined the coding form over three rounds of pair coding, and 19 studies were used to test and revise early versions of the coding form. The final coding form (Borrego et al., 2018 ) used a mix of multiple choice and free response items regarding study characteristics (bibliographic information, type of publication, location of study), course characteristics (discipline, course level, number of students sampled, and type of active learning), methodology (main type of evidence collected, sample size, and analysis methods), study findings (types of student responses and outcomes), and strategy reported (if the study explicitly mentioned using strategies to implementation of active learning).

In the end, only 29 studies explicitly described strategies to aid implementation of active learning (Fig. 1 ), and we used these 29 studies as the dataset for this study. The main difference between these 29 studies and the other 383 studies was that these 29 studies explicitly described the ways authors implemented active learning in their courses to address SRAL or positive student outcomes. Although some readers who are experienced active learning instructors or educational researchers may view pedagogies and strategies as integrated, we found that most papers described active learning methods in terms of student tasks, while advice on strategies, if included, tended to appear separately. We chose to not over interpret passing mentions of how active learning was implemented as strategies recommended by the authors.

Analysis procedure for coding strategies

To answer our second research question (What instructor strategies to aid implementation of active learning do the authors of these studies provide?), we closely reviewed the 29 studies to analyze the strategies in more detail. We used Boyatzis’s ( 1998 ) thematic analysis technique to compile all mentions of instructor strategies to aid implementation of active learning and categorize these excerpts into certain strategies. This technique uses both deductive and inductive coding processes (Creswell & Creswell, 2017 ; Jesiek, Mazzurco, Buswell, & Thompson, 2018 ).

In 2018, three researchers reread the 29 studies, marking excerpts related to strategies independently. We found a total of 126 excerpts. The number of excerpts within each study ranged from 1 to 14 excerpts ( M = 4, SD = 3). We then took all the excerpts and pasted each into its own row in a Google Sheet. We examined the entire spreadsheet as a team and grouped similar excerpts together using a deductive coding process. We used the explanation and facilitation conceptual framework (DeMonbrun et al., 2017 ) and placed each excerpt into either category. We also assigned a specific strategy (i.e., describing the purpose of the activity, or encouraging students) from the framework for each excerpt.

However, there were multiple excerpts that did not easily match either category; we set these aside for the inductive coding process. We then reviewed all excerpts without a category and suggested the creation of a new third category, called planning . We based this new category on the idea that the existing explanation and facilitation conceptual framework did not capture strategies that occurred outside of the classroom. We discuss the specific strategies within the planning category in the Results. With a new category in hand, we created a preliminary codebook consisting of explanation, facilitation, and planning categories, and their respective specific strategies.

We then passed the spreadsheet and preliminary codebook to another researcher who had not previously seen the excerpts. The second researcher looked through all the excerpts and assigned categories and strategies, without being able to see the suggestions of the initial three researchers. The second researcher also created their own new strategies and codes, especially when a specific strategy was not presented in the preliminary codebook. All of their new strategies and codes were created within the planning category. The second researcher agreed on assigned categories and implementation strategies for 71% of the total excerpts. A researcher from the initial strategies coding met with the second researcher and discussed all disagreements. The high number of disagreements, 29%, arose from the specific strategies within the new third category, planning. Since the second researcher created new planning strategies, by default these assigned codes would be a disagreement. The two researchers resolved the disagreements by finalizing a codebook with the now full and combined list of planning strategies and the previous explanation and facilitation strategies. Finally, they started the last round of coding, and they coded the excerpts with the final codebook. This time, they worked together in the same coding sessions. Any disagreements were immediately resolved through discussion and updating of final strategy codes. In the end, all 126 excerpts were coded and kept.

Characteristics of the primary studies

To answer our first research question (What are the characteristics of studies that examine affective and behavioral outcomes of active learning and provide instructor strategies?), we report the results from our coding and systematic review process. We discuss characteristics of studies within our dataset below and in Table 1 .

Type of publication and research audience

Of the 29 studies, 11 studies were published in conference proceedings, while the remaining 18 studies were journal articles. Examples of journals included the European Journal of Engineering Education , Journal of College Science Teaching , and PRIMUS (Problems, Resources, and Issues in Mathematics Undergraduate Studies).

In terms of research audiences and perspectives, both US and international views were represented. Eighteen studies were from North America, two were from Australia, three were from Asia, and six were from Europe. For more details about the type of research publications, full bibliographic information for all 29 studies is included in the Appendix.

Types of courses sampled

Studies sampled different types of undergraduate STEM courses. In terms of course year, most studies sampled first-year courses (13 studies). All four course years were represented (4 second-year, 3 third-year, 2 fourth-year, 7 not reported). In regards to course discipline or major, all major STEM education disciplines were represented. Fourteen studies were conducted in engineering courses, and most major engineering subdisciplines were represented, such as electrical and computer engineering (4 studies), mechanical engineering (3 studies), general engineering courses (3 studies), chemical engineering (2 studies), and civil engineering (1 study). Thirteen studies were conducted in science courses (3 physics/astronomy, 7 biology, 3 chemistry), and 2 studies were conducted in mathematics or statistics courses.

For teaching methods, most studies sampled traditional courses that were primarily lecture-based but included some in-class activities. The most common activity was giving class time for students to do problem solving (PS) (21 studies). Students were instructed to either do problem solving in groups (16 studies) or individually (5 studies) and sometimes both in the same course. Project or problem-based learning (PBL) was the second most frequently reported activity with 8 studies, and the implementation of this teaching method ranged from end of term final projects to an entire project or problem-based course. The third most common activity was using clickers (4 studies) or having class discussions (4 studies).

Research design, methods, and outcomes

The 29 studies used quantitative (10 studies), qualitative (6 studies), or mixed methods (13 studies) research designs. Most studies contained self-made instructor surveys (IS) as their main source of evidence (20 studies). In contrast, only 2 studies used survey instruments with evidence of validity (IEV). Other forms of data collection included using institutions’ end of course evaluations (EOC) (10 studies), observations (5 studies), and interviews (4 studies).

Studies reported a variety of different measures for researching students’ affective and behavioral responses to active learning. The most common measure was students’ self-reports of learning (an affective outcome); twenty-one studies measured whether students thought they learned more or less due to the active learning intervention. Other common measures included whether students participated in the activities (16 studies, participation), whether they enjoyed the activities (15 studies, enjoyment), and if students were satisfied with the overall course experience (13 studies, course satisfaction). Most studies included more than one measure. Some studies also measured course attendance (4 studies) and students’ self-efficacy with the activities and relevant STEM disciplines (4 studies).

We found that the 23 of the 29 studies reported positive or mostly positive outcomes for their students’ affective and behavioral responses to active learning. Only 5 studies reported mixed/neutral study outcomes, and only one study reported negative student response to active learning. We discuss the implications of this lack of negative study outcomes and reports of SRAL in our dataset in the “Discussion” section.

To answer our second research question (What instructor strategies to aid implementation of active learning do the authors of these studies provide?), we provide descriptions, categories, and excerpts of specific strategies found within our systematic literature review.

Explanation strategies

Explanation strategies provide students with clarifications and reasons for using active learning (DeMonbrun et al., 2017 ). Within the explanation category, we identified two specific strategies: establish expectations and explain the purpose .

Establish expectations

Establishing expectations means setting the tone and routine for active learning at both the course and in-class activity level. Instructors can discuss expectations at the beginning of the semester, at the start of a class session, or right before the activity.

For establishing expectations at the beginning of the semester, studies provide specific ways to ensure students became familiar with active learning as early as possible. This included “introduc[ing] collaborative learning at the beginning of the academic term” (Herkert , 1997 , p. 450) and making sure that “project instructions and the data were posted fairly early in the semester, and the students were made aware that the project was an important part of their assessment” (Krishnan & Nalim, 2009 , p. 5).

McClanahan and McClanahan ( 2002 ) described the importance of explaining how the course will use active learning and purposely using the syllabus to do this:

Set the stage. Create the expectation that students will actively participate in this class. One way to accomplish that is to include a statement in your syllabus about your teaching strategies. For example: I will be using a variety of teaching strategies in this class. Some of these activities may require that you interact with me or other students in class. I hope you will find these methods interesting and engaging and that they enable you to be more successful in this course . In the syllabus, describe the specific learning activities you plan to conduct. These descriptions let the students know what to expect from you as well as what you expect from them (emphasis added, p. 93).

Early on, students see that the course is interactive, and they also see the activities required to be successful in the course.

These studies and excerpts demonstrate the importance of explaining to students how in-class activities relate to course expectations. Instructors using active learning should start the semester with clear expectations for how students should engage with activities.

Explain the purpose

Explaining the purpose includes offering students reasons why certain activities are being used and convincing them of the importance of participating.

One way that studies explained the purpose of the activities was by leveraging and showing assessment data on active learning. For example, Lenz ( 2015 ) dedicated class time to show current students comments from previous students:

I spend the first few weeks reminding them of the research and of the payoff that they will garner and being a very enthusiastic supporter of the [active learning teaching] method. I show them comments I have received from previous classes and I spend a lot of time selling the method (p. 294).

Providing current students comments from previous semesters may help students see the value of active learning. Lake ( 2001 ) also used data from prior course offerings to show students “the positive academic performance results seen in the previous use of active learning” on the first day of class (p. 899).

However, sharing the effectiveness of the activities does not have to be constrained to the beginning of the course. Autin et al. ( 2013 ) used mid-semester test data and comparisons to sell the continued use of active learning to their students. They said to students:

Based on your reflections, I can see that many of you are not comfortable with the format of this class. Many of you said that you would learn better from a traditional lecture. However, this class, as a whole, performed better on the test than my other [lecture] section did. Something seems to be working here (p. 946).

Showing students’ comparisons between active learning and traditional lecture classes is a powerful way to explain how active learning is a benefit to students.

Explaining the purpose of the activities by sharing course data with students appears to be a useful strategy, as it tells students why active learning is being used and convinces students that active learning is making a difference.

Facilitation strategies

Facilitation strategies ensure the continued engagement in the class activities once they have begun, and many of the specific strategies within this category involve working directly with students. We identified two strategies within the facilitation category: approach students and encourage students .

Approach students

Approaching students means engaging with students during the activity. This includes physical proximity and monitoring students, walking around the classroom, and providing students with additional feedback, clarifications, or questions about the activity.

Several studies described how instructors circulated around the classroom to check on the progress of students during an activity. Lenz ( 2015 ) stated this plainly in her study, “While the students work on these problems I walk around the room, listening to their discussions” (p. 284). Armbruster et al. ( 2009 ) described this strategy and noted positive student engagement, “During each group-work exercise the instructor would move throughout the classroom to monitor group progress, and it was rare to find a group that was not seriously engaged in the exercise” (p. 209). Haseeb ( 2011 ) combined moving around the room and approaching students with questions, and they stated, “The instructor moves around from one discussion group to another and listens to their discussions, ask[ing] provoking questions” (p. 276). Certain group-based activities worked better with this strategy, as McClanahan and McClanahan ( 2002 ) explained:

Breaking the class into smaller working groups frees the professor to walk around and interact with students more personally. He or she can respond to student questions, ask additional questions, or chat informally with students about the class (p. 94).

Approaching students not only helps facilitate the activity, but it provides a chance for the instructor to work with students more closely and receive feedback. Instructors walking around the classroom ensure that both the students and instructor continue to engage and participate with the activity.

Encourage students

Encouraging students includes creating a supportive classroom environment, motivating students to do the activity, building respect and rapport with students, demonstrating care, and having a positive demeanor toward students’ success.

Ramsier et al. ( 2003 ) provided a detailed explanation of the importance of building a supportive classroom environment:

Most of this success lies in the process of negotiation and the building of mutual respect within the class, and requires motivation, energy and enthusiasm on behalf of the instructor… Negotiation is the key to making all of this work, and building a sense of community and shared ownership. Learning students’ names is a challenge but a necessary part of our approach. Listening to student needs and wants with regard to test and homework due dates…projects and activities, etc. goes a long way to build the type of relationships within the class that we need in order to maintain and encourage performance (pp. 16–18).

Here, the authors described a few specific strategies for supporting a positive demeanor, such as learning students’ names and listening to student needs and wants, which helped maintain student performance in an active learning classroom.

Other ways to build a supportive classroom environment were for instructors to appear more approachable. For example, Bullard and Felder ( 2007 ) worked to “give the students a sense of their instructors as somewhat normal and approachable human beings and to help them start to develop a sense of community” (p. 5). As instructors and students become more comfortable working with each other, instructors can work toward easing “frustration and strong emotion among students and step by step develop the students’ acceptance [of active learning]” (Harun, Yusof, Jamaludin, & Hassan, 2012 , p. 234). In all, encouraging students and creating a supportive environment appear to be useful strategies to aid implementation of active learning.

Planning strategies

The planning category encompasses strategies that occur outside of class time, distinguishing it from the explanation and facilitation categories. Four strategies fall into this category: design appropriate activities , create group policies , align the course , and review student feedback .

Design appropriate activities

Many studies took into consideration the design of appropriate or suitable activities for their courses. This meant making sure the activity was suitable in terms of time, difficulty, and constraints of the course. Activities were designed to strike a balance between being too difficult and too simple, to be engaging, and to provide opportunities for students to participate.

Li et al. ( 2009 ) explained the importance of outside-of-class planning and considering appropriate projects: “The selection of the projects takes place in pre-course planning. The subjects for projects should be significant and manageable” (p. 491). Haseeb ( 2011 ) further emphasized a balance in design by discussing problems (within problem-based learning) between two parameters, “the problem is deliberately designed to be open-ended and vague in terms of technical details” (p. 275). Armbruster et al. ( 2009 ) expanded on the idea of balanced activities by connecting it to group-work and positive outcomes, and they stated, “The group exercises that elicited the most animated student participation were those that were sufficiently challenging that very few students could solve the problem individually, but at least 50% or more of the groups could solve the problem by working as a team” (p. 209).

Instructors should consider the design of activities outside of class time. Activities should be appropriately challenging but achievable for students, so that students remain engaged and participate with the activity during class time.

Create group policies

Creating group policies means considering rules when using group activities. This strategy is unique in that it directly addresses a specific subset of activities, group work. These policies included setting team sizes and assigning specific roles to group members.

Studies outlined a few specific approaches for assigning groups. For example, Ramsier et al. ( 2003 ) recommended frequently changing and randomizing groups: “When students enter the room on these days they sit in randomized groups of 3 to 4 students. Randomization helps to build a learning community atmosphere and eliminates cliques” (p. 4). Another strategy in combination with frequent changing of groups was to not allow students to select their own groups. Lehtovuori et al. ( 2013 ) used this to avoid problems of freeriding and group dysfunction:

For example, group division is an issue to be aware of...An easy and safe solution is to draw lots to assign the groups and to change them often. This way nobody needs to suffer from a dysfunctional group for too long. Popular practice that students self-organize into groups is not the best solution from the point of view of learning and teaching. Sometimes friendly relationships can complicate fair division of responsibility and work load in the group (p. 9).

Here, Lehtovuori et al. ( 2013 ) considered different types of group policies and concluded that frequently changing groups worked best for students. Kovac ( 1999 ) also described changing groups but assigned specific roles to individuals:

Students were divided into groups of four and assigned specific roles: manager, spokesperson, recorder, and strategy analyst. The roles were rotated from week to week. To alleviate complaints from students that they were "stuck in a bad group for the entire semester," the groups were changed after each of the two in-class exams (p. 121).

The use of four specific group roles is a potential group policy, and Kovac ( 1999 ) continued the trend of changing group members often.

Overall, these studies describe the importance of thinking about ways to implement group-based activities before enacting them during class, and they suggest that groups should be reconstituted frequently. Instructors using group activities should consider whether to use specific group member policies before implementing the activity in the classroom.

Align the course

Aligning the course emphasizes the importance of purposely connecting multiple parts of the course together. This strategy involves planning to ensure students are graded on their participation with the activities as well as considering the timing of the activities with respect to other aspects of the course.

Li et al. ( 2009 ) described aligning classroom tasks by discussing the importance of timing, and they wrote, “The coordination between the class lectures and the project phases is very important. If the project is assigned near the directly related lectures, students can instantiate class concepts almost immediately in the project and can apply the project experience in class” (p. 491).

Krishnan and Nalim ( 2009 ) aligned class activities with grades to motivate students and encourage participation: “The project was a component of the course counting for typically 10-15% of the total points for the course grade. Since the students were told about the project and that it carried a significant portion of their grade, they took the project seriously” (p. 4). McClanahan and McClanahan ( 2002 ) expanded on the idea of using grades to emphasize the importance of active learning to students:

Develop a grading policy that supports active learning. Active learning experiences that are important enough to do are important enough to be included as part of a student's grade…The class syllabus should describe your grading policy for active learning experiences and how those grades factor into the student's final grade. Clarify with the students that these points are not extra credit. These activities, just like exams, will be counted when grades are determined (p. 93).

Here, they suggest a clear grading policy that includes how activities will be assessed as part of students’ final grades.

de Justo and Delgado ( 2014 ) connected grading and assessment to learning and further suggested that reliance on exams may negatively impact student engagement:

Particular attention should be given to alignment between the course learning outcomes and assessment tasks. The tendency among faculty members to rely primarily on written examinations for assessment purposes should be overcome, because it may negatively affect students’ engagement in the course activities (p. 8).

Instructors should consider their overall assessment strategies, as overreliance on written exams could mean that students engage less with the activities.

When planning to use active learning, instructors should consider how activities are aligned with course content and students’ grades. Instructors should decide before active learning implementation whether class participation and engagement will be reflected in student grades and in the course syllabus.

Review student feedback

Reviewing student feedback includes both soliciting feedback about the activity and using that feedback to improve the course. This strategy can be an iterative process that occurs over several course offerings.

Many studies utilized student feedback to continuously revise and improve the course. For example, Metzger ( 2015 ) commented that “gathering and reviewing feedback from students can inform revisions of course design, implementation, and assessment strategies” (p. 8). Rockland et al. ( 2013 ) further described changing and improving the course in response to student feedback, “As a result of these discussions, the author made three changes to the course. This is the process of continuous improvement within a course” (p. 6).

Herkert ( 1997 ) also demonstrated the use of student feedback for improving the course over time: “Indeed, the [collaborative] learning techniques described herein have only gradually evolved over the past decade through a process of trial and error, supported by discussion with colleagues in various academic fields and helpful feedback from my students” (p. 459).

In addition to incorporating student feedback, McClanahan and McClanahan ( 2002 ) commented on how student feedback builds a stronger partnership with students, “Using student feedback to make improvements in the learning experience reinforces the notion that your class is a partnership and that you value your students’ ideas as a means to strengthen that partnership and create more successful learning” (p. 94). Making students aware that the instructor is soliciting and using feedback can help encourage and build rapport with students.

Instructors should review student feedback for continual and iterative course improvement. Much of the student feedback review occurs outside of class time, and it appears useful for instructors to solicit student feedback to guide changes to the course and build student rapport.

Summary of strategies

We list the appearance of strategies within studies in Table 1 in short-hand form. No study included all eight strategies. Studies that included the most strategies were Bullard and Felder’s ( 2007 ) (7 strategies), Armbruster et al.’s ( 2009 ) (5 strategies), and Lenz’s ( 2015 ) (5 strategies). However, these three studies were exemplars, as most studies included only one or two strategies.

Table 2 presents a summary list of specific strategies, their categories, and descriptions. We also note the number of unique studies ( N ) and excerpts ( n ) that included the specific strategies. In total, there were eight specific strategies within three categories. Most strategies fell under the planning category ( N = 26), with align the course being the most reported strategy ( N = 14). Approaching students ( N = 13) and reviewing student feedback ( N = 11) were the second and third most common strategies, respectively. Overall, we present eight strategies to aid implementation of active learning.

Characteristics of the active learning studies

To address our first research question (What are the characteristics of studies that examine affective and behavioral outcomes of active learning and provide instructor strategies?), we discuss the different ways studies reported research on active learning.

Limitations and gaps within the final sample

First, we must discuss the gaps within our final sample of 29 studies. We excluded numerous active learning studies ( N = 383) that did not discuss or reflect upon the efficacy of their strategies to aid implementation of active learning. We also began this systematic literature review in 2015 and did not finish our coding and analysis of 2364 abstracts and 746 full-texts until 2018. We acknowledge that there have been multiple studies published on active learning since 2015. Acknowledging these limitations, we discuss our results and analysis in the context of the 29 studies in our dataset, which were published from 1990 to 2015.

Our final sample included only 2 studies that sampled mathematics and statistics courses. In addition, there was also a lack of studies outside of first-year courses. Much of the active learning research literature introduces interventions in first-year (cornerstone) or fourth-year (capstone) courses, but we found within our dataset a tendency to oversample first-year courses. However, all four course-years were represented, as well as all major STEM disciplines, with the most common STEM disciplines being engineering (14 studies) and biology (7 studies).

Thirteen studies implemented course-based active learning interventions, such as project-based learning (8 studies), inquiry-based learning (3 studies), or a flipped classroom (2 studies). Only one study, Lenz ( 2015 ), used a previously published active learning intervention, which was Process-Oriented Guided Inquiry Learning (POGIL). Other examples of published active learning programs include the Student-Centered Active Learning Environment for Upside-down Pedagogies (SCALE-UP, Gaffney et al., 2010 ) and Chemistry, Life, the Universe, and Everything (CLUE, Cooper & Klymkowsky, 2013 ), but these were not included in our sample of 29 studies.

In contrast, most of the active learning interventions involved adding in-class problem solving (either with individual students or groups of students) to a traditional lecture course (21 studies). For some instructors attempting to adopt active learning, using this smaller active learning intervention (in-class problem solving) may be a good starting point.

Despite the variety of quantitative, qualitative, and mixed method research designs, most studies used either self-made instructor surveys (20 studies) or their institution’s course evaluations (10 studies). The variation between so many different versions of instructor surveys and course evaluations made it difficult to compare data or attempt a quantitative meta-analysis. Further, only 2 studies used instruments with evidence of validity. However, that trend may change as there are more examples of instruments with evidence of validity, such as the Student Response to Instructional Practices (StRIP, DeMonbrun et al., 2017 ), the Biology Interest Questionnaire (BIQ, Knekta, Rowland, Corwin, & Eddy, 2020 ), and the Pedagogical Expectancy Violation Assessment (PEVA, Gaffney et al., 2010 ).

We were also concerned about the use of institutional course evaluations (10 studies) as evidence of students’ satisfaction and affective responses to active learning. Course evaluations capture more than just students’ responses to active learning, as the scores are biased toward the instructors’ gender (Mitchell & Martin, 2018 ) and race (Daniel, 2019 ), and they are strongly correlated with students’ expected grade in the class (Nguyen et al., 2017 ). Despite these limitations, we kept course evaluations in our keyword search and inclusion criteria, because they relate to instructors concerns about student resistance to active learning, and these scores continue to be used for important instructor reappointment, tenure, and promotion decisions (DeMonbrun et al., 2017 ).

In addition to students’ satisfaction, there were other measures related to students’ affective and behavioral responses to active learning. The most common measure was students’ self-reports of whether they thought they learned more or less (21 studies). Other important affective outcomes included enjoyment (13 studies) and self-efficacy (4 students). The most common behavioral measure was students’ participation (16 studies). However, missing from this sample were other affective outcomes, such as students’ identities, beliefs, emotions, values, and buy-in.

Positive outcomes for using active learning

Twenty-three of the 29 studies reported positive or mostly positive outcomes for their active learning intervention. At the start of this paper, we acknowledged that much of the existing research suggested the widespread positive benefits of using active learning in undergraduate STEM courses. However, much of these positive benefits related to active learning were centered on students’ cognitive learning outcomes (e.g., Theobald et al., 2020 ) and not students’ affective and behavioral responses to active learning. Here, we show positive affective and behavioral outcomes in terms of students’ self-reports of learning, enjoyment, self-efficacy, attendance, participation, and course satisfaction.

Due to the lack of mixed/neutral or negative affective outcomes, it is important to acknowledge potential publication bias within our dataset. Authors may be hesitant to report negative outcomes to active learning interventions. It could also be the case that negative or non-significant outcomes are not easily published in undergraduate STEM education venues. These factors could help explain the lack of mixed/neutral or negative study outcomes in our dataset.

Strategies to aid implementation of active learning

We aimed to answer the question: what instructor strategies to aid implementation of active learning do the authors of these studies provide? We addressed this question by providing instructors and readers a summary of actionable strategies they can take back to their own classrooms. Here, we discuss the range of strategies found within our systematic literature review.

Supporting instructors with actionable strategies

We identified eight specific strategies across three major categories: explanation, facilitation, and planning. Each strategy appeared in at least seven studies (Table 2 ), and each strategy was written to be actionable and practical.

Strategies in the explanation category emphasized the importance of establishing expectations and explaining the purpose of active learning to students. The facilitation category focused on approaching and encouraging students once activities were underway. Strategies in the planning category highlight the importance of working outside of class time to thoughtfully design appropriate activities , create policies for group work , align various components of the course , and review student feedback to iteratively improve the course.

However, as we note in the “Introduction” section, these strategies are not entirely new, and the strategies will not be surprising to experienced researchers and educators. Even still, there has yet to be a systematic review that compiles these instructor strategies in relation to students’ affective and behavioral responses to active learning. For example, the “explain the purpose” strategy is similar to the productive framing (e.g., Hutchison & Hammer, 2010 ) of the activity for students. “Design appropriate activities” and “align various components of the course” relate to Vygotsky’s ( 1978 ) theories of scaffolding for students (Shekhar et al., 2020 ). “Review student feedback” and “approaching students” relate to ideas on formative assessment (e.g., Pellegrino, DiBello, & Brophy, 2014 ) or revising the course materials in relation to students’ ongoing needs.

We also acknowledge that we do not have an exhaustive list of specific strategies to aid implementation of active learning. More work needs to be done measuring and observing these strategies in-action and testing the use of these strategies against certain outcomes. Some of this work of measuring instructor strategies has already begun (e.g., DeMonbrun et al., 2017 ; Finelli et al., 2018 ; Tharayil et al., 2018 ), but further testing and analysis would benefit the active learning community. We hope that our framework of explanation, facilitation, and planning strategies provide a guide for instructors adopting active learning. Since these strategies are compiled from the undergraduate STEM education literature and research on affective and behavioral responses to active learning, instructors have compelling reason to use these strategies to aid implementation of active learning.

One way to consider using these strategies is to consider the various aspects of instruction and their sequence. That is, planning strategies would be most applicable during the phase of work that occurs prior to classroom instruction, the explanation strategies would be more useful when introducing students to active learning activities, while facilitation strategies would be best enacted while students are already working and engaged in the assigned activities. Of course, these strategies may also be used in conjunction with each other and are not strictly limited to these phases. For example, one plausible approach could be using the planning strategies of design and alignment as areas of emphasis during explanation . Overall, we hope that this framework of strategies supports instructors’ adoption and sustained use of active learning.

Creation of the planning category

At the start of this paper, we presented a conceptual framework for strategies consisting of only explanation and facilitation categories (DeMonbrun et al., 2017 ). One of the major contributions of this paper is the addition of a third category, which we call the planning category, to the existing conceptual framework. The planning strategies were common throughout the systematic literature review, and many studies emphasized the need to consider how much time and effort is needed when adding active learning to the course. Although students may not see this preparation, and we did not see this type of strategy initially, explicitly adding the planning category acknowledges the work instructors do outside of the classroom.

The planning strategies also highlight the need for instructors to not only think about implementing active learning before they enter the class, but to revise their implementation after the class is over. Instructors should refine their use of active learning through feedback, reflection, and practice over multiple course offerings. We hope this persistence can lead to long-term adoption of active learning.

Despite our review ending in 2015, most of STEM instruction remains didactic (Laursen, 2019 ; Stains et al., 2018 ), and there has not been a long-term sustained adoption of active learning. In a push to increase the adoption of active learning within undergraduate STEM courses, we hope this study provided support and actionable strategies for instructors who are considering active learning but are concerned about student resistance to active learning.

We identified eight specific strategies to aid implementation of active learning based on three categories. The three categories of strategies were explanation, facilitation, and planning. In this review, we created the third category, planning, and we suggested that this category should be considered first when implementing active learning in the course. Instructors should then focus on explaining and facilitating their activity in the classroom. The eight specific strategies provided here can be incorporated into faculty professional development programs and readily adopted by instructors wanting to implement active learning in their STEM courses.

There remains important future work in active learning research, and we noted these gaps within our review. It would be useful to specifically review and measure instructor strategies in-action and compare its use against other affective outcomes, such as identity, interest, and emotions.

There has yet to be a study that compiles and synthesizes strategies reported from multiple active learning studies, and we hope that this paper filled this important gap. The strategies identified in this review can help instructors persist beyond awkward initial implementations, avoid some problems altogether, and most importantly address student resistance to active learning. Further, the planning strategies emphasize that the use of active learning can be improved over time, which may help instructors have more realistic expectations for the first or second time they implement a new activity. There are many benefits to introducing active learning in the classroom, and we hope that these benefits are shared among more STEM instructors and students.

Availability of data and materials

Journal articles and conference proceedings which make up this review can be found through reverse citation lookup. See the Appendix for the references of all primary studies within this systematic review. We used the following databases to find studies within the review: Web of Science, Academic Search Complete, Compendex, Inspec, Education Source, and Education Resource Information Center. More details and keyword search strings are provided in the “Methods” section.

Abbreviations

Science, technology, engineering, and mathematics

Student resistance to active learning

Instrument with evidence of validity

Instructor surveys

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Problem solving

Problem or project-based learning

End of course evaluations

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Acknowledgements

We thank our collaborators, Charles Henderson and Michael Prince, for their early contributions to this project, including screening hundreds of abstracts and full papers. Thank you to Adam Papendieck and Katherine Doerr for their feedback on early versions of this manuscript. Finally, thank you to the anonymous reviewers at the International Journal of STEM Education for your constructive feedback.

This work was supported by the National Science Foundation through grant #1744407. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

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Nguyen, K.A., Borrego, M., Finelli, C.J. et al. Instructor strategies to aid implementation of active learning: a systematic literature review. IJ STEM Ed 8 , 9 (2021). https://doi.org/10.1186/s40594-021-00270-7

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Transforming Teaching Through Active Learning: Case Studies from the Social Sciences

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November 16–17, 2018

Stetson University Miami, Florida

Jeff Gaab , Farmingdale State College Richard Vogel , Farmingdale State College

Introduction

This paper examines case studies of active learning pedagogical techniques in the social sciences. Whereas active and applied learning strategies have been around for some time, recent changes in the academy, our students, and the world make implementing some form of active learning, especially in subjects such as business and economics, the social sciences and the humanities, imperative. It is almost universally accepted that, for our twenty-first century students, the time is right to switch from purely teacher-based delivery of content to learning activities performed by students. This includes reaching our students through reading, writing, discussing, role-playing, listening, and reflecting. Active learning can also include specially designed games, capstone courses, and internships. Our analysis provides an overview of some of the active learning strategies we have employed at Farmingdale State College, SUNY, and their success as transformative teaching pedagogies.

Overview of Some of the Literature

Pedagogy and teaching methodologies in the social sciences and business have changed significantly over the past twenty years. The traditional lecture-based model of teaching supported by a series of in-class exams, classroom discussion of readings and course material, and supplemented with a research paper of varying length depending on the specific field, has given way to the realities of teaching Generation Z. While the effectiveness of the traditional lecture-based course is subject to debate, a whole new set of pedagogies embracing a range of technologies and modalities has emerged and proven to be not only more effective in reaching our students, but also better able to engage our students in the subject matter content.

Within the fields of business and economics, there has been a significant movement to introduce and use popular culture as a teaching tool. One of the methods embraced is the use of video clips from popular television shows. Hall and Pemska-Mickluch (2016) present the case of using clips from The Simpsons , Fox’s long-running cartoon series that is still popular. These clips tell a story in a way that engages students and keeps the subject matter approachable—economics in this case. After viewing episodes or clips of the show, students are asked to respond to and analyze the economic dimensions of the story, making the material more interesting and relevant to the students than when simply basing the discussion on historic facts and data.

Micheletto (2011) presented the case of the introduction of classroom experiments that are illustrative of key concepts in the field of economics, and that require students to use an audience response system to provide input. This process not only generates data, but it also creates an atmosphere where students are engaged and part of the process of generating knowledge. Onyema and Danil (2017) focus on the use of information and communications technology (ICT) in the classroom. They present the case for leveraging mobile devices for content delivery and flipped learning, and to convert the classroom into an active environment for knowledge creation by their students.

Hauhart and Grahe (2010) focus on the growing importance and use of the capstone course experience in the fields of sociology and psychology. In the capstone, students are expected to integrate, apply, and extend core concepts and skills developed during their studies.

The discussion above presents only a small portion of the growing body of literature on the various emerging methods that can be employed to reach our students. It is apparent though, that at their core, these methods focus on moving classroom teaching from passive lecture-based models to student-oriented active learning models.

Active Learning in the Social Sciences- Some Successful Examples.

Table 1 presents a range of examples and cases of active learning pedagogical techniques in the social sciences. Many of these methods have been applied in the classroom at Farmingdale. This active-learning approach includes reaching our students through reading, writing, discussing, role-playing, listening, and reflecting. Active learning can also include specially designed games, capstone courses, and internships.

Reacting to the Past: Pioneered at Barnard College, New York, Reacting consists of elaborate games set in the past in which students are assigned roles with “victory objectives” informed by classic texts in the history of ideas. ( )

Washington Internship Institute: Students receive credit from their home institution while interning in Washington D.C. in subjects such as environmental studies, history and the humanities, criminal justice/pre-law, biology, and health care. ( )

Short-Term Study Abroad: Students take a Farmingdale course with a Farmingdale instructor while visiting and experiencing another culture.

Applied Empirical Research Projects (Capstone courses): Students integrate a wide range of concepts, methods, and techniques from their specific field of study in the completion of a research project that may culminate with classroom/public presentations, multi-media presentations, or presentations at a research conference.

Business and Economic Simulations: Business simulations lead the student to apply concepts, methods, and techniques studied and acquired through their studies to make, apply, and reflect upon decisions to a situation leading to a range of potential outcomes.

Audience Response Systems

Introduction and Use of Popular Culture

Mock Trials (Ahmadov, 2011)

Flipped Classroom and Use of Personal Electronic Devices

Study abroad travel experiences expose students to other places, peoples, and cultures and are the surest way to get our students to think globally. Further, study-abroad promotes global citizenship. Study abroad is also a form of applied learning, and required for graduation at some colleges and universities in the United States. Farmingdale State College students are non-traditional, often first-time college students with full-time jobs. For these students, a full-semester traditional study abroad program is not an option for them. Therefore, we developed short-term study abroad options where students take a class with a one-week study abroad component (such as over spring break or the Thanksgiving holiday recess). Whereas employers are somewhat ambivalent about the “cultural and global competencies” that study-abroad curricula try to inculcate, research has shown that if students can clearly articulate how a study-abroad experience has developed or strengthened their interpersonal communication and leadership skills, they are more likely to be hired (Harder et.al, 2015, p. 41). Our courses were designed to do both: to strengthen communication and leadership skills, while developing students’ cultural and global competencies. All of these skills are components of active learning paradigms.

Travel Courses at Farmingdale State College conform to Kolb’s Active Learning matrix, which cycles through stages of Concrete Experience; Reflective Observation; Abstract Conceptualization; and Active Experimentation. Concrete Experience occurs through the travel component of the course. Students make Reflective Observations in the raw travel journals they are required to maintain and submit at the end of the semester. Abstract Conceptualizations are prompted by the critical thinking questions students answer in response to the workbook (which is the midterm) and textbook (which they write about in their journals) assigned for the class. Active Experimentation occurs through further critical thinking questions based on instructor comments on student journals, and through subsequent revision of those journals. The bulk of the writing and reflection for these classes takes place before and after the travel component is completed.

As part of their reflection students are asked to answer the question: What do you think you learned from this particular study-abroad class that you could not have learned from a regular, formal, lecture course? After an initial review by the instructor, students are allowed to take more time to revise their journals and reflect on and revise their answers to specific questions before final submission. The journals become more than just a travel diary; they became a scholarly review. Therefore, this course has demanded a writing intensive designation. Above all, constant writing, reflection, and revision, as well as discussion, has made this class a serious academic seminar and experiential learning experience.

Reacting to the Past ( www.barnard.edu/reacting ) is an innovative active learning pedagogy Farmingdale instructors have incorporated into their social sciences courses, especially history classes. Pioneered at Barnard College, New York, by noted historian Mark Carnes, the Reacting to the Past Consortium now consists of over 500 colleges and universities. The Reacting to the Past exercises consist of classroom games set in the past. Students are assigned roles with “victory objectives” based on assigned readings of classic texts. Reacting to the Past exercises allow students to become the historical actors they are reading about. The exercises place students into the historical situations they are studying: “Students learn by taking on roles, informed by classic texts, in elaborate games set in the past; they learn skills—speaking, writing, critical thinking, problem solving, leadership, and teamwork—in order to prevail in difficult and complicated situations.” Reacting to the Past roles have no “fixed script and outcome.” Students are required “to adhere to the philosophical and intellectual beliefs of the historical figures they have been assigned to play, they must devise their own means of expressing those ideas persuasively, in papers, speeches, or other public presentations; and students must also pursue a course of action they think will help them win the game.” Several Farmingdale instructors have participated in Reacting to the Past seminars, which are held every year in New York and around the country, and used this pedagogy very effectively in their classes. Faculty and students have noted that Reacting to the Past gave them a different and broader perspective on the material and issues under discussion.

Internships are an important component of active learning. Farmingdale State College has partnered with the Washington Internship Institute as one venue for internship opportunities for our students. The Washington Internship Institute offers a wide variety of internships in government offices, nonprofit organizations, and for-profit companies. Recent Farmingdale students have been placed at the IRS, the non-profit No Labels, The Center for American Democracy, CNN, the Iraqi Embassy, and Capitol Hill offices. The four-day-per-week internship is supplemented by two courses: an internship seminar and an extra course selected by the student. The Washington Internship faculty include top policy professionals and leading academics, who guide students in examining policy issues. They also utilize their extensive academic and professional connections to enrich courses with a variety of notable guest speakers and site visits. Students receive credit from their home institution while interning in Washington, D.C. in subjects such as environmental studies, history and the humanities, criminal justice/pre-law, biology and health care, etc. (www.wiidc.org).

Assessment of all of these active learning tools is crucial. All of these active learning strategies conform to Kolb’s Learning Cycle model in that each includes Concrete Experience, Reflective Observation, Abstract Conceptualization, and Active Experimentation. Kolb’s model informs our approach to assessment.

Conclusions

Over the past decade, colleges and university professors have had to find new ways to guide their students. The traditional “sage on the stage” model of instruction does not resonate with the reality that every student has access to a wide array of facts and knowledge right at their fingertips. Our task has moved to one of guiding our students in how to interpret, analyze, and present this vast set of facts and knowledge. The active-learning processes that we have presented above demonstrate the myriad of techniques that are now being applied in the classroom—all meant to better aid our students in gaining the knowledge and skills that they will need to be successful after leaving the college classroom.

Ahmadov, A. (2011). When great minds don’t think alike: Using mock trials in teaching political thought. PS: Political Science and Politics, 44 (3), 625-628.

Hall, J. C., Peck, A., & Podemska-Mickluch, M. (2016). Bringing active learning into high school economics: Some examples from The Simpsons . Journal of Economics and Economic Education Research, 17 (2), 55-63.

Harder, A., et al. (2015, March). Does study abroad increase employability? NACTA Journal , 41-48.

Hauhart, R.C., & Grahe, J. (2010). The undergraduate capstone course in the social sciences: Results from a regional survey. Teaching Sociology, 38 (1), 4-17.

Micheletto, M. J. (2011). Conducting a classroom mini-experiment using an audience response system: Demonstrating the isolation effect. Journal of College Teaching and Learning, 8 (8), 1-13.

Onyema, O.G., & Daniil, P. (2017). Educating the 21 st -century learners: Are educators using appropriate learning models for honing skills in the mobile age? Journal of Entrepreneurship Education, 20 (2), 1-15.

Blended Learning and Student-centered Active Learning Environment: a Case Study with STEM Undergraduate Students

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Published: 14 March 2022
Volume 22 , pages 210–236, ( 2022 )

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This paper describes an embedded case study of “blended” teaching integrated with traditional lessons in a Student-Centered Active Learning Environment and social activities on the platform. The didactic phenomena were designed by creating learning environments, artifacts, and teaching/learning sequences in authentic educational contexts. We aim at improving the task design of a mathematics lesson with an impact on students’ performance in mathematics. Quantitative results show considerable benefits in the evolution of the use and coordination of several systems of semiotic representation. As a result, a better predisposition to the study of the subject seems to appear; moreover, the satisfaction test shows the achievement of alternative teaching methodologies for most of the students.

Cet article décrit une étude de cas intégrée d’enseignement « en mode hybride» combiné à des cours traditionnels dans un environnement d’apprentissage pratique centré sur l’étudiant ainsi que des activités sociales sur la plate-forme. Les phénomènes didactiques ont été conçus en créant des milieux d’apprentissage, des artefacts, et des séquences d’enseignement et d’apprentissage dans des contextes pédagogiques authentiques. Ainsi, il semble se développer une meilleure prédisposition à l’étude de la matière; de plus, le questionnaire mesurant le taux de satisfaction indique que les méthodes d’enseignement alternatives fonctionnent pour la plupart des étudiants. Nous visons à améliorer l’élaboration de la tâche associée à un cours de mathématiques de façon à avoir une incidence sur la performance des étudiants en mathématiques. Les résultats quantitatifs démontrent des avantages importants en ce qui concerne les progrès dans l’utilisation et la coordination de différents systèmes de représentation sémiotique.

An Investigation of Using Blended Learning Pedagogy to Sustain Student Interest in Basic Science Subjects

Introduction: Collaborative Active Learning—Strategies, Assessment and Feedback

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Introduction

Why do so many students have difficulties in mathematics if it is supported by the earliest form of intelligence we have? One of the difficulties in learning mathematics is the impossibility of conceptualization based on meanings referring to a concrete reality. On the one hand, every mathematical concept uses representations because there are no “objects” to exhibit; conceptualization needs to go through representative registers. According to Duval ( 1993 ), comprehension in mathematics presupposes the coordination of at least two registers of semiotic representation. Such coordination is not natural in students. These difficulties are found not only in students beginning in mathematics, as some research in mathematics education shows (D’Amore, 2000 ; Duval, 1993 ; Sbaragli & Santi, 2011 ). Some difficulties continue to be encountered in secondary school students and are also found in students attending the first year of STEM courses. Although they decide to attend a scientific faculty, some students do not have strong mathematical skills. Others do not have a “good relationship” with mathematics.

These studies start from some considerations on the obstacles students encountered during the first year of university, mainly in so-called service courses. In these courses, passing the mathematics exam is a sin to expiate rather than a resource for further studies. Some students have difficulties related to problems in mathematics (Zan, 2007 ) and epistemological obstacles (Brousseau, 1976 ), misconceptions established by inadequate teaching practices in the primary school (Sbaragli & Santi, 2011 ), and, in the upper secondary school, Functions, (Tall & Vinner, 1981 ), Infinity (Arrigo & D’Amore, 1999 ), Limits (Bagni, 1999 ), and Inequations (Bazzini & Tsamir, 2001 ). Also, many pieces of research have shown difficulties related to different uses of the language, such as the relationship between verbal and formal language (Ferrari, 2003 ). Other challenges are due to the linguistic specificity of the mathematical text (Branchetti & Viale, 2015 ; D’Amore, 2000 ), the use of different systems of semiotic representation (Duval, 1993 ) and gestures (Arzarello, 2006 ), and the formulation of the texts of the problems (Zan, 2012 ).

The research related to university teaching has been spreading over the last decade in Europe (a network of INDRUM researchers has been set up to deal only with this type of research); however, it is not very articulated in Italy. Only a small number of studies have been conducted in this direction. On the other hand, these studies are more widespread internationally, for example, in Australia (Palmer et al., 2015 ; Marginson et al., 2013 ) and the USA (Langen & Dekkers, 2005 ).

Nevertheless, the transition to university is still a hot topic in the mathematics education research community because, despite it being researched extensively and despite many attempts to address and alleviate these difficulties (bridging courses, support centers, etc.), problems persist (Kouvela et al., 2018 ). The highlighted difficulties acquire particular importance in heterogeneous classes, considered in educational planning. Moreover, the dominant form of thought of the students is the algorithmic one (Fandiño Pinilla, 2008 ), and the approach to problem-solving seems to be more based on the analogy with similar problems, where the students try to remember if they have already seen that type of problem. Therefore, the study of mathematics is often associated with memorizing techniques. So, by delegating to the algorithm form, the student renounces the “responsibility” of setting up a resolving process based on a conceptual approach to the discipline and often associates formalized procedures to the very nature of mathematics.

These phenomena are well known and widely studied by researchers in mathematics education, especially on the part of the French School that has been more concerned with studying the effects of the didactical contract and are called “formal delegation and the need for formal justification” (Brousseau, 1998 ). These considerations come from looking for new ways to reach a more effective teaching–learning process. In the USA, many teaching methodologies have been tested, trying to improve the mathematics teaching–learning process at the university level. In particular, just-in-time teaching (JiTT) and peer-led team learning (PLTL) have been implemented with positive effects on student performance (Novak, 2011 ; Preszler, 2009 ).

JiTT is a pedagogical approach that consists of taking advantage in the classroom of feedback from the activities that students carry out at home, intending to improve teaching effectiveness, optimize classroom time, and improve student motivation. PLTL is a model of teaching undergraduate science, math, and engineering courses that introduce peer-led workshops as an integral part of a course. Students who have done well in a class (for instance, General Chemistry) are recruited to become peer leaders.

Although the two methodologies have been applied effectively, methodological uniqueness does not always ensure learning success because not all students learn in the same way (D’Amore & Sbaragli, 2011 ; Weber et al., 2020 ).

Starting from these considerations, in this article, we describe a case study to see if JiTT and PLTL methodologies can be used together. We aim at improving the task design of a mathematics lesson with an impact on students’ performance in mathematics, trying to foster a greater motivational and affective disposition towards the subject and an adequate instructional scaffolding to make the university student work in their proximal development zone. The experimentation is carried out with mechanical and management engineering students who attend Calculus 2 classes. This course was always conducted according to a traditional didactic approach: frontal lessons were alternated with written and oral tests at the end of the first semester, mainly assessing students’ knowledge. We proposed experimentation with blended learning. JiTT and PLTL methodologies are integrated with the support of a social platform into a student-centered learning environment, i.e., a Student-Centered Active Learning Environment with Upside-down Pedagogies (SCALE-UP). We ask ourselves the research questions: integrating these teaching methods, is there an improvement in students’ mathematical skills? Does it improve students’ approach to studying the discipline, enhancing good motivational and affective dispositions?

The experimentation results seem to show an improvement in the performance of the experimental class and a considerable increase in students’ interest and motivation. Also, many students, who initially had deficiencies on some topics, could achieve a positive result on the exam by working in the proximal development zone (Vygotsky, 1978 ) and with adequate scaffolding (Bruner, 1975 ).

This article is a prequel to other articles by the author about teaching mathematics in STEM courses and interdisciplinarity in mathematics education (Branchetti et al., 2018 ; Capone, 2022 ). Thanks to this preliminary, we have been able to compare how mathematics teaching in STEM courses changed before, during, and after the COVID pandemic (Branchetti et al. 2021 ; Capone & Lepore, 2020 ; Capone & Lepore, 2022 ). The paper is structured as follows. The “ Teaching Methodologies ” section will illustrate the teaching methodologies, methods applied, the social platform used, and the SCALE-UP learning environment, also regarded as the existing literature (related work). In the “ Conceptual Framework ” section, we will illustrate the theoretical background. In the “ The Case Study ” section, we will describe the case study. The “ Data Analysis and Results ” section will show the quantitative and qualitative analyses of the results obtained. Finally, the “ Discussion and Conclusions ” section will conclude and offer some future work ideas.

Teaching Methodologies

Teachers themselves are often looking for a methodology that can solve the difficulties of teaching–learning a subject. Many research pieces in pedagogy (Gallagher, 1994 ; Grossman et al., 2009 , for example) have studied the teaching–learning processes and analyzed which strategic teaching actions to implement according to the concrete training situations the particular characteristics of the students. Also, in mathematics education, there are many types of research (Clements & Sarama, 2004 ; Davis, 2013 ; Steffe & Thompson, 2000 ), which underline the importance of the methodological choice to convey mathematical contents or to encourage good motivational and affective dispositions to the study of mathematics. In general, good teaching should promote the development of different and more autonomous learning processes, not only by transmission or reception but also by discovery, action, and problems.

On the other hand, the teacher should ensure a customizable educational program because not all students learn in the same way. Furthermore, s/he should promote and consolidate students’ interest and motivation by creating a stimulating and innovative learning environment. D’Amore pointed out that sensational mistakes can be made by making the teaching choice fall on a single methodology. He classified these errors into pedagogical, epistemological, didactic, and semiotic errors (D’Amore, 2016 ). Using a unique method, one risks falling into what Raymond Duval ( 1993 ) calls the “cognitive paradox of learning”: the student will identify the mathematical object with its representation (in the best case, if the methodological tool was successful). The abstract mathematical object will be unreachable for that student (Duval, 1993 ). Therefore, mathematical learning will not have taken place at all.

Thus, among the many active methodologies widespread in mathematics education, the choice fell on blended learning, including, next to the traditional lesson, the integration of JiTT and PLTL methodologies, taking advantage of technological innovations, and an adapted learning environment. The e-learning approach allowed students to relate continuously with the teacher and tutors and activate peer-education dynamics, thanks to a constant peer-to-peer debate between all the class group members (Capone et al. 2017 ). This research hypothesizes that a change in university mathematics teaching methodology can decisively influence learning, especially in degree courses. The discipline has a “service” role compared to other study fields. It allows us to act on the motivation and partially stem the difficulties due to a teaching contract that sees the student imitative and oriented to reproduction procedures.

In the authors’ opinion, through collaboration with peers and students’ direct involvement, also mediated by technology, it is possible to reactivate more significant and lasting learning processes. So, this study experiments with a hybrid teaching method that blended different teaching methods (Fig. 1 ), focusing on students and their epistemological needs.

Blended methodologies

In the following, we will describe, in detail, the JiTT, PLTL, Edmodo social platform, and SCALE-UP learning environment.

Just-in-time Teaching

Just-in-time teaching is a pedagogical approach that consists of using in the classroom the feedback from the activities that students carry out at home to improve teaching effectiveness, optimize classroom time, and enhance student motivation. JiTT was first used in the late 1990s in Physics university courses in the USA, but its use has spread to many other academic disciplines. Following the methodological indications of JiTT, students are assigned some exercises, known as “Warmup exercises”, “Preflight checks”, or “Checkpoints” (Doyle, 1988 ), regarding the activities carried out in class. They are preparatory to the next lesson through an e-learning platform. The students work on the task at home and share it with each other by posting the exercises on the class’s page. The teacher can read students’ answers before the lesson to plan the classroom activities. S/he can start from the doubts, misconceptions, and difficulties that emerged from the discussion. This is one way to focus the university lesson on the student, which is rarely the case in daily teaching practice and promotes interactive learning. The following Table 1 clarifies this.

A JiTT teaching cycle can be outlined as follows:

JiTT’s activities also consider the motivational factors that influence students’ behavior. Theorists of motivational belief undertake the constructivist position that “the process of conceptual change is influenced by personal, motivational, social and historical processes, thus supporting a warm model of individual conceptual change” (Pintrich et al., 1993 , p. 197). The research has shown that university students who report that their teaching material is more interesting, relevant, and valuable are more likely to use more in-depth processing strategies such as metacognitive processing and control strategies. “At the level of class and task, there are several features that could increase students’ situational interest—such as challenge, choice, novelty, fantasy, and surprise”. (Malone et al. 1987 ).

Teachers and students become a teaching–learning team, ready to begin the lesson with an awareness of the class’s mental status, making the learning experience as relevant as possible to a particular class at a specific time. What happens in the classroom consists of a mix of preplanned activities and creative improvisation suggested by student responses and guided by in-class reactions to thoughts and opinions in those responses (Novak, 2011 ).

All JiTT instructions are mediated by the teacher’s presence in synchronous or asynchronous mode. Web materials serve as a communication and organizational tool as a pedagogical resource. Since a large part of the students’ learning occurs outside the classroom, JiTT professionals see their pedagogical strategy as a feedback loop between teaching and learning and school and outside school experiences. Essential factors in students’ educational success are student–student interaction, i.e., peer-learning, student–teacher interaction, and active time: these three factors are immensely enhanced by technology. Web-based interaction prepares students and teachers for the subsequent classroom interaction, gives students some control over their learning, and enriches classroom social contacts.

Peer-led Team Education

Peer-led team learning (PLTL) is a model of teaching undergraduate science, math, and engineering courses that introduces peer-led workshops as an important part of a class. Students who have done well in a class (for instance, General Chemistry) are recruited to become peer leaders. Peer leaders meet with small groups of six to ten students each week for one to two hours to discuss, debate, and engage in problem-solving related to the course material.

PLTL can be understood in the context of cognitive science. It is consistent with social constructivism and Vygotsky’s ideas ( 1932 ) because students are asked to construct their understanding under a more capable peer’s supervision. They can be said to be learning within the zone of proximal development. PLTL initially involved chemistry classes and was tested in many US countries. The methodology has been proven successful in various STEM courses (Báez-Galib et al., 2005 ; Lewis & Lewis, 2005 , for example). There are many examples of the application of the methodology in mathematics classes. For example, Liou-Mark et al. ( 2010 ) applied PLTL to PreCalculus courses, and they found that significant improvements in the performance of students attending the classes were achieved.

The methodology aims to facilitate students’ learning of the discipline by fostering interaction between the course students while helping each other in education (Gosser, 2011 ). Overall, Gosser ( 2011 ) found that, in a large number of studies, the average percentage of students receiving a positive assessment was 15% higher for students participating in PLTL groups than for students not participating in such groups. Remedial or enhancement courses are activated in many Italian universities, mainly linked to introductory classes. However, in the Italian context, there is no specific reference to the methodology of PLTL in the literature, although classes are, in some cases, organized with the same aims as PLTL. Our experimentation is inspired by research results in mathematics education in the USA, adapting the PLTL to the Italian university context. The PLTL methodology can be understood in cognitive sciences and follows social constructivism, Vygotsky’s ideas ( 1932 ), and Bruner’s instructional scaffolding ( 1975 ).

Edmodo ( https://edmodo.com ) is a social platform designed by Nick Borg and Jeff in 2008 for teaching, including students, teachers, and parents. Edmodo’s home page is very similar to Facebook’s home page. The working environment allows greater privacy because teachers can create a virtual classroom and allow only registered provided automatically generated code and periodically change. Students can create a profile in Edmodo and interact with the class and all the group members. In Edmodo, there are many tools to share files and ideas with other students and teachers. Edmodo allows users to upload documents, links, videos, and images stored in the library section. The site also offers the possibility to share materials between teachers who want to form a group and stay in touch. Participants can share media content such as homework, get their teachers’ suggestions, quizzes, notices, notes, and vote on polls (Jarc, 2010 ).

Researchers have investigated that social networks have a profound impact on the way students learn and collaborate (Capone et al., 2018 ); research results also attest to the satisfaction of many teachers who work in a collaborative environment increasing their educational professionalism. Some teachers noted that Edmodo has strengthened the relationships among pupils and led to a more solid class (Mills & Chandra, 2011 ). As a result, Edmodo can also be a tool that allows teachers to conduct a course more easily (Witherspoon, 2011 ).

Learning Environment

SCALE-UP is a learning environment specifically created to facilitate active and collaborative learning among students (Gaffney et al., 2008 ). The name SCALE-UP originally stood for “Student-Centered Activities for Large Enrolment Undergraduate Physics”, but given its characteristics, many institutions have used it for courses in different disciplines. The acronym has been changed to “Student-Centered Active Learning Environment with Upside-down Pedagogies”. The basic idea is that students are given a stimulus to reflect on (an exercise, a multiple-choice test, a task to look for mistakes made by other students). Teachers act as a coach and scaffolder, intervening appropriately in the groups without being intrusive, answering students’ questions that may arise while carrying out a task and make a comparison between the various groups at the end of each activity.

The spaces are carefully designed to facilitate interactions between students working on generally short tasks. In these spaces, students are engaged in hands-on learning activities or simulations. They sit around a table in order to interact face-to-face and work in small groups. A decade of research indicates significant learning improvements (Dori & Belcher, 2004 ). It was decided to adopt this model, taking up the experiments made at the Massachusetts Institute of Technology in Boston and adapting it to the course’s specific needs.

Conceptual Framework

The teaching methodologies that have been used for this experimentation have in common the Vygotskian perspective of teaching (Vygotsky, 1978 ) and Bruner’s idea of didactic scaffolding (Bruner, 1984 ). Scaffolding is the help given to a student during the whole learning process, and it is specific for each student; this didactic approach allows to experiment with student-centered learning. Vygotsky stresses that the community plays a fundamental role in creating meaning and developing cognition because cognitive skills and thought patterns are established in the social and cultural contexts of the learning environment (Vygotsky, 1978 ). Two significant ideas in Vygotsky’s work are the roots of PLTL. First, interaction with a more informed and qualified peer or teacher effectively develops skills and strategies. In other words, knowledge is scaffolding with the support of a more experienced and successful student. Secondly, tasks and activities should be designed to improve their performance levels. Vygotsky proposed the concept of the proximal development zone (ZPD), which is the difference between the independent problem-solving skills of students (lower end of the ZPD) and their development potential (upper end of the ZPD) with the guidance of more experienced peers. The scaffolding allows the student to work in their proximal development zone, gradually subtracting as the students becomes more and more autonomous.

Three essential features of scaffolding can facilitate learning (Wood & Wood, 1996 ). The first feature is the interaction between the student and the expert. This interaction should be collaborative for it to be effective.

The second is that learning should occur in the student’s proximal development zone. To do this, the teacher must continuously check the student’s level of knowledge. The third feature of scaffolding is that the expert’s support and guidance are gradually removed as the student becomes more competent until the student becomes independent. In agreement with the fact that “every function of cultural development appears first on the social and then on the psychological level, firstly among people as an interpsychological category, then within the student as intrapsychological category” (Vygotskij, 1987 , p. 11), we tried to enhance peer comparison.

The social platform supported collaborative learning among students and favored constant interaction with the teacher, who could take a supportive role. Moreover, the idea of working just in time requires the student’s active involvement in the lesson, who, from being a passive receiver of information, can become an active builder of their knowledge, creating a sort of community of practice (Wenger, 1996 ). This method, which has its roots in constructivism (Hurd, 2009 ), aims to build shared collective knowledge, a way of living, working, and studying, based mainly on sharing and overcoming individualism and competition. Ability becomes means to create collectively, following the method of social constructivism. Learning, coming from this perspective, is understood as:

1. Creation of meaning: from a lifelong learning perspective, our experience is significant. The experience becomes substantial when reflecting on it.

2. Identity development: learning is a process that allows us to interact, participate, and define our space/role in a community.

3. Belonging to a community: to change, to recognize oneself, or to leave, the individual must know his community, identifying with it or not, making their contribution.

4. Result of practice in a community: the union between know-how and competence.

According to Argyris and Schön ( 1978 ), who worked on individual and collective learning, a teaching action aims to train students to problematize the act, reflect, analyze, give meaning to their daily practice, and develop a very important competence: learning to learn. A community of practices is established and consolidated only through confrontation de visu. The online approach can favor and intensify establishing a community of practice. It is consolidated only through the direct interaction of the community members, triggering a continuous negotiation of practices and meanings and making the training/learning path a place of exchange. Reifications or realization of tasks is carried out collaboratively; active and collaborative participation is equal and personalized; negotiation of meanings or continuous reflection of the group on what has been done (Wenger, 1996 ).

Moreover, a social platform seems to contribute to the negotiation of meanings. However, it does not entirely replace the physical interaction between the community members: it would seem like the online environment works better if it is in complementarity with something solidly constituted offline, i.e., in presence (Cohen & Prusak, 2001 ).

In short, in the social dimension of learning, communities of learners can be considered, in a Vygotskian perspective, as multiple “zones of proximal development”. Here, mutual peer tutoring, fueled by cognitive scaffolding, creates “team choreography” (Le Boterf, 1999 ), which guides, without directing, the learner’s naive theories. The learner is taught to revisit his knowledge and reflect on his experiences. He is facilitated in solving problems in a situation of impasse. He is supported in knowledge construction, development of skills, and competencies to achieve training objectives centered on his needs. Interactive processes among community agents become an engine that promotes communication and sharing of knowledge, skills, expertise, and openness to multiple perspectives. The diversity of knowledge, experience, and skills within a working collective represents a potential for broader and richer action through the valorization of all types of intelligence and personal talents; at the same time, this diversity legitimizes diversity and understanding of differences. Scaffolding is therefore not only cognitive but also affective-motivational and relational-social. Affective scaffolding encourages, promotes, and approves the student to approach expert practice. It stimulates active participation, interest, and creativity, acting positively on the sense of confidence, on feelings of self-esteem and self-efficacy, and on empowerment aimed at commitment and responsibility, therefore on the motivation to learn.

The Case Study

We designed Calculus II’s course as a case study for the proposed methodology. The case study has ideographic and nomothetic intentions (Yin, 1981 , 2013 ). This section describes the course’s design, showing its structure and how the methods were mapped to it.

The experimental context is the mathematical class attended by the students of the first year of Mechanical Engineering and Management Engineering at the University of Salerno. The course was carried out during the second semester of the first year after students had attended and/or taken a Calculus 1 exam. The course has been restructured following the constructive alignment suggested by Biggs and Tang ( 2010 ).

The course included 90 h of lessons, divided into 54 h of theory lessons and 36 h of training; also 24 h of exercises with the tutors, dividing the students into two sub-groups, 12 additional hours of activities for students who have reported a short evaluation at the first test. The course has been designed considering the Teaching Council’s indications and the Lisbon descriptors.

The educational goals are subdivided into Knowledge and Understanding, Applying Knowledge and Understanding—Engineering Analysis, Applying knowledge and understanding—engineering design; Making judgments—engineering practice; and Communication skills and transversal skills.

About Knowledge and Understanding, the aims of understanding the terminology used in mathematical analysis; knowledge of demonstration methods; knowledge of the fundamental concepts of mathematical analysis. Knowledge related to integral functions of a variable, numerical series, sequences and series of functions, functions of several variables, differential equations, multiple integrations, curves, curves integrals, surfaces and surface integrals, and vector fields.

About Applying Knowledge and Understanding—Engineering Analysis, the aims are applying the theorems and the rules studied to solve problems; building methods and troubleshooting procedures; know how to process and communicate information using a formal linguistic log; applying knowledge of the concepts and methods of calculus and mathematical tools to solve differential equations, integral curves, and integral and surface integrals; perform series and integral calculations; and calculate maximum and minimum functions of two variables, applying knowledge to develop demonstrations of certain theorems consistently.

About Applying knowledge and understanding—engineering design, the aims are applying knowledge to find the most appropriate methods to solve a math problem and be able to find optimizations in solving a math problem.

About Making judgments—engineering practice, the aim is applying the acquired knowledge to contexts different from those presented during the course.

About Communication skills—transversal skills, the aim is to learn more about the topics covered by teaching materials other than those proposed during the course.

About Learning skills—transversal skills, the aims are learn how to decipher the topics discussed using teaching materials other than those proposed during the course and develop a positive attitude towards math based on respect for truth and availability to seek motivation and to clarify its validity.

In the following, the contents of the course have been scheduled (Table 2 ).

The teaching path has been divided into learning units, and the competence goals and training targets have been highlighted through appropriate competence indicators for each unit. In the following, Table 3 shows an example of the learning unit concerning surfaces and integral surfaces.

Participants

The participants in the educational experiment are 112 students attending the first year of Mechanical Engineering and Management Engineering at the University of Salerno. Also involved in the experiment were the course teacher, two experts of the discipline for the exercises, and three students attending the master’s degree in engineering as tutors. The background of the students is heterogeneous. As shown in Fig. 2 , most of them attended scientific high school (about 80%). In Italy, the scientific high school provides a more in-depth study of mathematics than other schools (132 h of mathematics in the last year), while in the classical high school (grammar), only 66 h in the last year. In the technical institutes, 132 h are foreseen. In professional institutes, mathematics subjects are dealt with more lightly because students generally decide to work after the last year of high school and not enroll at university. Although students already attended a Calculus class in the first semester, their background also affects the following examinations.

High school attended by the students

Besides, about 24% of the course students had not yet taken the Calculus 1 exam.

The research was conducted in compliance with the code of ethics. All experimental data, both the students’ verification tests and the answers to the questionnaire, were treated anonymously.

The methodology is based on a single case study to identify intervention strategies in the specific didactic situation. Direct observation, understood as student–teacher interaction through information technologies, collected empirical data on teaching effectiveness. The approach was ideographic based on qualitative methods through a questionnaire to students and from students’ interactions with the e-learning platform, and nomothetic based on quantitative data emerging from the results of the tests.

This is a non-comparative observational case study where an attempt is made to respond to a problematic situation. We aim to verify whether the comparative use of JiTT (just-in-time teaching) and PLTL (peer-led team learning) in mathematics education can lead students to acquire mathematical competence and satisfy the teaching action.

Integration of JiTT and PLTL, Using Edmodo in SCALE-UP environment

This subsection will describe how JiTT and PLTL methodologies were used in a Calculus II class with engineering students. To the classic lecture, we added e-learning activities using the Edmodo platform described in the previous section. After the lesson, a summary was loaded on the platform each time. Besides, we said exercises of increasing difficulty, and students were invited to carry them out by posting the tasks or results. Often the students confronted each other about carrying out the exercises and pointed out the difficulties they encountered or commented on the other students’ performance. In a non-invasive way, the teacher and tutors had the opportunity to read the comments and analyze the progress of the exercises. The teacher collected the most common errors or misconceptions highlighted by the words, which were often generated by an incorrect interpretation of the explanation in class or by the teacher’s wrong approach to the subject. The next lesson took its cue from brainstorming about the misconceptions that emerged from the exercises, which clarified any dark points. Students often send private messages to teachers or tutors, especially the most difficult ones. It made it possible to monitor step by step the skills acquired by the students, the problems encountered, and the points to dwell on with more considerable attention. In the following figure, we show the home page of the class Calculus II.

Visually it has a central space where messages appear, enclosed between two service boxes, on the right and left, as in Fig. 3 .

Homepage—Calculus II (Matematica 2)

Within the group, communication can be one-to-many (teacher to all, student to all) or discreet, between teacher and student, or student and student. In addition to communicating with the teacher, students can send attachment documents that the teacher marks online and send back to the sender (even in one-to-one mode). Other useful tools that the platform offers are a shared library where one can store documents and images, a calendar where it is possible to mark the deadlines of homework assignments and the dates of checks, create quizzes, and manage evaluations while protecting privacy. The e-learning approach allowed students to interact with teachers and tutors daily and ongoing basis. It enabled them to engage in and develop peer education through dialogue between all class members.

Interaction in a virtual community was also helpful because it allowed the transition from a colloquial language register to a formal one. As shown in Fig. 4 , the dialogue between students, even when using informal language, allowed the teacher to identify some difficulties in approaching the exercises.

In Fig. 4 a, a student asks colleagues to confirm correctly that the exercise is being carried out.

S1: Good evening, has anyone managed to set up this exercise, taken from the professor’s handouts? S2: I also divided the domain into two domains. I made the integral on the domain D1 and then on the domain D2, but I’m not sure. S1: Let us see if the professor reads us and can help us. T1: I confirm that the exercise is correct. Tomorrow, the lesson will begin with correcting this exercise because I observed that many people had difficulties with the group chat.

In Fig. 4 b, a student shows the execution of the exercise related to the resolution of a double integral; he shows how he identified the extremes of integration; although the exercise’s performance is correct, the exercise’s result is not correct.

S1: How do I find the domain and thus the extremes of integration? I have done it this way and cannot find it. S2: The exercise setup seems correct to me. You have made some calculation errors. S3: Here is my procedure. The result is correct. (Student S3 uploads the correct answer.)

In Fig. 4 c, a student reports on the teacher’s exercise and continues to carry it out in class.

S3: The professor asked me to publish the development of this domain done in the class because there were many students absent today. Good work! I hope it will be of help to you.

In Fig. 4 d, a student reports on the execution of the exercise.

The students discussed the teachers’ or tutors’ resolution of exercises in e-learning mode. The students chose the activities to be carried out, like in Fig. 4 a. The students ask for clarifications about activities they have encountered difficulties in, like in Fig. 4 b. Students share not completed exercises on the platform as their teacher left them this task as a stimulus, like in Fig. 4 c. Students share the platform’s tutoring exercises to support absent colleagues, like in Fig. 4 d. Thanks to all these interventions on the forum, the students’ shared posts and comments identify “Just in time”, the thematic cores deepened in the classroom, the misconceptions, and most common errors.

The aim has been to create a learning environment, a research community, and a living laboratory that stimulates ideas but, above all, motivates the students to ensure their educational success. Moreover, we tried to renounce the expressions “acquisition of knowledge” and “transfer of learning” and to think about learning in terms of legitimate peripheral participation (Lave & Wenger, 1991 ), to socially organized activities, understanding the educational process as social reconstruction starting from the biological forms of behavior (Vygotskij, 1987 ).

In addition to social interaction through the platform, students benefited from hours of practice with teaching assistants. Furthermore, small group activities were organized for students who did not achieve positive results in the first test. Experienced students supported these groups (generally 4 or 5 groups of 4 people), creating a social workshop to develop dynamics, experiment activities, design, share, and improve self-esteem and relational and communicative skills. In the following picture (Fig. 5 ), on the left, students work in groups in a circular arrangement during a PLTL laboratory at the Didactics of Mathematics Laboratory of the University of Salerno; on the right, a classic collection of students following a lecture.

a – d Some protocols from the Edmodo platform

Exercises and problems were submitted to students inspired by those carried out in the classroom: students did their homework in groups, often asking more experienced colleagues’ intervention. The bond of similarity perceived among the students involved in these educational interventions was based on their effectiveness. Feeling some commonality with the other people involved, sharing similar problems or everyday experiences with them, “seeing each other again” in other people’s actions/situations, etc. favored educational communication’s credibility and effectiveness. On the other hand, it changed students’ behavior and attitudes. Peer leaders have been seen as models to reread their experiences and acquire knowledge and skills of various kinds.

Data Analysis and Results

This section shows and discusses the case study results, analyzed from a quantitative and qualitative point of view.

Formative and Summative Assessment

The teaching activity was monitored continuously, not only through computer systems but also through two tests that have had a function of formative evaluation and summative evaluation. It made it possible to identify some students’ difficulties early, especially in mathematical competence. Those students who showed widespread fundamental deficiencies after the first test suggested that the study was supplemented with two additional hours of lessons, managed using the cooperative learning methodology. These integrative hours took place in a SCALE-UP learning environment. The students were divided into small groups and worked with a tutor who supported the students throughout the recovery of basic skills. The learning space was designed to facilitate student interaction and group interaction. The students’ results regarding essential mathematical competencies were collected following the first didactic interventions. It was obtained following the logic of mastery learning (Block & Burns, 1976 ), according to which all students can achieve basic goals in each discipline in enough time and with appropriate methodological changes. Two mid-term tests were given during the semester. The first test was on the topics of the first part of the course (functions of several variables, linear algebra, differential equations, curves, and integral curves). The second test was on the second part of the course (differential forms, multiple integrals, surface integrals, function series).

Below is an example of a question proposed to the students in the first test (Fig. 6 ).

To the left, a laboratory of SCALE-UP at the University of Salerno; to the right, a traditional classroom for the students

The following is an example of a question proposed to the students in a second test (Fig. 7 ).

A question in the first test

The following is an example of a question proposed to an examination test (Fig. 8 ).

A question of the second test

As can be seen from these examples of questions given to students during the tests and the exam, we tried to verify the skills acquired by the student or “the proven ability to use knowledge, skills and personal and methodological abilities to solve unknown problem situations” (EQF, 2005 ). The student’s skills were assessed considering the following dimensions: resources, i.e., the student’s basic knowledge and skills; interpretation structures, i.e., how the student reads and interprets problematic situations; structures in action, i.e., how the student reacts to a problem; self-regulatory structures, i.e., how the student learns from experience and adapts his strategies to the stresses coming from the context (Trinchero, 2012 ). In the specific case of the last question, the dimensions of competence evaluated are as follows in Table 4 .

The assessment of competencies was carried out based on the following assessment heading (Table 5 describes the four levels of competence).

The first test showed a rather high number of students who did not reach sufficient levels of competence in the items being studied, and only a few students acquired an advanced level, as shown in Table 6 .

The second test showed (in Table 7 ) a marked increase in the number of students who successfully passed the test, highlighting advanced skills.

The results were compared to the results of 117 students in the previous course of the same cohort, using the same assessment test format. It was found that 81% of students passed the exam in the winter session compared to 60% in the previous cohort. In addition, 58% achieved good results compared to 32% in the last year. The reported data seem to confirm a ten-year research record showing significant improvements in learning following the implementation of student-centered learning pathways (Beichner et al., 2006 ; Dori & Belcher, 2004 ).

These results seem to be following other research: Gavrin ( 2010 ) reported that 80% of the students in his JiTT class responded “yes” to “Do the JiTT exercises help you to be well prepared for the lecture?” versus 21% affirmative to the same question in “other classes”. He found a 58% vs. 18% split on “staying focused”, a 59% vs. 18% split on “feeling like an active participant”, and a 71% vs. 21% split on “finding classroom time useful” (Gavrin, 2010 ).

Satisfaction Questionnaire

At the end of the course, students were given a questionnaire to understand the difficulties encountered. When asked, “Have you experienced problems studying the course topics”, 63.8% state that they have located difficulties. The encountered difficulties concerned all the subjects with a higher incidence (39.1%) to study surfaces and surface integrals (Fig. 9 ). From the given test, the student’s satisfaction with the teaching strategies adopted and their cheerful disposition to the discipline study emerge, even though most claim to have encountered difficulties studying the discipline.

A question of examination test

The following question was asked: in your opinion, why did you encounter difficulties during the course?

The following graph (Fig. 10 ) shows the motivations most frequently cited by students due to the difficulties they encountered (90 students answered the question).

The difficulties of the subjects divided into topics

The motivations most frequently cited by students respond to the difficulties they encounter

The answers given by the students were as follows: The topics are difficult (34 students); we had little time to study the subjects (43 students); past deficiencies (28 students); the teacher was not always clear (10 students).

Although there were difficulties, many students highlighted that it was handy to give some space to the exercises and clarify the doubts that emerged on the platform in class.

In the following, there are some of the students’ answers to the satisfaction test:

S1: The lessons certainly have their difficulties, and that’s obvious. However, I appreciated how the teacher presented the topics and the time spent on the exercises in the classroom so that any doubts could be clarified in class. In most cases, the lessons went smoothly.

S2: I felt at ease, despite the difficulty of the topics dealt with; it was a pity not to be able to deepen them, but anyway, I am satisfied because the study of these topics gave me a wider view of the faculty I am attending.

S3: The course was not very simple due to the complexity of some topics but made easy by the teaching materials provided by the teacher and tutors.

At the end of the course, therefore, a better attitude to the study of the subject seems to emerge; from the satisfaction test, the appreciation of the use of alternative teaching methods appears in most students (79% appreciate the didactic innovations of the course very much, 10% enjoy much, 7% did not influence the educational success decisively, 4% prefer more traditional teaching).

Another important element of university teaching in STEM courses is the early drop-out of students due to low levels of knowledge in mathematics. An element that could be related to the effectiveness of the methodologies adopted is the reduction of dropouts compared to the previous year.

The dropout (4%) has been lower than the percentage of the previous year (10%).

Discussion and Conclusions

In this paper, the attempt to integrate the educational advantages of using the just-in-time teaching (JiTT) methodology with a blended online and in-class format teaching approach (Novak et al. 1999 ) in a Student-Centered Active Learning Environment with Upside-down Pedagogies (SCALE-UP) with the peer-led team learning methodology was examined. The students with whom the experiment was conducted attended the first year of engineering. Many of them considered mathematics an obstacle to further studies because of the subject’s difficulties and were not adequately motivated. We have focused on this research on these two aspects, studying and experimenting with alternative methodologies to frontal lessons to overcome obstacles of the discipline and encourage students to study mathematics. We have taken our starting point from methodologies already successfully tested in the USA, believing that one methodology does not always manage to be inclusive of all students to help them overcome the different and multiple difficulties of approaching mathematics.

Therefore, we have integrated JiTT and PLTL. In themselves, these two methodologies also included using an e-learning teaching that we thought to implement through the social platform Edmodo, both for its graphical interface and ease of use through the application available on mobile phones. These methodologies have been integrated harmoniously because their common cultural matrix can be found in Vygotsky’s and Bruner’s theories. The experiments were carried out during the whole semester, collecting quantitative and qualitative data.

The qualitative analysis based on the students’ answers shows considerable enthusiasm for using technological tools for continuous comparison with teachers and colleagues and supporting study.

From qualitative and quantitative data analyses alike, it seems that behavioral engagement is also positively associated with the realistic, practical, and guided discovery aspects of the task design, the activity structure, and the use of mobile technology. Additionally, working in a team also appears to have had a positive effect. Mathematics confidence is positively associated with real, guided, and practical tasks, with the use of technology, also appearing influential. Not surprisingly, both transformative and computational technology use is most significantly related to confidence using technology, with the variety of technologies noted as adding to flexibility and adaptability. In conjunction with the task design, the transformative and computational use of technology appears to have the most influence on students’ attitudes to using technology for learning mathematics.

In particular, the integration of JiTT and PLTL methodologies seems to provide learning outcomes coherent with the theses supported by the exponents of social constructivism and Vygotsky’s ideas, as students show to improve their skills under the guidance of a more capable peer acting in the proximal development zone. From the findings in the table related to the second test, it should be noted that there is an improvement in students’ performance in problem-solving; an increase in conceptual learning can also be seen (Fandiño Pinilla, 2008 ).

Although the small sample does not allow us to draw statistically significant conclusions, a definite improvement in the performance of the experimental class and a considerable increase in students’ interest and motivation were observed. As also confirmed by recent studies (Novak, 2011 ), JiTT seems to have activated learning that has respected the needs of the students, respected the time, and increased motivation to study. Thus, this first experimentation has successfully stimulated curiosity for new and more in-depth investigations.

JiTT seems to be encouraging all the class students to:

participate more actively and reflectively in the learning/teaching process;

share their experiences and points of view with colleagues on the course and with more experienced people; and

follow the lessons more actively and consistently in the classroom.

JiTT seems to have encouraged the experimenter teacher to:

show interest in the helpful mistake’s students make and offer corrective support;

take advantage of students’ mistakes to plan a more effective educational intervention in the classroom;

interact more directly with students;

amplify the time available for their lessons through synchronous and asynchronous interventions; and

encourage the student community to help each other.

Other qualifying aspects of the experience, to be further verified, have simplified the recovery by those absent from the lessons thanks to the e-learning method and availability of contents.

The SCALE-UP learning environment has made it possible for 45% of the students who had failed at the first test to make up for the fundamental shortcomings, increasing improvement.

The PLTL has contributed a lot to the recovery of basic skills because students were constantly confronted with their peers in line with Vygotsky’s research and pedagogical research on educational scaffolding methods.

One of the fundamental aspects highlighted by the students in the interviews is that the methodologies adopted to put the student at the center, his needs, and the educational activities of the teacher have been adapted to theirs. This seems to have spurred them to participate in both presence and online courses. Strategic management of these core components consists of the analysis, decisions, and course of action that an organization or individual that operates programs or classes needs to create and sustain to ensure the quality of learning. Active participation in the lessons has improved student performance, as evidenced in other studies, as evidenced by the results of the tests. The teacher’s presence in discussions has facilitated learning and clarifying any learners’ questions (instructor participation in class discussion). Therefore, attention to the discussion, especially conceptualizing, has been very important in learning processes. For example, in mathematics, it is justified every time the constitution of a mathematician is involved, from the outside (real-world mathematization) or the inside of mathematics (theory of functions).

The approach to the discussion was understood as an attempt to provide a set of tools for analysis and planning by the experienced teacher without reducing the responsibility of the pupils. This Vygotskyan process referred to interactions between subjects (teachers and pupils) who played different roles that must be preserved and valued in the teaching–learning activity. An important aspect was encouraging peer learning within a teaching community (also virtual) by creating working groups or encouraging the accessible aggregation of students in working groups through team-based learning methods. Like Vygotsky suggested, peer communication also allowed internalizing cognitive processes implicit in interactions and provided new patterns that influenced individual thinking, emphasizing the proximal development zone. The quantitative data concerned improving the skills found by comparing the results of the tests carried out during the semester and a satisfaction test. From the beginning, the experimentation shows greater participation of the students in the educational dialogue and the class because the lesson was inspired by their training needs, the difficulties encountered in carrying out the homework, and the need to respond to their request to overcome specific cognitive barriers.

The data show an improvement of the student’s performance compared to students of the previous year’s cohort. The satisfaction test shows a better affective disposition of the students towards the study of mathematics. After these tests, the experimentation also continues with students, integrating further stimuli to the study, such as augmented reality for studying functions in two variables. This first experiment successfully stimulated curiosity for new and more in-depth investigations. Although the smallness of the sample does not allow us to draw statistically significant conclusions, a clear improvement in the performance of the experimental class and a considerable increase in student interest and motivation have been observed. The success of the didactic intervention is also highlighted by the small number of dropouts (4%), lower than the percentage of the previous year (10%). Other qualifying aspects of the experience, not negligible, to be subjected to further testing, were facilitation of reintegration by the absents from the lessons thanks to the e-learning method of delivery of some contents and the attention paid to students with special educational needs who were able to fill their gaps and felt involved in the educational activity.

The educational findings can be summarized as follows:

students’ ability to solve problems is improved.

their conceptual understanding is increased

their attitudes are better

failure rates (especially for women and minorities) are drastically reduced

Thanks to SCALE-UP, scaffolding is intellectual, technical, organizational support, emotional, cognitive, and metacognitive. Emotional because it aims to stimulate the learner to learn, encourage them, and encourage them to overcome any barriers of a motivational nature. Meta-cognitive is intended to support the learner in acquiring specific knowledge or competence and developing metacognitive skills that will enable them to learn. In this way, a Calculus course has been of service to the student and colleagues in subsequent classes.

The research findings showed that blended learning by integrating several teaching methodologies can provide students with the tools for a better predisposition to learning. In addition, the integration of JiTT and PLTL in a SCALE-UP learning environment seems to confirm the idea that social interactions are at the origin of the construction of individual skills and that possessing individual skills of a certain complexity allows the individual to subsequently participate in more complex social interactions, which in turn will enable the construction of skills of higher complexity.

This article is a prequel to other articles by the author on teaching mathematics in STEM courses. This study’s qualitative and quantitative data show that student participation, student-to-student interaction, and teacher-to-student interaction have increased thanks to teaching methodologies such as JiTT and PLTL in a SCALE-UP learning environment. The social platform seems to have influenced this process. It was thus decided in the following years to use an adaptive e-learning platform to support students in finding the material and increase the levels of participation, engagement, and motivation.

This preliminary feasibility study provided the basis for more detailed studies based on the analysis of factors such as participation, engagement, and motivation and the impact on improving students’ competencies. This preliminary study aimed to compare how mathematics teaching in STEM courses changed before, during, and after the COVID pandemic (Branchetti et al. 2021 ; Capone & Lepore, 2020 , 2021 , 2022 ).

Change history

20 july 2022.

Missing Open Access funding information has been added in the Funding Note.

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Capone, R. Blended Learning and Student-centered Active Learning Environment: a Case Study with STEM Undergraduate Students. Can. J. Sci. Math. Techn. Educ. 22 , 210–236 (2022). https://doi.org/10.1007/s42330-022-00195-5

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Active learning tools improve the learning outcomes, scientific attitude, and critical thinking in higher education: Experiences in an online course during the COVID ‐19 pandemic

Izadora volpato rossi.

1 Postgraduate Program in Cellular and Molecular Biology, Federal University of Paraná, Curitiba Brazil, Brazil

Jordana Dinorá de Lima

Bruna sabatke, maria alice ferreira nunes, graciela evans ramirez.

2 Technological Professional Education Sector, Federal University of Paraná, Curitiba Brazil

Marcel Ivan Ramirez

3 EVAHPI ‐ Extracellular Vesicles and Host‐Parasite Interactions Research Group Laboratório de Biologia Molecular e Sistemática de Tripanossomatideos, Carlos Chagas Institute‐Fiocruz, Curitiba Brazil

Associated Data

Active teaching methodologies have been placed as a hope for changing education at different levels, transiting from passive lecture‐centered to student‐centered learning. With the health measures of social distance, the COVID‐19 pandemic forced a strong shift to remote education. With the challenge of delivering quality education through a computer screen, we validated and applied an online course model using active teaching tools for higher education. We incorporated published active‐learning strategies into an online construct, with problem‐based inquiry and design of inquiry research projects to serve as our core active learning tool. The gains related to students' science learning experiences and their attitudes toward science were assessed by applying questionnaires before, during, and after the course. The course counted on the participation of 83 students, most of them (60.8%) from postgraduate students. Our results show that engagement provided by active learning methods can improve performance both in hard and soft skills. Students' participation seems to be more relevant when activities require the interaction of information, prediction, and reasoning, such as open‐ended questions and design of research projects. Therefore, our data show that, in pandemic, active learning tools benefit students and improve their critical thinking and their motivation and positive positioning in science.

1. INTRODUCTION

Academically first‐world countries have debated how the training of students should be, from basic primary education at schools to higher education at universities. 1 , 2 , 3 , 4 A major concern is how education can collaborate in the formation of citizens and professionals capable of leading technological, economic, social, cultural, and political changes. 5 , 6 , 7 Specifically, in the area of science, researchers should be trained with skills that go beyond the technical reproduction of experiments, but that employ critical thinking and that are capable of applying scientific concepts to propose solutions and generate knowledge. 8 , 9 , 10 The change of curricular programs in the STEM area (science, technology, engineering, and mathematics) and new proposals for educational strategies have been stimulated in different countries. 11 , 12 Lecture‐based and teacher‐centered pedagogy is undergoing a shift toward more active learning, in which students build their own understanding of a subject through learning activities. 13 , 14 The benefits of active learning seem substantial, both in cognitive learning and in the development of soft skills by students, such as leadership, problem‐solving, and autonomy. 15 , 16 , 17 In Brazil, few efforts have been made to discuss structural changes in education from basic to university. The absence of adequate working conditions encourages teachers to adopt an old‐fashioned type of education, in which passive teaching methods predominate. Although there is no state initiative that encourages the incorporation of active learning methods, some higher teaching institutions have introduced methods of problem‐solving, critical thinking, and/or problem‐based learning with inspiring success. 18 , 19 , 20 , 21

Active learning comprises approaches that focus more on developing students' skills than transmitting information and require students to perform activities that require higher‐order thinking. 13 For this, students use critical thinking, which involves analysis, reflection, evaluation, interpretation, and inference to synthesize information that is obtained through reading, observation, communication, or experience to answer a question. 22 There are several methodologies that fit the concept of active teaching, such as inquiry‐based learning, project‐based learning, and problem‐based learning. 17 , 23 , 24 Among them is, for example, project‐based learning is a model that organizes learning around projects, in which challenging questions or problems are involved that involve proposing solutions, formulating hypotheses, and investigative activities. 17

The COVID‐19 pandemic has produced a situation of health emergency, economic, and social instability that challenged the entire educational system. The intense contact and exchange of information that took place during face‐to‐face classes in normal life have been restricted to virtual spaces. Given all these sudden changes, online courses have been a viable option to prepare students at different levels (Figure 1 ). Although some groups have already reported their teaching experiences and perceptions in times of lockdown and social distance, 25 , 26 , 27 , 28 , 29 , 30 , 31 very few of them reported the impact of active learning on online courses, and rarer are the studies in postgraduate students. During the pandemic, we have seen the opportunity to validate a course model with the aim of actively encouraging students of higher education to acquire important biological concepts. We planned to create a rich, multifaceted course that integrated active learning methodologies. We incorporated active‐learning strategies that allowed transit in the course from passive lecture‐centered to active student‐centered learning. With this approach, we were interested in understanding the benefit of our course at the student formation and in answering two important questions:

Does the course increase the cognitive and intellectual skills of the students?
How was the impact of critical thinking methodologies on the student's attitudes toward science and soft skills?

Our interest was concentrated in analyzing whether students through the course showed more enthusiasm for the concept of research and science. Crucial elements in science such as forming and testing hypotheses, defining strategies, communicating results were evaluated to determine whether critical thinking methods could improve thinking and rational logic. In order to assess students' gains in these two aspects, we applied questionnaires to students before, during, and after the course. Here, we will comment on the results of this experience that incorporated active methodologies and student‐teacher interaction tools for remote higher education.

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Passive (teacher‐centered) and active (student‐centered) learning in classroom or remote teaching models

2. MATERIAL AND METHODS

2.1. undergraduate pilot course to validate online active learning tools.

In order to validate an online course model and test some active learning tools, we have offered a course aimed primarily at undergraduates. The subject of this course was cell culture which has a wide interest and application in the biological area. Knowledge on cell culture is required for some research activities and also represents a promising alternative for replacement of animal experimentation.

In order to follow contagious preventive actions during the COVID‐19 pandemic, the course was administered remotely in a teleconference format through the Microsoft Teams platform. This platform allows the instructors to interact through video, audio, and live chat, which gives the feeling of a personal meeting from a safe distance. Before each class, there was a moment of relaxation with “icebreaker” conversations to get to know the audience. This moment helped to create a more intimate environment and also to share tensions and concerns about the pandemic.

The course had a total of 15 h, 10 h of synchronous activities and 5 h of asynchronous activities. Synchronous activities included lectures, simultaneous online quiz activities, and discussion of scientific papers. Asynchronous activities consisted of two questionnaires containing guided questions for critical reading of a scientific paper (one of the papers involving chronic diseases and the other infectious diseases). After returning this questionnaire, the papers were discussed during classes. To measure perceptions of the overall effectiveness of the course and the proposed methodologies, we asked students to complete a questionnaire at the end of the course.

2.2. Experimental undergraduate and postgraduate course

2.2.1. course design.

The experimentation course was offered as a satellite event during a symposium hosted by a Postgraduate Program at a Brazilian state university. The focus of the course was redefined from our previous basic course to contemplate strategies for the study of infectious diseases using cell culture. In order to know the profile of the enrolled students, we applied two questionnaires containing open and closed questions: one with demographic questions and previous research experience and the other about their previous experiences with active learning methodologies.

The course had a short duration (12 h total), divided between synchronous (7 h) and asynchronous activities (5 h). The synchronous activities of the course were structured as follows: (i) 2 h of key concepts to introduce the subject and situate the content and emphasis of the course; (ii) 2 h of strategies for studying the pathogen‐host cell interaction using cell culture, (iii) 1 h of presentation of an inquiry research project (IRP) with the subject chosen by the participant, (iv) 1 h of questions about concepts and strategies to solve problems (Table 1 ). The “offline” time was used to prepare the scientific IRP and participate in the questionnaires with questions related to the classes. The description of the activities developed can be found in the topic “Active learning instruments/tools” below.

Course schedule

Learning activities	Description	S.A.T.	A.A.T.
Lecture 1. Introductory concepts		2 h	0
Lecture 2. Study strategies of pathogen‐host cell interaction using cell culture		2 h	0
Simultaneous online quiz	Quick fixation questions answered online in real time and then corrected	1 h	0
Inquiry research project	Preparation and presentation of IRP with theme chosen by the participant	1 h	3 h
Problem‐based inquiry	Questions of class related concepts and strategies for solving biology problems	1 h	2 h

Abbreviations: A.A.T., asynchronous activities time; S.A.T., Synchronous Activities Time.

2.2.2. Active learning instruments/tools

In order to place the student as the center of the course, we incorporated some active‐learning strategies into an online course construct. Some moments of the dynamics of the classes and the approaches used during the course are gathered in Video S 1 . We proposed some activities that required student's engagement:

The quiz was a knowledge fixation tool performed at the end of lectures. In this activity, participants answered questions related to the presented content directly through the Voxvote website ( https://www.voxvote.com/ ). Table 2 contains some examples of applied questions; the questions were corrected at the end of the time proposed by the VoxVote tool (Video S 1 , min 02:36–02:51).

Examples of questions administered during live quiz using VoxVote

We proposed to the participants to develop an IRP to stimulate the construction of knowledge and critical thinking. The IRP should contain the scientific relevance of the project, main objectives, and methodologies to achieve the proposed objectives. Along with the description of the project, participants could send a graphic design summarizing their project proposal, following a Graphical Abstract model indicated as a reference (Figure S 1 ). The IRP was sent using Google Forms. The IRP proposals were evaluated by all instructors who selected the best 10 for presentation based on criteria of coherence and conceptualization of the biological question, ampleness of the applied methodologies, and connection between the proposed strategies.

Inquiry questionnaires

Two online questionnaires were sent to all participants via email and were available for at least 48 h. Both questionnaires contained eight multiple‐choice and four open‐ended questions about biological concepts related to the course subject. The first questionnaire (Q1) was available before the beginning of the course, while the second (Q2) was available 2 days after the experimental course started. Q1 and Q2 had the same level of difficulty, with multiple‐choices (basic) and problem‐based questions (open‐ended) (see Table 3 ). Q2 was answered while the students were simultaneously participating in several activities of the hosted event.

Examples of questions applied in the inquiry questionnaires



The fluidity of the plasma membrane increases with:	You read in a scientific article that Dexamethasone (a corticosteroid type drug) helps in the treatment of coronavirus infection, but the article provided only clinical data on mortality, intubation rate, or length of hospitalization time. How would you investigate the mechanism of action of Dexamethasone for the benefits seen in the study?


Check the correct alternative regarding the immune system:	One of the mechanisms of fungi and bacteria virulence is the formation of biofilm. These structures contribute to antibiotic resistance. How would you experimentally demonstrate that biofilm is important in the pathogenesis of disease and for antibiotic resistance?

2.2.3. Inquiry questionnaire assessment

Questionnaire responses were corrected by five evaluators. Multiple‐choice questions scores were calculated by sum of the right answers. Open‐ended questions required a more detailed evaluation process where four evaluation criteria were scored in each answer: comprehension, specificity, ampleness, and connection. All evaluators considered whether the student had understood the question (comprehension), the approaches that the student proposed to solve the problem (ampleness), the specificity of this or these approaches (specificity), and the rationale and feasibility of the strategy (connection). For comprehension evaluation only 0 (lack of comprehension) and 1 (adequately answered). The other criteria considered three levels of score: insufficient (0), good (1), and excellent (2). The maximum score was seven points for each answer. Answers zeroed in comprehension were not evaluated in the remaining criteria. Furthermore, the order of questions and answers were randomized to avoid possible bias during the assessment process. The scores were generated from the average of five evaluators. Total score was calculated by the sum of multiple‐choice questions (0%–50%) and open‐ended questions (0%–50%).

Intra‐questionnaires comparisons, that is, between questions, were assessed by ANOVA, while questionnaire differences were analyzed by unpaired t test. All analyses were performed in GraphPad Prism version 6.01.

2.2.4. Analysis of students' perception of the course

At the end of the course, students were asked to fill up their impressions and suggestions about the course in a feedback form containing multiple‐choice and open‐ended questions. Some questions were to choose the sentence which they felt more identified and in others the students evaluated sentences in a five points scale, with 0 being “nothing” and 5 being “very” (Likert scale. 32 ). Open‐ended questions were added to stimulate the students to express their opinion about the course. The open‐ended data were coded in categories considering the most cited answer for each question. Qualitative thematic content analysis was applied to quantify answers, providing support for a quantitative evaluation.

3.1. The online course can be a platform of active learning methodologies: A pilot experience

In order to validate an online course model and test some active learning tools, we have offered a course aimed primarily at undergraduates during pandemic. The wide theme Cell Culture was well received by students, attracting participants from different fields of health sciences (including biology, biomedicine, pharmacy, biotechnology, and medicine—data not shown) and with different backgrounds (3.37% bachelor degree, 56.75% undergraduate students, 18.91% mastering students, 4.72% masters, 10.13% doctoral students, graduate course 2.02% and 4.05% doctoral also participated. n = 148. Figure S 2 A).

The great advantage of remote education is being able to bring together or to mix participants from different educational institutions and different backgrounds. Participants were from 22 different Brazilian institutions and 1 foreign institution, with public and private education (Figure S 2 B).

Although only 29% of students had worked with cell culture, the positive perception of the course was very high (Figure 2a ). Moreover, 87% of the participants evaluated the course as excellent (Figure 2b ). Active learning tools used during the course (real‐time online quiz [live], paper reading guide, etc.) was positively rated by participants (data not shown) and the participants pointed out as main strengths the didactics, teaching methodology, and the interaction between teacher and student (Figure 2c ).

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The methodology tools used during the validation course were positively evaluated by the participants. (a) Course evaluation by participants. (b) Contribution in the course in learning cell culture. (c) The open‐ended question on “course strengths” was content analyzed, and the responses were classified into categories that included similar statements

Excited by the positive experience of the first course, we decided to go deeper into a course aimed at postgraduate students to understand whether active learning tools could improve their cognitive and thinking skills. With the validation and approval of the active learning approach, we decided to maintain some activities (such as the real‐time online quiz and questionnaires) and adjust some activities targeting the topic to the participants.

3.2. Experimental course: Active learning tools improve the performance of students in higher education

3.2.1. participants students profile: a representative sample of brazilian higher education.

The second experience with the online course model had a heterogeneous audience profile, including participants with different levels and from different locations. There were 83 enrolled, most of them master students (38.0%) (Figure 3a ). Undergraduate students constituted 24.1% and PhD students 19.0%. There was also the participation of PhDs, constituting a very heterogeneous public. The participants belonged to 22 Brazilian institutions from different states (Figure 3b ). Although 94% had previous research experience, only 59.4% had experience in cell culture (Figure S 3 A), either carrying out in vitro experiments (full experience) or just accompanying other people (partial experience) (Figure 3c ). The focus of the course was infectious diseases, which was the object of work of 59.5% of participants, including the biological model of bacteria (20.3%), fungi (15.2%), parasites (16.5%), and viruses (7.6%) (Figure S 3 B).

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The audience of attendants to the course was heterogeneous. (a) Participants' educational background, divided between complete and incomplete. Others include “specialist” as complete and “Incomplete second degree” and “residency” as incomplete. (b) Distribution of participants' institutions in Brazilian states (highlighted in gray). (c) Students' previous experience with cell culture techniques

To obtain an overview of students' previous experience with teaching methodologies, we asked students ( n = 60) about which method was most used during their academic experience. The majority of the respondents (76.7%) affirm that their predominant teaching approach was passive, mainly represented by traditional lectures (Figure S 4 A,B). Among graduate students, 50% answered that their classes have similar proportions between active and passive classes (Figure S 4 C). When asked in an open question about what could be improved in their education (undergraduate or graduate), 72.1% of students admitted that other teaching approaches could be employed (data not shown). Most comments pointed to the necessity of interactive classes, including solving clinical cases and practical application of knowledge. The answers pointed out that most of the students (76.7%) consider that active teaching methodologies are excellent for their learning and that participating interactively in the subjects improve their apprenticeship (Figure S 4 D).

3.2.2. Active methodologies promote improved short‐term learning outcomes

Interested in observing the development of students during the course, we used research‐based learning approaches through the application of questionnaires in a pretest (Q1) and posttest (Q2). Fifty‐four students participated in the online questionnaire activities (Figure S 5 —graduation: n = 14; masters: n = 25; doctoral: n = 14; postdoctoral: n = 3; other: n = 1). Most of them participated in the first questionnaire (Q1: n = 49), while a minority participated in the second one (Q2: n = 26); finally, 20 students participated in both questionnaires.

The average scores of students in the questionnaires were higher in Q2 compared with Q1 (Figure 4a , Table S 1 ). This progress was distributed similarly through multiple‐choice (13.51%) and open‐ended questions (15.67%). On average, no student had zeroed their score in Q2, which may represent that students were more committed to the second test (Figure 4a ). The proportion of students with high performance (total score > 80%) was at least three times higher in Q2 compared with Q1 (6.1% at Q1 and 19.2% at Q2. Figure 4b ). The students showed improvement in all four criteria evaluated in the open‐ended questions from Q1 to Q2 (Suppl. Figure 6 ). When multiple‐choice and open‐ended questions were analyzed separately, Q2's superior performance was predominantly due to the scores at the multiple‐choice questions (Figure 4c ) than from the open‐ended (Figure 4d ).

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Students showed a rapid evolution in their performance during the course. (a) General average score in each questionnaire (0%–100%); multiple‐choice and open‐ended questions represent 50% of the score each; (b) Proportion of students within score ranges in Q1 ( n = 49) and Q2 ( n = 26). (c) Students' scores average only in the multiple‐choice questions between questionnaires; (d) Students' scores average only in the open‐ended questions between questionnaires

We hypothesized that the overall improvement of open‐ended questions may be due to a lower engagement at the more difficult and exploratory questions (such as the open‐ended questions). Regarding this point we calculated the student dropout rate to each question by the rate of NA answers—that is, described as blank answers and “I don't know” type of answers. In fact, the dropout for open‐ended questions (Q1: 22% and Q2: 15%, Table 4 ) was higher than for multiple‐choice questions, which was irrelevant (Q1: 2% and Q2: 0%). Furthermore, there was a 31.8% reduction in the dropout rate in open‐ended questions from Q2 compared with Q1 (Table 4 ). This may indicate that the students felt more confident and motivated to commit intellectual effort during the performance of Q2, resulting in a better outcome.

Dropout rate among open‐ended questions in Q1 and Q2

	OE 1	OE 2	OE 3	OE 4	Dropout average
	14%	32%	22%	20%	22%
	19%	11%	7%	22%	15%

Note : Dropout was considered for blank answers and “I don't know” type of answers. “OE” stands for open‐ended questions from 1 to 4 in each questionnaire.

3.2.3. Formulating hypotheses and proposing strategies: A scientist‐like experience through project‐based learning

The inclusion of project‐based learning strategies is effective in STEM courses, to involve students in authentic “real world” tasks. 17 , 33 During the course, students were motivated to prepare a mini scientific project to answer a biological question of their interest; applying cell culture strategies (see Materials and Methods). The elaboration of the scientific IRP represented the most demanding activity for the student and we had only 26.5% of participation (22 IRPs), most of which are master's students (Figure S 7 ). This type of activity was a challenge for the students, who feel freedom to “think outside the box” and find ways to answer their biological questions. Many students elaborate different and curious hypotheses, from which the instructors selected the 10 best IRPs based on criteria of coherence, conceptualization, applied methodologies, and connection between the proposed strategies. We were able to see some students who stood out for the quality of their IRP proposal. Interestingly, among the 10 best IRPs selected, the fourth part was written by undergraduate students (data not shown). In addition, we reserved a period of the course for the presentation of the selected IRPs to the whole class at a “symposium‐like moment,” using their graphical abstracts as support. This type of activity adds other soft skills to students, such as communication and accepting challenges, essential for future scientists. Part of the presentations of the selected students and their graphical abstract/poster as other course activities were compiled in Video S 1 (min 03:01–03:51).

3.2.4. Engagement in active‐learning activities correlates to better student performance

Active methodologies place the student as the center of learning and for this reason, their effectiveness relies heavily on the student's engagement in activities. Motivated by the various studies that show a positive correlation between student engagement and performance, 12 , 34 , 35 , 36 , 37 , 38 we assessed whether the most engaged students during our course had higher scores.

First, we evaluated the scores of the group of students who participated in both inquiry questionnaires (“BOTH”) separated from those who have answered only one of the questionnaires (“ONLY Q1” or “ONLY Q2”). This analysis showed that students that were engaged in both activities had higher performance in open‐ended questions, but not in multiple‐choice (Figure 5A,B ).

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Highly engaged students have better performances in open‐ended questions. (a) Students' scores average in the multiple‐choice questions within each engagement subgroup; (b) Students' scores in the open‐ended questions within each engagement subgroup. (c) Venn diagram, representing the number of participants in each activity (Q1, Q2, IRP, and TOP IRP). (d) Total score (%) in Q1 and Q2 analyzed in groups classified by the level of engagement in the course activities. The questionnaire to which the average scores refer is indicated by the horizontal bars (Q1 or Q2). (e) Students average in multiple‐choice questions within each group engagement. (f) Students average in open‐ended questions within each group engagement

We hypothesized whether engagement in activities proposed during the course (questionnaires and IRP) would be related to the best performance of students. For this, we considered the following groups: students who had been selected as TOP IRP and also participated in both Q1 and Q2 (TOP IRP + Q1 + Q2, n = 5), students who participated in Q1 and Q2 and sent IRP (but were not TOP IRP, named IRP + Q1 + Q2, n = 6), students who only participated in the questionnaires (BOTH Q1 and Q2, n = 9) and those who participated in only one of the questionnaires (Only Q1, n = 23 or Only Q2, n = 3) (Figure 5c ). Interestingly, half of the students who were selected as TOP IRP also engaged in both Q1 and Q2 ( n = 5). The students who participated in all activities had higher score levels when compared with the other groups of engagement, mainly in the open‐ended questions analyzed separately (Figure 5d ). Among the students who participated in the IRP, the best scores were from the students who were in the top‐10 IRP (TOP IRP) (Figure 5c,d ). Our data show that the participants who answered only one of the questionnaires (Only Q1 or Only Q2) had the worst scores in the open questions and shows that involvement in more than one activity improves the student's performance (Figure 5d ). Altogether, the data show a positive trend in the relationship between engagement and performance (Figure S 8 ).

3.2.5. Active learning tools improve students' critical thinking and motivation in science

The evaluation of the course was positive by 74% of the participants ( n = 50), who considered that the course was excellent (Figure 6a ). The open‐ended questions on “Course strengths” and “Course weaknesses” were content analyzed, and the responses were classified into categories that included similar statements (Table 5 ). Among the strengths, 70% of the students considered the didactics as a strong point, which includes the quality of the presentations, the confidence of the instructors regarding the domain of the content, the lesson plan, and the dynamics of the class. Fifty‐six percent of the participants assessed that the student–teacher interaction was a positive aspect of the classes, where the students revealed that they felt included (even remotely). Another point highlighted as strength of the classes was the teaching methodology and the subjects covered, which brought a balance between variety and depth. As negative points of the course, issues with infrastructure and technical problems (such as timetable, platform, class time, sound) and course complexity for a short time were mentioned.

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Students demonstrate a positive feeling about active learning tool. (a) Percentage of responses from students on the multiple‐choice question “How do you think the course contributed to your learning?,” with possible answers “excellent,” “moderate,” and “insufficient.” (b) Percentage of responses to the multiple‐choice question “In the questionnaires, what type of question do you prefer?” with possible answers “multiple‐choice,” “open‐ended,” and “I have no preference.” (c) Percentage of students' responses to the question “How do you evaluate the problem‐based questions present in the questionnaires?” with possible answers “They were excellent,” “They were very difficult,” and “They were very simple.” (d) Percentage of responses to the question “How did you feel during the conduct of the inquiry research project?,” with possible responses being “motivated,” “comfortable,” and “apprehensive.” The percentage of responses was calculated on the number of students who answered the questionnaire ( n = 50)

The main positive points cited by the students were didactics, teaching methodology, and instructor–student interaction

Response category	Students answers (%)
Effective course components (course strengths)
Instructors didactics	70
Content organization	24
Active teaching methodology	32
Interactivity between instructors and students	56
Suggested course improvements (course weakness)
Infrastructure and technical problems (timetable, platform, class time, sound)	46
Activities complexity	6
Didactics	14
Deviation from content	6
Online/remote course model	6
Course complexity for a short time	42

Note : content categories in the table represent any categories included by more than 6% ( n ≥ 3) of students who responded to feedback. The open‐ended questions on “course strengths” and “course weaknesses” were content analyzed, and the responses were classified into categories that included similar statements.

The students' feelings about the course's active learning tools were assessed by the feedback form. Students were instructed to rate from 1 to 5 on how positive the online inquiry questionnaires were for their learning, being 1 “negative” and 5 “very positive.” The average score of the responses was 4.34, indicating that the questionnaires were validated by the students. Regarding the type of question contained in the questionnaires, 48% of students prefer multiple‐choice questions (Figure 6b ). This shows that at least half of students prefer questions that students prefer questions that only recall information and do not require elaborating their own reasoning. Despite the high preference for multiple‐choice questions among the participants (48%), 62% considered that discursive problem‐solving questions are a great way to make them think critically and formulate strategies for real situations that a researcher faces (Figure 6c ).

One of the proposed activities was the writing of an IRP about some biological question of their interest. The participation rate in IRPs was relatively low (26.2%), being 68.2% postgraduate students. Interestingly, 54% of the participants felt motivated during elaboration of the scientific project (Figure 6d ). In an open question, the participants affirm that the elaboration of an IRP improves its positioning in science, becoming more critical and more motivated. It is also mentioned that the IRP stimulates the acquisition of more knowledge, they are able to expand their scientific vision, simulate a real situation of researchers, and collaboration in scientific communication (data not shown).

In general, there was a demonstration of positive perception regarding active learning methodologies by most students (96%) (data not shown). The main points commented by the students regarding their perception of active methodologies were that they are more effective for lasting learning, stimulate critical thinking and improve the dynamics of the class and the student–teacher interaction.

When consulted in an open‐ended question about the skills they improved with the course, the answers were directed to three points: incorporation of knowledge, motivation about science, and gains in their skills on scientific processes. Forty‐four percent of the participants cited an improvement in their logical critical and rational thinking. A gain in knowledge of the subject was pointed out by 22% of them, and the expansion of the vision by 20% (Figure 7a ). It is also interesting to note that 94% of the participants indicate that the course was able to give a real insight into problems that scientists face in their research. When questioned how motivated they are to solve scientific problems using critical thinking after the course on a scale of 1 to 5 (1: nothing; 5: very), the average response was 4.14, with a rating of 4 and 5 by 86% of them (Figure 7b ).

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Object name is BMB-49-888-g007.jpg

Active methodologies are able to increase the incorporation of knowledge, motivation in front of science and students show gains in soft skills. (a) Answers to the open question “what are the main gains you obtained with the course?” were categorized among common themes (showing categories that comprise 6% [ n = 3] or more of the answers). (b) Student responses to the question “how motivated are you to solve scientific problems using critical thinking after the course?” on a scale of 1 to 5 (1: Nothing; 5: Very). The percentage of responses was calculated on the number of students who answered the questionnaire ( n = 50)

4. DISCUSSION

The constant concern with excellence in the scientific training of academics encountered a new challenge during the COVID‐19 pandemic: how to engage students in effective learning in remote education? This question was the driving force of our study, which reports a semi‐experimental online course for higher education. Our course incorporated active methodology tools that promoted the integration of students in the construction of knowledge and stimulated their critical thinking skills. For this, we proposed problem‐based learning strategies in questionnaires, elaboration of a scientific project, and online quiz in order to complete the lectures. In the last few months, there has been a huge increase in the number of studies dedicated to developing and validating active‐learning strategies in remote or hybrid education, driven by the pandemic. 28 , 39 , 40 , 41 , 42

Our study was interested in evaluating mainly two types of achievement in students: (i) Cognitive and intellectual skills (learning outcomes) and (ii) Critical thinking, attitudes toward science and soft skills. For this, different activities and questionnaires were applied before, during, and after the course. Our data show that student engagement in the different active learning tools proposed is directly linked to their performance in the course. The average score of the groups that participated in all the proposed activities and stood out in the writing of the IRP was considerably higher compared with the groups with less involvement in the course when evaluating the discursive questions. In fact, other studies have already shown that active learning approaches in the classroom improve academic performance. In a long‐term study (3 years), the implementation of problem‐based learning (PBL) and learning by teaching (LbT) resulted in an increase from 5 to 6–7 in the average scores in final exams of engineering students. 43 Interactive‐engagement also shows score improvements in physics courses compared with traditional pedagogical strategies. 44

Our data show that student involvement is a key point for their learning. This is widely accepted and experienced at different levels. 45 , 46 Emotional, behavioral, and cognitive dimensions can be considered when analyzing engagement. 47 First, emotional engagement happens when students are emotionally affected and motivated by the learning environment. 48 In our courses, introductory icebreakers and friendly communication was a factor that contributed to students to feel comfortable in interacting with instructors and with each other. Second, behavioral engagement corresponds to attitudes students demonstrate in class, such as listening and paying attention to the class or the persistence and concentration in activities. 49 In this scenario, at least three forms of interaction were provided (chat, audio only, and video), in which the chat demonstrated that students were constantly connected to instructors during the presentation. Finally, cognitive engagement happens when students apply their ability to select, connect, and plan in constructing and self‐regulating the learning process. 47 , 50 Here, these movements were detected, under our point of view, in the construction of the IRP and in the responses to open‐ended questions in both questionnaires, in which students provide strategies to real problems inside and outside their fields of study. All three‐dimensions of engagement are linked together and may contribute to improvement on students' academic performance, then one should not consider them solely.

Beyond the intellectual benefit, traditionally used as teaching quality indicators, we hypothesized that student‐centered teaching methodologies would lead to a positive attitude or perception with science and thinking skills. In a self‐assessment, students reported that they had an improvement in their critical thinking, which involves judging the information with criteria and healthy skepticism. This relationship between active learning and improving critical thinking has been reported in other groups around the world. 22 , 51 , 52 Active‐learning strategies (such as collaborative work in small groups and case studies) improved students' critical thinking skills as measured by the Watson‐Glaser Critical Thinking Appraisal, which assesses decision‐making ability as well as predicts judgment, problem‐solving, and creativity. 53 Umbach and Wawrzynski 54 analyzed two sets of American national data and showed a positive relationship between university environments where teachers used active and collaborative learning techniques and students' gains in personal‐social development. Improving students' ability to recognize problems and apply effective strategies and solutions to fundamental challenges in the field is the basis of good scientific training. Our results show that tools of active methodology can impact the attitude of students that will be reflected in future scientists able to position themselves in the face of problems.

The improvement of the indicators added to the approval of the course by the students confirmed that the approaches were well chosen and encouraged us to write our experience in order to facilitate the implementation of active methodologies in other courses. We opted for active learning tools that could be easily applied to the virtual environment, improving the dynamics of the classes. Online questionnaires seem to be a great option for validating students' learning, and makes them reflect on the class and apply their knowledge in the answers. Because our courses aim at a scientific formation associated with the resolution of real problems, the questionnaires addressed both concept questions and interpretive/exploratory open‐ended questions. This allowed us to highlight a clear problem in Brazilian education: students are trained as “information recorders/archivers” and not as “critical thinkers,” as many students showed good levels in concept questions and poor performance in problem‐based questions. The use of open and closed questions is ideal to provide greater freedom of responses for students and to stimulate reasoning, but they also need clear criteria for their correction. In order to guarantee the impartiality of the corrections, all five instructors of the courses corrected all the questions and the scores were given by an average between evaluators.

During the course design, we were interested in getting immediate feedback on student learning in relation to the main concepts discussed. For this, at the final of everyday classes, ~10 final minutes were reserved for an online quiz. This activity was very interesting to reaffirm “take home messages,” that is, what the student cannot “get out of class” without learning and their perception about the acquired knowledge. There are several online tools for this type of quiz, and we emphasize that the most interesting ones are those that allow a real‐time assessment of the result with a percentage of “votes” in each of the questions. This allows questions to be promptly corrected and students can use that time to clear up any doubts.

During the undergraduate course, we opted for a questionnaire that represented a “critical reading guide” for scientific papers. Participation in the questionnaires was very positive, but we replaced this activity with the elaboration of a mini‐scientific project in the graduate course, since reading scientific papers is a basic/trivial activity for graduate students. The preparation of the IRP represented the most demanding activity for the student, because there he should use the knowledge of the course to answer a scientific question of his preference. This type of activity gives students freedom to “think outside the box” and search for ways to answer biological questions that interest them. With this activity, we detected—observed some students who were highlighted for their commitment to develop a project as a principal investigator. In addition, we reserved a time within the course for some students who had the IRPs selected to present for everybody. This type of activity adds other soft skills to students, such as communication and accepting challenges, which are essential for future scientists.

Although we have achieved good results as an online course model for higher education, we have encountered some limitations in our study. The course was presented in a short‐time (3 consecutive days) which hampered a robust evaluation regarding the impact of active tools in student progress. In addition, the experimental course was transmitted simultaneously with other activities of the hosted congress, which may have impacted on students' outcomes due to other demanding activities. In addition, because it is an optional course (as a satellite event), there were no ways to require student participation, nor condition performance to the approval of the course. This could have been caused, among other possible reasons, by the low responsiveness in certain activities, showing that part of the students only engages in activities when they are required for approval. Previous experiences with the theme were not considered as a differential advantage, students from different fields in health and biological sciences were analyzed together; the same happened to undergraduate students and postdoctoral fellows, for example. Finally, a point that can be seen in a positive and negative way was the heterogeneity of the class. This was interesting because it brought the most different backgrounds to the same class, however, it also made it difficult to know about the level of knowledge among students, since the same knowledge could be very basic or essential for some and very advanced or specific for others.

Interestingly, although our study was carried out during a pandemic, with a limited number of students, our data reflect the profile of Brazilian education. The students admit that most of their academic training was with passive approaches, but they are interested and willing to more interactive activities. This exposes a gap in the unequal Brazilian educational model: changes in the educational environment are strongly necessary to prepare citizens socially and personally able to participate in society in a democratic way. 55 , 56 , 57 The current model of higher education in force in Europe after the establishment of the parameters determined by the European Higher Education Area prioritizes among the student's abilities the development of an autonomous learning capacity. 58 , 59 However, the models found in traditional schools, including Brazil, prepare students equally, minimizing the idea that knowledge acquisition is motivated in cognitive, personal, and also social skills. 60

The introduction of active learning methodologies has been widely encouraged worldwide, but it requires a great effort from both teachers and students: educators need to review their lesson plans and add new tools and students need to be willing to engage in the construction of knowledge. 14 Unquestionably, the process requires dynamic instructors, with a flexible mind and willing to use the class to produce a transformation in the students to acquire knowledge through active methodologies. The course was carried out after 3 months in full lockdown. We have no elements to evaluate if the impact of our proposal could be different spending more time within the course. Certainly, with all the uncertainties of this moment in the world, our experience reaffirms the remote method of learning when using elements of critical thinking and active methodologies, with a real benefit of self‐confidence and empowerment of students to motivate themselves in their long and arduous road to be a scientist.

Above all, our experience showed that making the student the center of the class brings not only cognitive benefits (such as intellectual growth) but also in the psychosocial and personal spheres, giving students independence, improvement in their effective communication, and in their ability to accept challenges for self‐development. Our data show that active learning tools that require constant engagement benefits students and improve their critical thinking. This study also shows that if courses on various scientific topics were reformulated by adding active methodologies, it is likely that more students will obtain better intellectual baggage and positive positioning towards participation in science, forming/preparing more powerful thinkers.

CONFLICT OF INTEREST

No competing interest has been declared. All authors have seen and approved the manuscript. The manuscript has not been accepted or published elsewhere.

Supporting information

Appendix S1. Supporting Information.

ACKNOWLEDGMENTS

We are grateful for the invitation from the Graduate Program in Biosciences and Pathophysiology (State University of Maringá) through Prof. Gessilda de Alcantara Nogueira de Melo to participate in the VII International Meeting of Biosciences and physiopathology. This study received support from FIOCRUZ, UFPR, CNPq, CAPES, and Programa Básico de Parasitologia AUXPE 2041/2011 (CAPES) Brazil. Marcel Ivan Ramirez is currently a fellow from CNPq‐Brazil.

Rossi IV, de Lima JD, Sabatke B, Nunes MAF, Ramirez GE, Ramirez MI. Active learning tools improve the learning outcomes, scientific attitude, and critical thinking in higher education: Experiences in an online course during the COVID‐19 pandemic . Biochem Mol Biol Educ . 2021; 49 :888–903. 10.1002/bmb.21574 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Contributor Information

Izadora Volpato Rossi, Email: moc.liamg@otaplovarodazi .

Marcel Ivan Ramirez, Email: [email protected] .

Center for Educational Effectiveness

Active learning, creating an engaging & inclusive environment ( read full series ), what is it.

Active learning strategies are instructional activities that engage students in doing things as well as thinking about what they are doing (adapted from Bonwell and Eison, 1991). Active learning approaches support the student-centered, co-construction of knowledge, skills, and values (more than the transmission of information from the instructor to the students).

The National Survey of Student Engagement (NSSE) has followed the engagement experiences of thousands of college students since 2000. Their consistent results show that hands-on, integrative, and collaborative active learning experiences lead to high levels of student achievement and personal development (Kuh et al., 2017). Owens et al. (2017) found that active learning can positively impact student motivation. Reimer et al. (2016) found active learning to be particularly beneficial to first-generation college students in STEM courses, boosting both retention and passing rates.

In a meta-analysis involving high enrollment lectures findings show that active learning increases student performance on exams by an average of 6%, and decreased failure rates from 34% to 22% (Freeman et al., 2014).

Teaching Strategies

Break up lectures for time to process, discuss, or practice. In a Think/Write-Pair-Share activity, ask the class a question, and then give students a few minutes to think about or write down a response. Students then pair up and share their ideas.
Assess students’ understanding. In the Muddiest Point ask students (towards the end of class) to write a short note explaining which point from that day’s class is most unclear to them. This strategy helps to better assess student learning and helps students reflect on their learning process.
Implement reciprocal teaching activities. For a Gallery Walk, set up stations or displays throughout the room. Organize so students rotate through each station (individually or in groups), completing a task or responding to a specific prompt at each station.
Organize and structure for inquiry-based learning. Give student teams a Case Study describing a real world and/or field-related problem. Each team must then develop a solution to the problem, using course concepts, outside research, etc.

Integrate writing-to-learn activities. Free writes, for example, are short, ungraded, in-class exploratory writing activities meant to get students engaged in a course topic.

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A Case Study in Promoting Active Learning

To adopt active learning methods, Carson College eliminated large course sections and took steps to educate faculty in the latest pedagogies.
The school also designed learning spaces conducive to active learning and created more extracurricular content to keep students on campus longer.
Since these adjustments have been implemented, attendance is up and students are more engaged in the classroom.

While many higher education institutions recognize the value of active learning, some find it challenging to adapt existing lecture courses to a more interactive style. That’s particularly true at large state universities where budgets are constrained and some core courses have triple-digit enrollments in each section.

When schools want to convert to a more active learning style, some faculty will protest that such a delivery method is impossible when there are hundreds of students per section. Professors might lament that it’s impossible to get to know so many students, that there are too many papers to grade, that students don’t want to engage, or that active learning exercises create too much movement and chaos in the classroom. This type of resistance makes it challenging for schools to make the switch.

Another problem is that many instructors simply don’t know how to teach using active learning methods. In a recent article in The Chronicle of Higher Education, Beth McMurtrie lists a number of problems related to college-level teaching. First, teaching is rarely rewarded and sometimes not even valued. Second, the workforce is dominated by contingent faculty members. And third, few universities spend time and effort helping instructors become good teachers. Doctoral programs will require candidates to spend two to three years taking seminars on research theory and methods, but schools do not educate these candidates about active learning—or any other kind of teaching method.

At the Carson College of Business at Washington State University, we have heard all these concerns expressed. We believe they’re all well-founded. And yet, as we studied our assurance of learning data and held conversations with industry partners, we became convinced that we needed to change our teaching style to one of active learning. We knew it would be hard. We changed anyway.

A Series of Targeted Changes

We took six steps to make it possible to adopt a new teaching style:

We eliminated very large course sections. Although we previously had courses with hundreds of students per section, we have reduced the maximum enrollment of any business course to 70 students. This has allowed us to create more interactive and engaging learning environments.

We did not achieve this goal by cutting enrollments, reducing course offerings, or relying on more adjunct faculty. Instead, we hired more full-time faculty members, both teaching-track and tenure-track. These new hires also contribute to our research mission. While this change increased our faculty costs, we considered it a worthwhile investment.

As we studied our assurance of learning data and held conversations with industry partners, we became convinced that we needed to change our teaching style to one of active learning.

We made sure faculty were educated in active-learning pedagogies. Many of our faculty members were not familiar with the latest research and best practices on how to teach effectively using active learning. To address this issue, we created a new three-credit full-semester seminar that all doctoral students in the business school must take, ideally before they teach their first course. It fosters skills in areas such as active-learning pedagogies and backward course design , in which learning goals are set before the course is put together. We also offered new faculty from industry the opportunity to audit the seminar.

Moreover, we developed a series of modules about teaching—specifically about active learning. We put this onboarding resource online so new faculty could view it before arriving on campus at the beginning of the semester.

We created teaching-focused professional development activities for veteran faculty. Four activities have been particularly useful:

We offer a case-writing academy that guides faculty through each step of the case-writing process: recognizing a need for a case on a specific topic, setting effective learning goals, creating a story, preparing questions, creating a teaching plan, and ideally publishing the case and plan.
We run “lunch-and-learn” sessions featuring speakers from the faculty and staff of the college and the broader university. Presenters have covered topics such as running group projects, managing fairness, using simulations, and understanding challenges that first generation students face.
We encourage faculty to work with peers, observing each other teach and providing feedback. We think this informal peer mentoring is as important as the formal mentoring we had already been doing.
We provide course design support to faculty who teach virtual courses. We educate them in effective techniques for online asynchronous teaching, and we require them to design their courses months before classes begin.

We improved the way we evaluate teaching quality and effectiveness. To determine how well faculty are teaching and students are learning, we commissioned a task force to study how we could use data other than end-of-course surveys. For instance, we are modifying our annual review process so that faculty complete mini teaching portfolios that include annotated syllabi, statements of active learning methods they have employed, examples of exams and assignments, and reports of teaching observations.

We also are considering both direct and indirect measures from our assurance of learning process when we assess how students are achieving program learning goals. We are using all this data to improve our programs—as we did four years ago when we revised our core curriculum.

We expect improvements in our learning assessments and graduate placement rates. Faculty already are reporting that they have seen more student engagement and increasing levels of student attendance.

We created learning spaces conducive to active learning. The building that houses most of our classrooms was built in the middle of the 20th century and contains classrooms suitable only for lecturing. We are pursuing fundraising for a new building, but we cannot wait for it to be built before introducing new teaching methods. Therefore, we’ve found other existing classrooms on campus and refurnished them in styles that facilitate active learning. For instance, for classes that include case discussions, we are using rooms with parliamentary-style seating.

We created engaging extracurricular content. Too many students were just attending classes and leaving campus without participating in any additional activities that would enhance their learning experiences and improve their career readiness. To change this situation, we created a co-curricular program that all students are required to complete before they graduate, and we hired a small staff to run it.

The program offers hundreds of different activities each year, including workshops, guest lectures, competitions, internships, and study abroad programs. Students complete a portion of these activities to accrue “badges” for practicing certain skills such as networking or for taking advantage of opportunities such as high-impact learning experiences. Because these activities require only about 15 hours per year, students accept this additional requirement.

Sharing Our Story

To make these important adjustments and fulfill our educational mission, we did not simply rely on a meager state budget, but actively pursued funding. We’ve emphasized delivery of this program in our communications with alumni and supporters, and that has allowed us to raise philanthropic revenues. We’ve also generated resources based on strategic program design. For example, we closed our very small face-to-face MBA program and focused on building an outstanding online program that could be delivered at scale.

We implemented all these changes because we believe that active learning is the best way to prepare our students for their professional careers. We also believe that we owe our students an education worthy of the time and money they have sacrificed to attend our college.

While it is still too early to tell what long-term effects these changes will have, we do expect improvements in our end-of-program learning assessments and graduate placement rates. But in the short term, faculty at all levels already are reporting that they have seen more student engagement in the classroom. They’ve also noted increasing levels of student attendance—a typical jump is from 50 percent to 80 percent.

In her Chronicle article, McMurtrie calls for “Colleges that truly support good teaching … to … broadcast their successes more loudly.” That’s why we are sharing our story. We want other schools on state budgets to know that it is possible, if not entirely easy, to adopt active learning at a large scale. In fact, schools at any budgetary level can do the same.

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A Case Study in Promoting Active Learning
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USING THE CASE STUDY METHODOLOGY TO PROMOTE ACTIVE LEARNING

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TABLE OF CONTENTS

Instructor strategies to aid implementation of active learning: a systematic literature review

Introduction

Conceptual framework: instructor strategies to reduce resistance

Definitions

Study timeline, data collection, and sample selection

Coding procedure

Analysis procedure for coding strategies

Characteristics of the primary studies

Type of publication and research audience

Types of courses sampled

Research design, methods, and outcomes

Explanation strategies

Establish expectations

Explain the purpose

Facilitation strategies

Approach students

Encourage students

Planning strategies

Design appropriate activities

Create group policies

Align the course

Review student feedback

Summary of strategies

Characteristics of the active learning studies

Limitations and gaps within the final sample

Positive outcomes for using active learning

Strategies to aid implementation of active learning

Supporting instructors with actionable strategies

Creation of the planning category

Availability of data and materials

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Transforming Teaching Through Active Learning: Case Studies from the Social Sciences

Introduction

Overview of Some of the Literature

Active Learning in the Social Sciences- Some Successful Examples.

Conclusions

Blended Learning and Student-centered Active Learning Environment: a Case Study with STEM Undergraduate Students

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