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How To Write A Lab Report | Step-by-Step Guide & Examples

Published on May 20, 2021 by Pritha Bhandari . Revised on July 23, 2023.

A lab report conveys the aim, methods, results, and conclusions of a scientific experiment. The main purpose of a lab report is to demonstrate your understanding of the scientific method by performing and evaluating a hands-on lab experiment. This type of assignment is usually shorter than a research paper .

Lab reports are commonly used in science, technology, engineering, and mathematics (STEM) fields. This article focuses on how to structure and write a lab report.

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Table of contents

Structuring a lab report, introduction, other interesting articles, frequently asked questions about lab reports.

The sections of a lab report can vary between scientific fields and course requirements, but they usually contain the purpose, methods, and findings of a lab experiment .

Each section of a lab report has its own purpose.

• Title: expresses the topic of your study
• Abstract : summarizes your research aims, methods, results, and conclusions
• Introduction: establishes the context needed to understand the topic
• Method: describes the materials and procedures used in the experiment
• Results: reports all descriptive and inferential statistical analyses
• Discussion: interprets and evaluates results and identifies limitations
• Conclusion: sums up the main findings of your experiment
• References: list of all sources cited using a specific style (e.g. APA )
• Appendices : contains lengthy materials, procedures, tables or figures

Although most lab reports contain these sections, some sections can be omitted or combined with others. For example, some lab reports contain a brief section on research aims instead of an introduction, and a separate conclusion is not always required.

If you’re not sure, it’s best to check your lab report requirements with your instructor.

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Your title provides the first impression of your lab report – effective titles communicate the topic and/or the findings of your study in specific terms.

Create a title that directly conveys the main focus or purpose of your study. It doesn’t need to be creative or thought-provoking, but it should be informative.

• The effects of varying nitrogen levels on tomato plant height.
• Testing the universality of the McGurk effect.
• Comparing the viscosity of common liquids found in kitchens.

An abstract condenses a lab report into a brief overview of about 150–300 words. It should provide readers with a compact version of the research aims, the methods and materials used, the main results, and the final conclusion.

Think of it as a way of giving readers a preview of your full lab report. Write the abstract last, in the past tense, after you’ve drafted all the other sections of your report, so you’ll be able to succinctly summarize each section.

To write a lab report abstract, use these guiding questions:

• What is the wider context of your study?
• What research question were you trying to answer?
• How did you perform the experiment?
• What did your results show?
• How did you interpret your results?
• What is the importance of your findings?

Nitrogen is a necessary nutrient for high quality plants. Tomatoes, one of the most consumed fruits worldwide, rely on nitrogen for healthy leaves and stems to grow fruit. This experiment tested whether nitrogen levels affected tomato plant height in a controlled setting. It was expected that higher levels of nitrogen fertilizer would yield taller tomato plants.

Levels of nitrogen fertilizer were varied between three groups of tomato plants. The control group did not receive any nitrogen fertilizer, while one experimental group received low levels of nitrogen fertilizer, and a second experimental group received high levels of nitrogen fertilizer. All plants were grown from seeds, and heights were measured 50 days into the experiment.

The effects of nitrogen levels on plant height were tested between groups using an ANOVA. The plants with the highest level of nitrogen fertilizer were the tallest, while the plants with low levels of nitrogen exceeded the control group plants in height. In line with expectations and previous findings, the effects of nitrogen levels on plant height were statistically significant. This study strengthens the importance of nitrogen for tomato plants.

Your lab report introduction should set the scene for your experiment. One way to write your introduction is with a funnel (an inverted triangle) structure:

• Start with the broad, general research topic
• Narrow your topic down your specific study focus
• End with a clear research question

Begin by providing background information on your research topic and explaining why it’s important in a broad real-world or theoretical context. Describe relevant previous research on your topic and note how your study may confirm it or expand it, or fill a gap in the research field.

This lab experiment builds on previous research from Haque, Paul, and Sarker (2011), who demonstrated that tomato plant yield increased at higher levels of nitrogen. However, the present research focuses on plant height as a growth indicator and uses a lab-controlled setting instead.

Next, go into detail on the theoretical basis for your study and describe any directly relevant laws or equations that you’ll be using. State your main research aims and expectations by outlining your hypotheses .

Based on the importance of nitrogen for tomato plants, the primary hypothesis was that the plants with the high levels of nitrogen would grow the tallest. The secondary hypothesis was that plants with low levels of nitrogen would grow taller than plants with no nitrogen.

Your introduction doesn’t need to be long, but you may need to organize it into a few paragraphs or with subheadings such as “Research Context” or “Research Aims.”

A lab report Method section details the steps you took to gather and analyze data. Give enough detail so that others can follow or evaluate your procedures. Write this section in the past tense. If you need to include any long lists of procedural steps or materials, place them in the Appendices section but refer to them in the text here.

You should describe your experimental design, your subjects, materials, and specific procedures used for data collection and analysis.

Experimental design

Briefly note whether your experiment is a within-subjects  or between-subjects design, and describe how your sample units were assigned to conditions if relevant.

A between-subjects design with three groups of tomato plants was used. The control group did not receive any nitrogen fertilizer. The first experimental group received a low level of nitrogen fertilizer, while the second experimental group received a high level of nitrogen fertilizer.

Describe human subjects in terms of demographic characteristics, and animal or plant subjects in terms of genetic background. Note the total number of subjects as well as the number of subjects per condition or per group. You should also state how you recruited subjects for your study.

List the equipment or materials you used to gather data and state the model names for any specialized equipment.

List of materials

35 Tomato seeds

15 plant pots (15 cm tall)

Light lamps (50,000 lux)

Nitrogen fertilizer

Measuring tape

Describe your experimental settings and conditions in detail. You can provide labelled diagrams or images of the exact set-up necessary for experimental equipment. State how extraneous variables were controlled through restriction or by fixing them at a certain level (e.g., keeping the lab at room temperature).

Light levels were fixed throughout the experiment, and the plants were exposed to 12 hours of light a day. Temperature was restricted to between 23 and 25℃. The pH and carbon levels of the soil were also held constant throughout the experiment as these variables could influence plant height. The plants were grown in rooms free of insects or other pests, and they were spaced out adequately.

Your experimental procedure should describe the exact steps you took to gather data in chronological order. You’ll need to provide enough information so that someone else can replicate your procedure, but you should also be concise. Place detailed information in the appendices where appropriate.

In a lab experiment, you’ll often closely follow a lab manual to gather data. Some instructors will allow you to simply reference the manual and state whether you changed any steps based on practical considerations. Other instructors may want you to rewrite the lab manual procedures as complete sentences in coherent paragraphs, while noting any changes to the steps that you applied in practice.

If you’re performing extensive data analysis, be sure to state your planned analysis methods as well. This includes the types of tests you’ll perform and any programs or software you’ll use for calculations (if relevant).

First, tomato seeds were sown in wooden flats containing soil about 2 cm below the surface. Each seed was kept 3-5 cm apart. The flats were covered to keep the soil moist until germination. The seedlings were removed and transplanted to pots 8 days later, with a maximum of 2 plants to a pot. Each pot was watered once a day to keep the soil moist.

The nitrogen fertilizer treatment was applied to the plant pots 12 days after transplantation. The control group received no treatment, while the first experimental group received a low concentration, and the second experimental group received a high concentration. There were 5 pots in each group, and each plant pot was labelled to indicate the group the plants belonged to.

50 days after the start of the experiment, plant height was measured for all plants. A measuring tape was used to record the length of the plant from ground level to the top of the tallest leaf.

In your results section, you should report the results of any statistical analysis procedures that you undertook. You should clearly state how the results of statistical tests support or refute your initial hypotheses.

The main results to report include:

• any descriptive statistics
• statistical test results
• the significance of the test results
• estimates of standard error or confidence intervals

The mean heights of the plants in the control group, low nitrogen group, and high nitrogen groups were 20.3, 25.1, and 29.6 cm respectively. A one-way ANOVA was applied to calculate the effect of nitrogen fertilizer level on plant height. The results demonstrated statistically significant ( p = .03) height differences between groups.

Next, post-hoc tests were performed to assess the primary and secondary hypotheses. In support of the primary hypothesis, the high nitrogen group plants were significantly taller than the low nitrogen group and the control group plants. Similarly, the results supported the secondary hypothesis: the low nitrogen plants were taller than the control group plants.

These results can be reported in the text or in tables and figures. Use text for highlighting a few key results, but present large sets of numbers in tables, or show relationships between variables with graphs.

You should also include sample calculations in the Results section for complex experiments. For each sample calculation, provide a brief description of what it does and use clear symbols. Present your raw data in the Appendices section and refer to it to highlight any outliers or trends.

The Discussion section will help demonstrate your understanding of the experimental process and your critical thinking skills.

In this section, you can:

• Interpret your results
• Compare your findings with your expectations
• Identify any sources of experimental error
• Explain any unexpected results
• Suggest possible improvements for further studies

Interpreting your results involves clarifying how your results help you answer your main research question. Report whether your results support your hypotheses.

• Did you measure what you sought out to measure?
• Were your analysis procedures appropriate for this type of data?

Compare your findings with other research and explain any key differences in findings.

• Are your results in line with those from previous studies or your classmates’ results? Why or why not?

An effective Discussion section will also highlight the strengths and limitations of a study.

• Did you have high internal validity or reliability?
• How did you establish these aspects of your study?

When describing limitations, use specific examples. For example, if random error contributed substantially to the measurements in your study, state the particular sources of error (e.g., imprecise apparatus) and explain ways to improve them.

The results support the hypothesis that nitrogen levels affect plant height, with increasing levels producing taller plants. These statistically significant results are taken together with previous research to support the importance of nitrogen as a nutrient for tomato plant growth.

However, unlike previous studies, this study focused on plant height as an indicator of plant growth in the present experiment. Importantly, plant height may not always reflect plant health or fruit yield, so measuring other indicators would have strengthened the study findings.

Another limitation of the study is the plant height measurement technique, as the measuring tape was not suitable for plants with extreme curvature. Future studies may focus on measuring plant height in different ways.

The main strengths of this study were the controls for extraneous variables, such as pH and carbon levels of the soil. All other factors that could affect plant height were tightly controlled to isolate the effects of nitrogen levels, resulting in high internal validity for this study.

Your conclusion should be the final section of your lab report. Here, you’ll summarize the findings of your experiment, with a brief overview of the strengths and limitations, and implications of your study for further research.

Some lab reports may omit a Conclusion section because it overlaps with the Discussion section, but you should check with your instructor before doing so.

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A lab report conveys the aim, methods, results, and conclusions of a scientific experiment . Lab reports are commonly assigned in science, technology, engineering, and mathematics (STEM) fields.

The purpose of a lab report is to demonstrate your understanding of the scientific method with a hands-on lab experiment. Course instructors will often provide you with an experimental design and procedure. Your task is to write up how you actually performed the experiment and evaluate the outcome.

In contrast, a research paper requires you to independently develop an original argument. It involves more in-depth research and interpretation of sources and data.

A lab report is usually shorter than a research paper.

The sections of a lab report can vary between scientific fields and course requirements, but it usually contains the following:

• Abstract: summarizes your research aims, methods, results, and conclusions
• References: list of all sources cited using a specific style (e.g. APA)
• Appendices: contains lengthy materials, procedures, tables or figures

The results chapter or section simply and objectively reports what you found, without speculating on why you found these results. The discussion interprets the meaning of the results, puts them in context, and explains why they matter.

In qualitative research , results and discussion are sometimes combined. But in quantitative research , it’s considered important to separate the objective results from your interpretation of them.

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How to Write a Lab Report – with Example/Template

April 11, 2024

Perhaps you’re in the midst of your challenging AP chemistry class in high school, or perhaps college you’re enrolled in biology , chemistry , or physics at university. At some point, you will likely be asked to write a lab report. Sometimes, your teacher or professor will give you specific instructions for how to format and write your lab report, and if so, use that. In case you’re left to your own devices, here are some guidelines you might find useful. Continue reading for the main elements of a lab report, followed by a detailed description of the more writing-heavy parts (with a lab report example/lab report template). Lastly, we’ve included an outline that can help get you started.

What is a lab report?

A lab report is an overview of your experiment. Essentially, it explains what you did in the experiment and how it went. Most lab reports end up being 5-10 pages long (graphs or other images included), though the length depends on the experiment. Here are some brief explanations of the essential parts of a lab report:

Title : The title says, in the most straightforward way possible, what you did in the experiment. Often, the title looks something like, “Effects of ____ on _____.” Sometimes, a lab report also requires a title page, which includes your name (and the names of any lab partners), your instructor’s name, and the date of the experiment.

Abstract : This is a short description of key findings of the experiment so that a potential reader could get an idea of the experiment before even beginning.

Introduction : This is comprised of one or several paragraphs summarizing the purpose of the lab. The introduction usually includes the hypothesis, as well as some background information.

Lab Report Example (Continued)

Materials : Perhaps the simplest part of your lab report, this is where you list everything needed for the completion of your experiment.

Methods : This is where you describe your experimental procedure. The section provides necessary information for someone who would want to replicate your study. In paragraph form, write out your methods in chronological order, though avoid excessive detail.

Data : Here, you should document what happened in the experiment, step-by-step. This section often includes graphs and tables with data, as well as descriptions of patterns and trends. You do not need to interpret all of the data in this section, but you can describe trends or patterns, and state which findings are interesting and/or significant.

Discussion of results : This is the overview of your findings from the experiment, with an explanation of how they pertain to your hypothesis, as well as any anomalies or errors.

Conclusion : Your conclusion will sum up the results of your experiment, as well as their significance. Sometimes, conclusions also suggest future studies.

Sources : Often in APA style , you should list all texts that helped you with your experiment. Make sure to include course readings, outside sources, and other experiments that you may have used to design your own.

How to write the abstract

The abstract is the experiment stated “in a nutshell”: the procedure, results, and a few key words. The purpose of the academic abstract is to help a potential reader get an idea of the experiment so they can decide whether to read the full paper. So, make sure your abstract is as clear and direct as possible, and under 200 words (though word count varies).

When writing an abstract for a scientific lab report, we recommend covering the following points:

• Background : Why was this experiment conducted?
• Objectives : What problem is being addressed by this experiment?
• Methods : How was the study designed and conducted?
• Results : What results were found and what do they mean?
• Conclusion : Were the results expected? Is this problem better understood now than before? If so, how?

How to write the introduction

The introduction is another summary, of sorts, so it could be easy to confuse the introduction with the abstract. While the abstract tends to be around 200 words summarizing the entire study, the introduction can be longer if necessary, covering background information on the study, what you aim to accomplish, and your hypothesis. Unlike the abstract (or the conclusion), the introduction does not need to state the results of the experiment.

Here is a possible order with which you can organize your lab report introduction:

• Intro of the intro : Plainly state what your study is doing.
• Background : Provide a brief overview of the topic being studied. This could include key terms and definitions. This should not be an extensive literature review, but rather, a window into the most relevant topics a reader would need to understand in order to understand your research.
• Importance : Now, what are the gaps in existing research? Given the background you just provided, what questions do you still have that led you to conduct this experiment? Are you clarifying conflicting results? Are you undertaking a new area of research altogether?
• Prediction: The plants placed by the window will grow faster than plants placed in the dark corner.
• Hypothesis: Basil plants placed in direct sunlight for 2 hours per day grow at a higher rate than basil plants placed in direct sunlight for 30 minutes per day.
• How you test your hypothesis : This is an opportunity to briefly state how you go about your experiment, but this is not the time to get into specific details about your methods (save this for your results section). Keep this part down to one sentence, and voila! You have your introduction.

How to write a discussion section

Here, we’re skipping ahead to the next writing-heavy section, which will directly follow the numeric data of your experiment. The discussion includes any calculations and interpretations based on this data. In other words, it says, “Now that we have the data, why should we care?”  This section asks, how does this data sit in relation to the hypothesis? Does it prove your hypothesis or disprove it? The discussion is also a good place to mention any mistakes that were made during the experiment, and ways you would improve the experiment if you were to repeat it. Like the other written sections, it should be as concise as possible.

Here is a list of points to cover in your lab report discussion:

• Weaker statement: These findings prove that basil plants grow more quickly in the sunlight.
• Stronger statement: These findings support the hypothesis that basil plants placed in direct sunlight grow at a higher rate than basil plants given less direct sunlight.
• Factors influencing results : This is also an opportunity to mention any anomalies, errors, or inconsistencies in your data. Perhaps when you tested the first round of basil plants, the days were sunnier than the others. Perhaps one of the basil pots broke mid-experiment so it needed to be replanted, which affected your results. If you were to repeat the study, how would you change it so that the results were more consistent?
• Implications : How do your results contribute to existing research? Here, refer back to the gaps in research that you mentioned in your introduction. Do these results fill these gaps as you hoped?
• Questions for future research : Based on this, how might your results contribute to future research? What are the next steps, or the next experiments on this topic? Make sure this does not become too broad—keep it to the scope of this project.

How to write a lab report conclusion

This is your opportunity to briefly remind the reader of your findings and finish strong. Your conclusion should be especially concise (avoid going into detail on findings or introducing new information).

Here are elements to include as you write your conclusion, in about 1-2 sentences each:

• Restate your goals : What was the main question of your experiment? Refer back to your introduction—similar language is okay.
• Restate your methods : In a sentence or so, how did you go about your experiment?
• Key findings : Briefly summarize your main results, but avoid going into detail.
• Limitations : What about your experiment was less-than-ideal, and how could you improve upon the experiment in future studies?
• Significance and future research : Why is your research important? What are the logical next-steps for studying this topic?

Template for beginning your lab report

Here is a compiled outline from the bullet points in these sections above, with some examples based on the (overly-simplistic) basil growth experiment. Hopefully this will be useful as you begin your lab report.

1) Title (ex: Effects of Sunlight on Basil Plant Growth )

2) Abstract (approx. 200 words)

• Background ( This experiment looks at… )
• Objectives ( It aims to contribute to research on…)
• Methods ( It does so through a process of…. )
• Results (Findings supported the hypothesis that… )
• Conclusion (These results contribute to a wider understanding about…)

3) Introduction (approx. 1-2 paragraphs)

• Intro ( This experiment looks at… )
• Background ( Past studies on basil plant growth and sunlight have found…)
• Importance ( This experiment will contribute to these past studies by…)
• Hypothesis ( Basil plants placed in direct sunlight for 2 hours per day grow at a higher rate than basil plants placed in direct sunlight for 30 minutes per day.)
• How you will test your hypothesis ( This hypothesis will be tested by a process of…)

4) Materials (list form) (ex: pots, soil, seeds, tables/stands, water, light source )

5) Methods (approx. 1-2 paragraphs) (ex: 10 basil plants were measured throughout a span of…)

6) Data (brief description and figures) (ex: These charts demonstrate a pattern that the basil plants placed in direct sunlight…)

7) Discussion (approx. 2-3 paragraphs)

• Support or reject hypothesis ( These findings support the hypothesis that basil plants placed in direct sunlight grow at a higher rate than basil plants given less direct sunlight.)
• Factors that influenced your results ( Outside factors that could have altered the results include…)
• Implications ( These results contribute to current research on basil plant growth and sunlight because…)
• Questions for further research ( Next steps for this research could include…)
• Restate your goals ( In summary, the goal of this experiment was to measure…)
• Restate your methods ( This hypothesis was tested by…)
• Key findings ( The findings supported the hypothesis because…)
• Limitations ( Although, certain elements were overlooked, including…)
• Significance and future research ( This experiment presents possibilities of future research contributions, such as…)
• Sources (approx. 1 page, usually in APA style)

Final thoughts – Lab Report Example

Hopefully, these descriptions have helped as you write your next lab report. Remember that different instructors may have different preferences for structure and format, so make sure to double-check when you receive your assignment. All in all, make sure to keep your scientific lab report concise, focused, honest, and organized. Good luck!

For more reading on coursework success, check out the following articles:

• How to Write the AP Lang Argument Essay (With Example)
• How to Write the AP Lang Rhetorical Analysis Essay (With Example)
• 49 Most Interesting Biology Research Topics
• 50 Best Environmental Science Research Topics
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With a BA from Wesleyan University and an MFA from the University of Illinois at Urbana-Champaign, Sarah is a writer, educator, and artist. She served as a graduate instructor at the University of Illinois, a tutor at St Peter’s School in Philadelphia, and an academic writing tutor and thesis mentor at Wesleyan’s Writing Workshop.

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Scientific Reports

What this handout is about.

This handout provides a general guide to writing reports about scientific research you’ve performed. In addition to describing the conventional rules about the format and content of a lab report, we’ll also attempt to convey why these rules exist, so you’ll get a clearer, more dependable idea of how to approach this writing situation. Readers of this handout may also find our handout on writing in the sciences useful.

Background and pre-writing

Why do we write research reports.

You did an experiment or study for your science class, and now you have to write it up for your teacher to review. You feel that you understood the background sufficiently, designed and completed the study effectively, obtained useful data, and can use those data to draw conclusions about a scientific process or principle. But how exactly do you write all that? What is your teacher expecting to see?

To take some of the guesswork out of answering these questions, try to think beyond the classroom setting. In fact, you and your teacher are both part of a scientific community, and the people who participate in this community tend to share the same values. As long as you understand and respect these values, your writing will likely meet the expectations of your audience—including your teacher.

So why are you writing this research report? The practical answer is “Because the teacher assigned it,” but that’s classroom thinking. Generally speaking, people investigating some scientific hypothesis have a responsibility to the rest of the scientific world to report their findings, particularly if these findings add to or contradict previous ideas. The people reading such reports have two primary goals:

• They want to gather the information presented.
• They want to know that the findings are legitimate.

Your job as a writer, then, is to fulfill these two goals.

How do I do that?

Good question. Here is the basic format scientists have designed for research reports:

• Introduction

Methods and Materials

This format, sometimes called “IMRAD,” may take slightly different shapes depending on the discipline or audience; some ask you to include an abstract or separate section for the hypothesis, or call the Discussion section “Conclusions,” or change the order of the sections (some professional and academic journals require the Methods section to appear last). Overall, however, the IMRAD format was devised to represent a textual version of the scientific method.

The scientific method, you’ll probably recall, involves developing a hypothesis, testing it, and deciding whether your findings support the hypothesis. In essence, the format for a research report in the sciences mirrors the scientific method but fleshes out the process a little. Below, you’ll find a table that shows how each written section fits into the scientific method and what additional information it offers the reader.

Thinking of your research report as based on the scientific method, but elaborated in the ways described above, may help you to meet your audience’s expectations successfully. We’re going to proceed by explicitly connecting each section of the lab report to the scientific method, then explaining why and how you need to elaborate that section.

Although this handout takes each section in the order in which it should be presented in the final report, you may for practical reasons decide to compose sections in another order. For example, many writers find that composing their Methods and Results before the other sections helps to clarify their idea of the experiment or study as a whole. You might consider using each assignment to practice different approaches to drafting the report, to find the order that works best for you.

What should I do before drafting the lab report?

The best way to prepare to write the lab report is to make sure that you fully understand everything you need to about the experiment. Obviously, if you don’t quite know what went on during the lab, you’re going to find it difficult to explain the lab satisfactorily to someone else. To make sure you know enough to write the report, complete the following steps:

• What are we going to do in this lab? (That is, what’s the procedure?)
• Why are we going to do it that way?
• What are we hoping to learn from this experiment?
• Why would we benefit from this knowledge?
• Consult your lab supervisor as you perform the lab. If you don’t know how to answer one of the questions above, for example, your lab supervisor will probably be able to explain it to you (or, at least, help you figure it out).
• Plan the steps of the experiment carefully with your lab partners. The less you rush, the more likely it is that you’ll perform the experiment correctly and record your findings accurately. Also, take some time to think about the best way to organize the data before you have to start putting numbers down. If you can design a table to account for the data, that will tend to work much better than jotting results down hurriedly on a scrap piece of paper.
• Record the data carefully so you get them right. You won’t be able to trust your conclusions if you have the wrong data, and your readers will know you messed up if the other three people in your group have “97 degrees” and you have “87.”
• Consult with your lab partners about everything you do. Lab groups often make one of two mistakes: two people do all the work while two have a nice chat, or everybody works together until the group finishes gathering the raw data, then scrams outta there. Collaborate with your partners, even when the experiment is “over.” What trends did you observe? Was the hypothesis supported? Did you all get the same results? What kind of figure should you use to represent your findings? The whole group can work together to answer these questions.
• Consider your audience. You may believe that audience is a non-issue: it’s your lab TA, right? Well, yes—but again, think beyond the classroom. If you write with only your lab instructor in mind, you may omit material that is crucial to a complete understanding of your experiment, because you assume the instructor knows all that stuff already. As a result, you may receive a lower grade, since your TA won’t be sure that you understand all the principles at work. Try to write towards a student in the same course but a different lab section. That student will have a fair degree of scientific expertise but won’t know much about your experiment particularly. Alternatively, you could envision yourself five years from now, after the reading and lectures for this course have faded a bit. What would you remember, and what would you need explained more clearly (as a refresher)?

Once you’ve completed these steps as you perform the experiment, you’ll be in a good position to draft an effective lab report.

Introductions

How do i write a strong introduction.

For the purposes of this handout, we’ll consider the Introduction to contain four basic elements: the purpose, the scientific literature relevant to the subject, the hypothesis, and the reasons you believed your hypothesis viable. Let’s start by going through each element of the Introduction to clarify what it covers and why it’s important. Then we can formulate a logical organizational strategy for the section.

The inclusion of the purpose (sometimes called the objective) of the experiment often confuses writers. The biggest misconception is that the purpose is the same as the hypothesis. Not quite. We’ll get to hypotheses in a minute, but basically they provide some indication of what you expect the experiment to show. The purpose is broader, and deals more with what you expect to gain through the experiment. In a professional setting, the hypothesis might have something to do with how cells react to a certain kind of genetic manipulation, but the purpose of the experiment is to learn more about potential cancer treatments. Undergraduate reports don’t often have this wide-ranging a goal, but you should still try to maintain the distinction between your hypothesis and your purpose. In a solubility experiment, for example, your hypothesis might talk about the relationship between temperature and the rate of solubility, but the purpose is probably to learn more about some specific scientific principle underlying the process of solubility.

For starters, most people say that you should write out your working hypothesis before you perform the experiment or study. Many beginning science students neglect to do so and find themselves struggling to remember precisely which variables were involved in the process or in what way the researchers felt that they were related. Write your hypothesis down as you develop it—you’ll be glad you did.

As for the form a hypothesis should take, it’s best not to be too fancy or complicated; an inventive style isn’t nearly so important as clarity here. There’s nothing wrong with beginning your hypothesis with the phrase, “It was hypothesized that . . .” Be as specific as you can about the relationship between the different objects of your study. In other words, explain that when term A changes, term B changes in this particular way. Readers of scientific writing are rarely content with the idea that a relationship between two terms exists—they want to know what that relationship entails.

Not a hypothesis:

“It was hypothesized that there is a significant relationship between the temperature of a solvent and the rate at which a solute dissolves.”

Hypothesis:

“It was hypothesized that as the temperature of a solvent increases, the rate at which a solute will dissolve in that solvent increases.”

Put more technically, most hypotheses contain both an independent and a dependent variable. The independent variable is what you manipulate to test the reaction; the dependent variable is what changes as a result of your manipulation. In the example above, the independent variable is the temperature of the solvent, and the dependent variable is the rate of solubility. Be sure that your hypothesis includes both variables.

Justify your hypothesis

You need to do more than tell your readers what your hypothesis is; you also need to assure them that this hypothesis was reasonable, given the circumstances. In other words, use the Introduction to explain that you didn’t just pluck your hypothesis out of thin air. (If you did pluck it out of thin air, your problems with your report will probably extend beyond using the appropriate format.) If you posit that a particular relationship exists between the independent and the dependent variable, what led you to believe your “guess” might be supported by evidence?

Scientists often refer to this type of justification as “motivating” the hypothesis, in the sense that something propelled them to make that prediction. Often, motivation includes what we already know—or rather, what scientists generally accept as true (see “Background/previous research” below). But you can also motivate your hypothesis by relying on logic or on your own observations. If you’re trying to decide which solutes will dissolve more rapidly in a solvent at increased temperatures, you might remember that some solids are meant to dissolve in hot water (e.g., bouillon cubes) and some are used for a function precisely because they withstand higher temperatures (they make saucepans out of something). Or you can think about whether you’ve noticed sugar dissolving more rapidly in your glass of iced tea or in your cup of coffee. Even such basic, outside-the-lab observations can help you justify your hypothesis as reasonable.

Background/previous research

This part of the Introduction demonstrates to the reader your awareness of how you’re building on other scientists’ work. If you think of the scientific community as engaging in a series of conversations about various topics, then you’ll recognize that the relevant background material will alert the reader to which conversation you want to enter.

Generally speaking, authors writing journal articles use the background for slightly different purposes than do students completing assignments. Because readers of academic journals tend to be professionals in the field, authors explain the background in order to permit readers to evaluate the study’s pertinence for their own work. You, on the other hand, write toward a much narrower audience—your peers in the course or your lab instructor—and so you must demonstrate that you understand the context for the (presumably assigned) experiment or study you’ve completed. For example, if your professor has been talking about polarity during lectures, and you’re doing a solubility experiment, you might try to connect the polarity of a solid to its relative solubility in certain solvents. In any event, both professional researchers and undergraduates need to connect the background material overtly to their own work.

Organization of this section

Most of the time, writers begin by stating the purpose or objectives of their own work, which establishes for the reader’s benefit the “nature and scope of the problem investigated” (Day 1994). Once you have expressed your purpose, you should then find it easier to move from the general purpose, to relevant material on the subject, to your hypothesis. In abbreviated form, an Introduction section might look like this:

“The purpose of the experiment was to test conventional ideas about solubility in the laboratory [purpose] . . . According to Whitecoat and Labrat (1999), at higher temperatures the molecules of solvents move more quickly . . . We know from the class lecture that molecules moving at higher rates of speed collide with one another more often and thus break down more easily [background material/motivation] . . . Thus, it was hypothesized that as the temperature of a solvent increases, the rate at which a solute will dissolve in that solvent increases [hypothesis].”

Again—these are guidelines, not commandments. Some writers and readers prefer different structures for the Introduction. The one above merely illustrates a common approach to organizing material.

How do I write a strong Materials and Methods section?

As with any piece of writing, your Methods section will succeed only if it fulfills its readers’ expectations, so you need to be clear in your own mind about the purpose of this section. Let’s review the purpose as we described it above: in this section, you want to describe in detail how you tested the hypothesis you developed and also to clarify the rationale for your procedure. In science, it’s not sufficient merely to design and carry out an experiment. Ultimately, others must be able to verify your findings, so your experiment must be reproducible, to the extent that other researchers can follow the same procedure and obtain the same (or similar) results.

Here’s a real-world example of the importance of reproducibility. In 1989, physicists Stanley Pons and Martin Fleischman announced that they had discovered “cold fusion,” a way of producing excess heat and power without the nuclear radiation that accompanies “hot fusion.” Such a discovery could have great ramifications for the industrial production of energy, so these findings created a great deal of interest. When other scientists tried to duplicate the experiment, however, they didn’t achieve the same results, and as a result many wrote off the conclusions as unjustified (or worse, a hoax). To this day, the viability of cold fusion is debated within the scientific community, even though an increasing number of researchers believe it possible. So when you write your Methods section, keep in mind that you need to describe your experiment well enough to allow others to replicate it exactly.

With these goals in mind, let’s consider how to write an effective Methods section in terms of content, structure, and style.

Sometimes the hardest thing about writing this section isn’t what you should talk about, but what you shouldn’t talk about. Writers often want to include the results of their experiment, because they measured and recorded the results during the course of the experiment. But such data should be reserved for the Results section. In the Methods section, you can write that you recorded the results, or how you recorded the results (e.g., in a table), but you shouldn’t write what the results were—not yet. Here, you’re merely stating exactly how you went about testing your hypothesis. As you draft your Methods section, ask yourself the following questions:

• How much detail? Be precise in providing details, but stay relevant. Ask yourself, “Would it make any difference if this piece were a different size or made from a different material?” If not, you probably don’t need to get too specific. If so, you should give as many details as necessary to prevent this experiment from going awry if someone else tries to carry it out. Probably the most crucial detail is measurement; you should always quantify anything you can, such as time elapsed, temperature, mass, volume, etc.
• Rationale: Be sure that as you’re relating your actions during the experiment, you explain your rationale for the protocol you developed. If you capped a test tube immediately after adding a solute to a solvent, why did you do that? (That’s really two questions: why did you cap it, and why did you cap it immediately?) In a professional setting, writers provide their rationale as a way to explain their thinking to potential critics. On one hand, of course, that’s your motivation for talking about protocol, too. On the other hand, since in practical terms you’re also writing to your teacher (who’s seeking to evaluate how well you comprehend the principles of the experiment), explaining the rationale indicates that you understand the reasons for conducting the experiment in that way, and that you’re not just following orders. Critical thinking is crucial—robots don’t make good scientists.
• Control: Most experiments will include a control, which is a means of comparing experimental results. (Sometimes you’ll need to have more than one control, depending on the number of hypotheses you want to test.) The control is exactly the same as the other items you’re testing, except that you don’t manipulate the independent variable-the condition you’re altering to check the effect on the dependent variable. For example, if you’re testing solubility rates at increased temperatures, your control would be a solution that you didn’t heat at all; that way, you’ll see how quickly the solute dissolves “naturally” (i.e., without manipulation), and you’ll have a point of reference against which to compare the solutions you did heat.

Describe the control in the Methods section. Two things are especially important in writing about the control: identify the control as a control, and explain what you’re controlling for. Here is an example:

“As a control for the temperature change, we placed the same amount of solute in the same amount of solvent, and let the solution stand for five minutes without heating it.”

Structure and style

Organization is especially important in the Methods section of a lab report because readers must understand your experimental procedure completely. Many writers are surprised by the difficulty of conveying what they did during the experiment, since after all they’re only reporting an event, but it’s often tricky to present this information in a coherent way. There’s a fairly standard structure you can use to guide you, and following the conventions for style can help clarify your points.

• Subsections: Occasionally, researchers use subsections to report their procedure when the following circumstances apply: 1) if they’ve used a great many materials; 2) if the procedure is unusually complicated; 3) if they’ve developed a procedure that won’t be familiar to many of their readers. Because these conditions rarely apply to the experiments you’ll perform in class, most undergraduate lab reports won’t require you to use subsections. In fact, many guides to writing lab reports suggest that you try to limit your Methods section to a single paragraph.
• Narrative structure: Think of this section as telling a story about a group of people and the experiment they performed. Describe what you did in the order in which you did it. You may have heard the old joke centered on the line, “Disconnect the red wire, but only after disconnecting the green wire,” where the person reading the directions blows everything to kingdom come because the directions weren’t in order. We’re used to reading about events chronologically, and so your readers will generally understand what you did if you present that information in the same way. Also, since the Methods section does generally appear as a narrative (story), you want to avoid the “recipe” approach: “First, take a clean, dry 100 ml test tube from the rack. Next, add 50 ml of distilled water.” You should be reporting what did happen, not telling the reader how to perform the experiment: “50 ml of distilled water was poured into a clean, dry 100 ml test tube.” Hint: most of the time, the recipe approach comes from copying down the steps of the procedure from your lab manual, so you may want to draft the Methods section initially without consulting your manual. Later, of course, you can go back and fill in any part of the procedure you inadvertently overlooked.
• Past tense: Remember that you’re describing what happened, so you should use past tense to refer to everything you did during the experiment. Writers are often tempted to use the imperative (“Add 5 g of the solid to the solution”) because that’s how their lab manuals are worded; less frequently, they use present tense (“5 g of the solid are added to the solution”). Instead, remember that you’re talking about an event which happened at a particular time in the past, and which has already ended by the time you start writing, so simple past tense will be appropriate in this section (“5 g of the solid were added to the solution” or “We added 5 g of the solid to the solution”).
• Active: We heated the solution to 80°C. (The subject, “we,” performs the action, heating.)
• Passive: The solution was heated to 80°C. (The subject, “solution,” doesn’t do the heating–it is acted upon, not acting.)

Increasingly, especially in the social sciences, using first person and active voice is acceptable in scientific reports. Most readers find that this style of writing conveys information more clearly and concisely. This rhetorical choice thus brings two scientific values into conflict: objectivity versus clarity. Since the scientific community hasn’t reached a consensus about which style it prefers, you may want to ask your lab instructor.

How do I write a strong Results section?

Here’s a paradox for you. The Results section is often both the shortest (yay!) and most important (uh-oh!) part of your report. Your Materials and Methods section shows how you obtained the results, and your Discussion section explores the significance of the results, so clearly the Results section forms the backbone of the lab report. This section provides the most critical information about your experiment: the data that allow you to discuss how your hypothesis was or wasn’t supported. But it doesn’t provide anything else, which explains why this section is generally shorter than the others.

Before you write this section, look at all the data you collected to figure out what relates significantly to your hypothesis. You’ll want to highlight this material in your Results section. Resist the urge to include every bit of data you collected, since perhaps not all are relevant. Also, don’t try to draw conclusions about the results—save them for the Discussion section. In this section, you’re reporting facts. Nothing your readers can dispute should appear in the Results section.

Most Results sections feature three distinct parts: text, tables, and figures. Let’s consider each part one at a time.

This should be a short paragraph, generally just a few lines, that describes the results you obtained from your experiment. In a relatively simple experiment, one that doesn’t produce a lot of data for you to repeat, the text can represent the entire Results section. Don’t feel that you need to include lots of extraneous detail to compensate for a short (but effective) text; your readers appreciate discrimination more than your ability to recite facts. In a more complex experiment, you may want to use tables and/or figures to help guide your readers toward the most important information you gathered. In that event, you’ll need to refer to each table or figure directly, where appropriate:

“Table 1 lists the rates of solubility for each substance”

“Solubility increased as the temperature of the solution increased (see Figure 1).”

If you do use tables or figures, make sure that you don’t present the same material in both the text and the tables/figures, since in essence you’ll just repeat yourself, probably annoying your readers with the redundancy of your statements.

Feel free to describe trends that emerge as you examine the data. Although identifying trends requires some judgment on your part and so may not feel like factual reporting, no one can deny that these trends do exist, and so they properly belong in the Results section. Example:

“Heating the solution increased the rate of solubility of polar solids by 45% but had no effect on the rate of solubility in solutions containing non-polar solids.”

This point isn’t debatable—you’re just pointing out what the data show.

As in the Materials and Methods section, you want to refer to your data in the past tense, because the events you recorded have already occurred and have finished occurring. In the example above, note the use of “increased” and “had,” rather than “increases” and “has.” (You don’t know from your experiment that heating always increases the solubility of polar solids, but it did that time.)

You shouldn’t put information in the table that also appears in the text. You also shouldn’t use a table to present irrelevant data, just to show you did collect these data during the experiment. Tables are good for some purposes and situations, but not others, so whether and how you’ll use tables depends upon what you need them to accomplish.

Tables are useful ways to show variation in data, but not to present a great deal of unchanging measurements. If you’re dealing with a scientific phenomenon that occurs only within a certain range of temperatures, for example, you don’t need to use a table to show that the phenomenon didn’t occur at any of the other temperatures. How useful is this table?

As you can probably see, no solubility was observed until the trial temperature reached 50°C, a fact that the text part of the Results section could easily convey. The table could then be limited to what happened at 50°C and higher, thus better illustrating the differences in solubility rates when solubility did occur.

As a rule, try not to use a table to describe any experimental event you can cover in one sentence of text. Here’s an example of an unnecessary table from How to Write and Publish a Scientific Paper , by Robert A. Day:

As Day notes, all the information in this table can be summarized in one sentence: “S. griseus, S. coelicolor, S. everycolor, and S. rainbowenski grew under aerobic conditions, whereas S. nocolor and S. greenicus required anaerobic conditions.” Most readers won’t find the table clearer than that one sentence.

When you do have reason to tabulate material, pay attention to the clarity and readability of the format you use. Here are a few tips:

• Number your table. Then, when you refer to the table in the text, use that number to tell your readers which table they can review to clarify the material.
• Give your table a title. This title should be descriptive enough to communicate the contents of the table, but not so long that it becomes difficult to follow. The titles in the sample tables above are acceptable.
• Arrange your table so that readers read vertically, not horizontally. For the most part, this rule means that you should construct your table so that like elements read down, not across. Think about what you want your readers to compare, and put that information in the column (up and down) rather than in the row (across). Usually, the point of comparison will be the numerical data you collect, so especially make sure you have columns of numbers, not rows.Here’s an example of how drastically this decision affects the readability of your table (from A Short Guide to Writing about Chemistry , by Herbert Beall and John Trimbur). Look at this table, which presents the relevant data in horizontal rows:

It’s a little tough to see the trends that the author presumably wants to present in this table. Compare this table, in which the data appear vertically:

The second table shows how putting like elements in a vertical column makes for easier reading. In this case, the like elements are the measurements of length and height, over five trials–not, as in the first table, the length and height measurements for each trial.

• Make sure to include units of measurement in the tables. Readers might be able to guess that you measured something in millimeters, but don’t make them try.

• Don’t use vertical lines as part of the format for your table. This convention exists because journals prefer not to have to reproduce these lines because the tables then become more expensive to print. Even though it’s fairly unlikely that you’ll be sending your Biology 11 lab report to Science for publication, your readers still have this expectation. Consequently, if you use the table-drawing option in your word-processing software, choose the option that doesn’t rely on a “grid” format (which includes vertical lines).

How do I include figures in my report?

Although tables can be useful ways of showing trends in the results you obtained, figures (i.e., illustrations) can do an even better job of emphasizing such trends. Lab report writers often use graphic representations of the data they collected to provide their readers with a literal picture of how the experiment went.

When should you use a figure?

Remember the circumstances under which you don’t need a table: when you don’t have a great deal of data or when the data you have don’t vary a lot. Under the same conditions, you would probably forgo the figure as well, since the figure would be unlikely to provide your readers with an additional perspective. Scientists really don’t like their time wasted, so they tend not to respond favorably to redundancy.

If you’re trying to decide between using a table and creating a figure to present your material, consider the following a rule of thumb. The strength of a table lies in its ability to supply large amounts of exact data, whereas the strength of a figure is its dramatic illustration of important trends within the experiment. If you feel that your readers won’t get the full impact of the results you obtained just by looking at the numbers, then a figure might be appropriate.

Of course, an undergraduate class may expect you to create a figure for your lab experiment, if only to make sure that you can do so effectively. If this is the case, then don’t worry about whether to use figures or not—concentrate instead on how best to accomplish your task.

Figures can include maps, photographs, pen-and-ink drawings, flow charts, bar graphs, and section graphs (“pie charts”). But the most common figure by far, especially for undergraduates, is the line graph, so we’ll focus on that type in this handout.

At the undergraduate level, you can often draw and label your graphs by hand, provided that the result is clear, legible, and drawn to scale. Computer technology has, however, made creating line graphs a lot easier. Most word-processing software has a number of functions for transferring data into graph form; many scientists have found Microsoft Excel, for example, a helpful tool in graphing results. If you plan on pursuing a career in the sciences, it may be well worth your while to learn to use a similar program.

Computers can’t, however, decide for you how your graph really works; you have to know how to design your graph to meet your readers’ expectations. Here are some of these expectations:

• Keep it as simple as possible. You may be tempted to signal the complexity of the information you gathered by trying to design a graph that accounts for that complexity. But remember the purpose of your graph: to dramatize your results in a manner that’s easy to see and grasp. Try not to make the reader stare at the graph for a half hour to find the important line among the mass of other lines. For maximum effectiveness, limit yourself to three to five lines per graph; if you have more data to demonstrate, use a set of graphs to account for it, rather than trying to cram it all into a single figure.
• Plot the independent variable on the horizontal (x) axis and the dependent variable on the vertical (y) axis. Remember that the independent variable is the condition that you manipulated during the experiment and the dependent variable is the condition that you measured to see if it changed along with the independent variable. Placing the variables along their respective axes is mostly just a convention, but since your readers are accustomed to viewing graphs in this way, you’re better off not challenging the convention in your report.
• Label each axis carefully, and be especially careful to include units of measure. You need to make sure that your readers understand perfectly well what your graph indicates.
• Number and title your graphs. As with tables, the title of the graph should be informative but concise, and you should refer to your graph by number in the text (e.g., “Figure 1 shows the increase in the solubility rate as a function of temperature”).
• Many editors of professional scientific journals prefer that writers distinguish the lines in their graphs by attaching a symbol to them, usually a geometric shape (triangle, square, etc.), and using that symbol throughout the curve of the line. Generally, readers have a hard time distinguishing dotted lines from dot-dash lines from straight lines, so you should consider staying away from this system. Editors don’t usually like different-colored lines within a graph because colors are difficult and expensive to reproduce; colors may, however, be great for your purposes, as long as you’re not planning to submit your paper to Nature. Use your discretion—try to employ whichever technique dramatizes the results most effectively.
• Try to gather data at regular intervals, so the plot points on your graph aren’t too far apart. You can’t be sure of the arc you should draw between the plot points if the points are located at the far corners of the graph; over a fifteen-minute interval, perhaps the change occurred in the first or last thirty seconds of that period (in which case your straight-line connection between the points is misleading).
• If you’re worried that you didn’t collect data at sufficiently regular intervals during your experiment, go ahead and connect the points with a straight line, but you may want to examine this problem as part of your Discussion section.
• Make your graph large enough so that everything is legible and clearly demarcated, but not so large that it either overwhelms the rest of the Results section or provides a far greater range than you need to illustrate your point. If, for example, the seedlings of your plant grew only 15 mm during the trial, you don’t need to construct a graph that accounts for 100 mm of growth. The lines in your graph should more or less fill the space created by the axes; if you see that your data is confined to the lower left portion of the graph, you should probably re-adjust your scale.
• If you create a set of graphs, make them the same size and format, including all the verbal and visual codes (captions, symbols, scale, etc.). You want to be as consistent as possible in your illustrations, so that your readers can easily make the comparisons you’re trying to get them to see.

How do I write a strong Discussion section?

The discussion section is probably the least formalized part of the report, in that you can’t really apply the same structure to every type of experiment. In simple terms, here you tell your readers what to make of the Results you obtained. If you have done the Results part well, your readers should already recognize the trends in the data and have a fairly clear idea of whether your hypothesis was supported. Because the Results can seem so self-explanatory, many students find it difficult to know what material to add in this last section.

Basically, the Discussion contains several parts, in no particular order, but roughly moving from specific (i.e., related to your experiment only) to general (how your findings fit in the larger scientific community). In this section, you will, as a rule, need to:

Explain whether the data support your hypothesis

• Acknowledge any anomalous data or deviations from what you expected

Derive conclusions, based on your findings, about the process you’re studying

• Relate your findings to earlier work in the same area (if you can)

Explore the theoretical and/or practical implications of your findings

Let’s look at some dos and don’ts for each of these objectives.

This statement is usually a good way to begin the Discussion, since you can’t effectively speak about the larger scientific value of your study until you’ve figured out the particulars of this experiment. You might begin this part of the Discussion by explicitly stating the relationships or correlations your data indicate between the independent and dependent variables. Then you can show more clearly why you believe your hypothesis was or was not supported. For example, if you tested solubility at various temperatures, you could start this section by noting that the rates of solubility increased as the temperature increased. If your initial hypothesis surmised that temperature change would not affect solubility, you would then say something like,

“The hypothesis that temperature change would not affect solubility was not supported by the data.”

Note: Students tend to view labs as practical tests of undeniable scientific truths. As a result, you may want to say that the hypothesis was “proved” or “disproved” or that it was “correct” or “incorrect.” These terms, however, reflect a degree of certainty that you as a scientist aren’t supposed to have. Remember, you’re testing a theory with a procedure that lasts only a few hours and relies on only a few trials, which severely compromises your ability to be sure about the “truth” you see. Words like “supported,” “indicated,” and “suggested” are more acceptable ways to evaluate your hypothesis.

Also, recognize that saying whether the data supported your hypothesis or not involves making a claim to be defended. As such, you need to show the readers that this claim is warranted by the evidence. Make sure that you’re very explicit about the relationship between the evidence and the conclusions you draw from it. This process is difficult for many writers because we don’t often justify conclusions in our regular lives. For example, you might nudge your friend at a party and whisper, “That guy’s drunk,” and once your friend lays eyes on the person in question, she might readily agree. In a scientific paper, by contrast, you would need to defend your claim more thoroughly by pointing to data such as slurred words, unsteady gait, and the lampshade-as-hat. In addition to pointing out these details, you would also need to show how (according to previous studies) these signs are consistent with inebriation, especially if they occur in conjunction with one another. To put it another way, tell your readers exactly how you got from point A (was the hypothesis supported?) to point B (yes/no).

Acknowledge any anomalous data, or deviations from what you expected

You need to take these exceptions and divergences into account, so that you qualify your conclusions sufficiently. For obvious reasons, your readers will doubt your authority if you (deliberately or inadvertently) overlook a key piece of data that doesn’t square with your perspective on what occurred. In a more philosophical sense, once you’ve ignored evidence that contradicts your claims, you’ve departed from the scientific method. The urge to “tidy up” the experiment is often strong, but if you give in to it you’re no longer performing good science.

Sometimes after you’ve performed a study or experiment, you realize that some part of the methods you used to test your hypothesis was flawed. In that case, it’s OK to suggest that if you had the chance to conduct your test again, you might change the design in this or that specific way in order to avoid such and such a problem. The key to making this approach work, though, is to be very precise about the weakness in your experiment, why and how you think that weakness might have affected your data, and how you would alter your protocol to eliminate—or limit the effects of—that weakness. Often, inexperienced researchers and writers feel the need to account for “wrong” data (remember, there’s no such animal), and so they speculate wildly about what might have screwed things up. These speculations include such factors as the unusually hot temperature in the room, or the possibility that their lab partners read the meters wrong, or the potentially defective equipment. These explanations are what scientists call “cop-outs,” or “lame”; don’t indicate that the experiment had a weakness unless you’re fairly certain that a) it really occurred and b) you can explain reasonably well how that weakness affected your results.

If, for example, your hypothesis dealt with the changes in solubility at different temperatures, then try to figure out what you can rationally say about the process of solubility more generally. If you’re doing an undergraduate lab, chances are that the lab will connect in some way to the material you’ve been covering either in lecture or in your reading, so you might choose to return to these resources as a way to help you think clearly about the process as a whole.

This part of the Discussion section is another place where you need to make sure that you’re not overreaching. Again, nothing you’ve found in one study would remotely allow you to claim that you now “know” something, or that something isn’t “true,” or that your experiment “confirmed” some principle or other. Hesitate before you go out on a limb—it’s dangerous! Use less absolutely conclusive language, including such words as “suggest,” “indicate,” “correspond,” “possibly,” “challenge,” etc.

Relate your findings to previous work in the field (if possible)

We’ve been talking about how to show that you belong in a particular community (such as biologists or anthropologists) by writing within conventions that they recognize and accept. Another is to try to identify a conversation going on among members of that community, and use your work to contribute to that conversation. In a larger philosophical sense, scientists can’t fully understand the value of their research unless they have some sense of the context that provoked and nourished it. That is, you have to recognize what’s new about your project (potentially, anyway) and how it benefits the wider body of scientific knowledge. On a more pragmatic level, especially for undergraduates, connecting your lab work to previous research will demonstrate to the TA that you see the big picture. You have an opportunity, in the Discussion section, to distinguish yourself from the students in your class who aren’t thinking beyond the barest facts of the study. Capitalize on this opportunity by putting your own work in context.

If you’re just beginning to work in the natural sciences (as a first-year biology or chemistry student, say), most likely the work you’ll be doing has already been performed and re-performed to a satisfactory degree. Hence, you could probably point to a similar experiment or study and compare/contrast your results and conclusions. More advanced work may deal with an issue that is somewhat less “resolved,” and so previous research may take the form of an ongoing debate, and you can use your own work to weigh in on that debate. If, for example, researchers are hotly disputing the value of herbal remedies for the common cold, and the results of your study suggest that Echinacea diminishes the symptoms but not the actual presence of the cold, then you might want to take some time in the Discussion section to recapitulate the specifics of the dispute as it relates to Echinacea as an herbal remedy. (Consider that you have probably already written in the Introduction about this debate as background research.)

This information is often the best way to end your Discussion (and, for all intents and purposes, the report). In argumentative writing generally, you want to use your closing words to convey the main point of your writing. This main point can be primarily theoretical (“Now that you understand this information, you’re in a better position to understand this larger issue”) or primarily practical (“You can use this information to take such and such an action”). In either case, the concluding statements help the reader to comprehend the significance of your project and your decision to write about it.

Since a lab report is argumentative—after all, you’re investigating a claim, and judging the legitimacy of that claim by generating and collecting evidence—it’s often a good idea to end your report with the same technique for establishing your main point. If you want to go the theoretical route, you might talk about the consequences your study has for the field or phenomenon you’re investigating. To return to the examples regarding solubility, you could end by reflecting on what your work on solubility as a function of temperature tells us (potentially) about solubility in general. (Some folks consider this type of exploration “pure” as opposed to “applied” science, although these labels can be problematic.) If you want to go the practical route, you could end by speculating about the medical, institutional, or commercial implications of your findings—in other words, answer the question, “What can this study help people to do?” In either case, you’re going to make your readers’ experience more satisfying, by helping them see why they spent their time learning what you had to teach them.

Works consulted

We consulted these works while writing this handout. This is not a comprehensive list of resources on the handout’s topic, and we encourage you to do your own research to find additional publications. Please do not use this list as a model for the format of your own reference list, as it may not match the citation style you are using. For guidance on formatting citations, please see the UNC Libraries citation tutorial . We revise these tips periodically and welcome feedback.

American Psychological Association. 2010. Publication Manual of the American Psychological Association . 6th ed. Washington, DC: American Psychological Association.

Beall, Herbert, and John Trimbur. 2001. A Short Guide to Writing About Chemistry , 2nd ed. New York: Longman.

Blum, Deborah, and Mary Knudson. 1997. A Field Guide for Science Writers: The Official Guide of the National Association of Science Writers . New York: Oxford University Press.

Booth, Wayne C., Gregory G. Colomb, Joseph M. Williams, Joseph Bizup, and William T. FitzGerald. 2016. The Craft of Research , 4th ed. Chicago: University of Chicago Press.

Briscoe, Mary Helen. 1996. Preparing Scientific Illustrations: A Guide to Better Posters, Presentations, and Publications , 2nd ed. New York: Springer-Verlag.

Council of Science Editors. 2014. Scientific Style and Format: The CSE Manual for Authors, Editors, and Publishers , 8th ed. Chicago & London: University of Chicago Press.

Davis, Martha. 2012. Scientific Papers and Presentations , 3rd ed. London: Academic Press.

Day, Robert A. 1994. How to Write and Publish a Scientific Paper , 4th ed. Phoenix: Oryx Press.

Porush, David. 1995. A Short Guide to Writing About Science . New York: Longman.

Williams, Joseph, and Joseph Bizup. 2017. Style: Lessons in Clarity and Grace , 12th ed. Boston: Pearson.

You may reproduce it for non-commercial use if you use the entire handout and attribute the source: The Writing Center, University of North Carolina at Chapel Hill

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How to Write a Lab Report

Lab Reports Describe Your Experiment

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Lab reports are an essential part of all laboratory courses and usually a significant part of your grade. If your instructor gives you an outline for how to write a lab report, use that. Some instructors require a lab report to be included in a lab notebook , while others will request a separate report. Here's how to write a lab report you can use if you aren't sure what to write or need an explanation of what to include in the different parts of the report.

A lab report is how you explain what you did in ​your experiment, what you learned, and what the results meant.

Lab Report Essentials

Not all lab reports have title pages, but if your instructor wants one, it would be a single page that states:​

• The title of the experiment.
• Your name and the names of any lab partners.
• Your instructor's name.
• The date the experiment was performed or the date the report was submitted.

The title says what you did. It should be brief (aim for ten words or less) and describe the main point of the experiment or investigation. An example of a title would be: "Effects of Ultraviolet Light on Borax Crystal Growth Rate". If you can, begin your title using a keyword rather than an article like "The" or "A".

Introduction or Purpose

Usually, the introduction is one paragraph that explains the objectives or purpose of the lab. In one sentence, state the hypothesis. Sometimes an introduction may contain background information, briefly summarize how the experiment was performed, state the findings of the experiment, and list the conclusions of the investigation. Even if you don't write a whole introduction, you need to state the purpose of the experiment, or why you did it. This would be where you state your hypothesis .

List everything needed to complete your experiment.

Describe the steps you completed during your investigation. This is your procedure. Be sufficiently detailed so that anyone can read this section and duplicate your experiment. Write it as if you were giving directions for someone else to do the lab. It may be helpful to provide a figure to diagram your experimental setup.

Numerical data obtained from your procedure usually presented as a table. Data encompasses what you recorded when you conducted the experiment. It's just the facts, not any interpretation of what they mean.

Describe in words what the data means. Sometimes the Results section is combined with the Discussion.

Discussion or Analysis

The Data section contains numbers; the Analysis section contains any calculations you made based on those numbers. This is where you interpret the data and determine whether or not a hypothesis was accepted. This is also where you would discuss any mistakes you might have made while conducting the investigation. You may wish to describe ways the study might have been improved.

Conclusions

Most of the time the conclusion is a single paragraph that sums up what happened in the experiment, whether your hypothesis was accepted or rejected, and what this means.

Figures and Graphs

Graphs and figures must both be labeled with a descriptive title. Label the axes on a graph, being sure to include units of measurement. The independent variable is on the X-axis, and the dependent variable (the one you are measuring) is on the Y-axis. Be sure to refer to figures and graphs in the text of your report: the first figure is Figure 1, the second figure is Figure 2, etc.

If your research was based on someone else's work or if you cited facts that require documentation, then you should list these references.

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Lab Report Format: Step-by-Step Guide & Examples

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

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

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

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

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

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In psychology, a lab report outlines a study’s objectives, methods, results, discussion, and conclusions, ensuring clarity and adherence to APA (or relevant) formatting guidelines.

A typical lab report would include the following sections: title, abstract, introduction, method, results, and discussion.

The title page, abstract, references, and appendices are started on separate pages (subsections from the main body of the report are not). Use double-line spacing of text, font size 12, and include page numbers.

The report should have a thread of arguments linking the prediction in the introduction to the content of the discussion.

This must indicate what the study is about. It must include the variables under investigation. It should not be written as a question.

Title pages should be formatted in APA style .

The abstract provides a concise and comprehensive summary of a research report. Your style should be brief but not use note form. Look at examples in journal articles . It should aim to explain very briefly (about 150 words) the following:

• Start with a one/two sentence summary, providing the aim and rationale for the study.
• Describe participants and setting: who, when, where, how many, and what groups?
• Describe the method: what design, what experimental treatment, what questionnaires, surveys, or tests were used.
• Describe the major findings, including a mention of the statistics used and the significance levels, or simply one sentence summing up the outcome.
• The final sentence(s) outline the study’s “contribution to knowledge” within the literature. What does it all mean? Mention the implications of your findings if appropriate.

The abstract comes at the beginning of your report but is written at the end (as it summarises information from all the other sections of the report).

Introduction

The purpose of the introduction is to explain where your hypothesis comes from (i.e., it should provide a rationale for your research study).

Ideally, the introduction should have a funnel structure: Start broad and then become more specific. The aims should not appear out of thin air; the preceding review of psychological literature should lead logically into the aims and hypotheses.

• Start with general theory, briefly introducing the topic. Define the important key terms.
• Explain the theoretical framework.
• Summarise and synthesize previous studies – What was the purpose? Who were the participants? What did they do? What did they find? What do these results mean? How do the results relate to the theoretical framework?
• Rationale: How does the current study address a gap in the literature? Perhaps it overcomes a limitation of previous research.
• Aims and hypothesis. Write a paragraph explaining what you plan to investigate and make a clear and concise prediction regarding the results you expect to find.

There should be a logical progression of ideas that aids the flow of the report. This means the studies outlined should lead logically to your aims and hypotheses.

Do be concise and selective, and avoid the temptation to include anything in case it is relevant (i.e., don’t write a shopping list of studies).

USE THE FOLLOWING SUBHEADINGS:

Participants

• How many participants were recruited?
• Say how you obtained your sample (e.g., opportunity sample).
• Give relevant demographic details (e.g., gender, ethnicity, age range, mean age, and standard deviation).
• State the experimental design .
• What were the independent and dependent variables ? Make sure the independent variable is labeled and name the different conditions/levels.
• For example, if gender is the independent variable label, then male and female are the levels/conditions/groups.
• How were the IV and DV operationalized?
• Identify any controls used, e.g., counterbalancing and control of extraneous variables.
• List all the materials and measures (e.g., what was the title of the questionnaire? Was it adapted from a study?).
• You do not need to include wholesale replication of materials – instead, include a ‘sensible’ (illustrate) level of detail. For example, give examples of questionnaire items.
• Include the reliability (e.g., alpha values) for the measure(s).
• Describe the precise procedure you followed when conducting your research, i.e., exactly what you did.
• Describe in sufficient detail to allow for replication of findings.
• Be concise in your description and omit extraneous/trivial details, e.g., you don’t need to include details regarding instructions, debrief, record sheets, etc.
• Assume the reader has no knowledge of what you did and ensure that he/she can replicate (i.e., copy) your study exactly by what you write in this section.
• Write in the past tense.
• Don’t justify or explain in the Method (e.g., why you chose a particular sampling method); just report what you did.
• Only give enough detail for someone to replicate the experiment – be concise in your writing.
• The results section of a paper usually presents descriptive statistics followed by inferential statistics.
• Report the means, standard deviations, and 95% confidence intervals (CIs) for each IV level. If you have four to 20 numbers to present, a well-presented table is best, APA style.
• Name the statistical test being used.
• Report appropriate statistics (e.g., t-scores, p values ).
• Report the magnitude (e.g., are the results significant or not?) as well as the direction of the results (e.g., which group performed better?).
• It is optional to report the effect size (this does not appear on the SPSS output).
• Avoid interpreting the results (save this for the discussion).
• Make sure the results are presented clearly and concisely. A table can be used to display descriptive statistics if this makes the data easier to understand.
• DO NOT include any raw data.
• Follow APA style.

Use APA Style

• Numbers reported to 2 d.p. (incl. 0 before the decimal if 1.00, e.g., “0.51”). The exceptions to this rule: Numbers which can never exceed 1.0 (e.g., p -values, r-values): report to 3 d.p. and do not include 0 before the decimal place, e.g., “.001”.
• Percentages and degrees of freedom: report as whole numbers.
• Statistical symbols that are not Greek letters should be italicized (e.g., M , SD , t , X 2 , F , p , d ).
• Include spaces on either side of the equals sign.
• When reporting 95%, CIs (confidence intervals), upper and lower limits are given inside square brackets, e.g., “95% CI [73.37, 102.23]”
• Outline your findings in plain English (avoid statistical jargon) and relate your results to your hypothesis, e.g., is it supported or rejected?
• Compare your results to background materials from the introduction section. Are your results similar or different? Discuss why/why not.
• How confident can we be in the results? Acknowledge limitations, but only if they can explain the result obtained. If the study has found a reliable effect, be very careful suggesting limitations as you are doubting your results. Unless you can think of any c onfounding variable that can explain the results instead of the IV, it would be advisable to leave the section out.
• Suggest constructive ways to improve your study if appropriate.
• What are the implications of your findings? Say what your findings mean for how people behave in the real world.
• Suggest an idea for further research triggered by your study, something in the same area but not simply an improved version of yours. Perhaps you could base this on a limitation of your study.
• Concluding paragraph – Finish with a statement of your findings and the key points of the discussion (e.g., interpretation and implications) in no more than 3 or 4 sentences.

Reference Page

The reference section lists all the sources cited in the essay (alphabetically). It is not a bibliography (a list of the books you used).

In simple terms, every time you refer to a psychologist’s name (and date), you need to reference the original source of information.

If you have been using textbooks this is easy as the references are usually at the back of the book and you can just copy them down. If you have been using websites then you may have a problem as they might not provide a reference section for you to copy.

References need to be set out APA style :

Author, A. A. (year). Title of work . Location: Publisher.

Journal Articles

Author, A. A., Author, B. B., & Author, C. C. (year). Article title. Journal Title, volume number (issue number), page numbers

A simple way to write your reference section is to use Google scholar . Just type the name and date of the psychologist in the search box and click on the “cite” link.

Next, copy and paste the APA reference into the reference section of your essay.

Once again, remember that references need to be in alphabetical order according to surname.

Psychology Lab Report Example

Quantitative paper template.

Quantitative professional paper template: Adapted from “Fake News, Fast and Slow: Deliberation Reduces Belief in False (but Not True) News Headlines,” by B. Bago, D. G. Rand, and G. Pennycook, 2020,  Journal of Experimental Psychology: General ,  149 (8), pp. 1608–1613 ( https://doi.org/10.1037/xge0000729 ). Copyright 2020 by the American Psychological Association.

Qualitative paper template

Qualitative professional paper template: Adapted from “‘My Smartphone Is an Extension of Myself’: A Holistic Qualitative Exploration of the Impact of Using a Smartphone,” by L. J. Harkin and D. Kuss, 2020,  Psychology of Popular Media ,  10 (1), pp. 28–38 ( https://doi.org/10.1037/ppm0000278 ). Copyright 2020 by the American Psychological Association.

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Lab Report Format – How to Write a Laboratory Report

A science laboratory experiment isn’t truly complete until you’ve written the lab report. You may have taken excellent notes in your laboratory notebook, but it isn’t the same as a lab report. The lab report format is designed to present experimental results so they can be shared with others. A well-written report explains what you did, why you did it, and what you learned. It should also generate reader interest, potentially leading to peer-reviewed publication and funding.

Sections of a Lab Report

There is no one lab report format. The format and sections might be specified by your instructor or employer. What really matters is covering all of the important information.

Label the sections (except the title). Use bold face type for the title and headings. The order is:

You may or may not be expected to provide a title page. If it is required, the title page includes the title of the experiment, the names of the researchers, the name of the institution, and the date.

The title describes the experiment. Don’t start it with an article (e.g., the, an, a) because it messes up databases and isn’t necessary. For example, a good title might be, “Effect of Increasing Glucose Concentration on Danio rerio Egg Hatching Rates.” Use title case and italicize the scientific names of any species.

Introduction

Sometimes the introduction is broken into separate sections. Otherwise, it’s written as a narrative that includes the following information:

• State the purpose of the experiment.
• State the hypothesis.
• Review earlier work on the subject. Refer to previous studies. Cover the background so a reader understands what is known about a subject and what you hope to learn that is new.
• Describe your approach to answering a question or solving a problem. Include a theory or equation, if appropriate.

This section describes experimental design. Identify the parameter you changed ( independent variable ) and the one you measured ( dependent variable ). Describe the equipment and set-up you used, materials, and methods. If a reader can’t picture the apparatus from your description, include a photograph or diagram. Sometimes this section is broken into “Materials” and “Methods.”

Your lab notebook contains all of the data you collected in the experiment. You aren’t expected to reproduce all of this in a lab report. Instead, provide labelled tables and graphs. The first figure is Figure 1, the second is Figure 2, etc. The first graph is Graph 1. Refer to figures and graphs by their figure number. For some experiments, you may need to include labelled photographs. Cite the results of any calculations you performed, such as slope and standard deviation. Discuss sources of error here, including instrument, standard, and random errors.

Discussion or Conclusions

While the “Results” section includes graphs and tables, the “Discussion” or “Conclusions” section focuses on what the results mean. This is where you state whether or not the objective of the experiment was met and what the outcome means.  Propose reasons for discrepancies between expected and actual outcomes. Finally, describe the next logical step in your research and ways you might improve on the experiment.

References or Bibliography

Did you build upon work conducted by someone else? Cite the work. Did you consult a paper relating to the experiment? Credit the author. If you’re unsure whether to cite a reference or not, a good rule of thumb is to include a reference for any fact not known to your audience. For some reports, it’s only necessary to list publications directly relating to your procedure and conclusions.

The Tone of a Lab Report

Lab reports should be informative, not entertaining. This isn’t the place for humor, sarcasm, or flowery prose. A lab report should be:

• Concise : Cover all the key points without getting crazy with the details.
• Objective : In the “Conclusions” section, you can propose possible explanations for your results. Otherwise, keep your opinions out of the report. Instead, present facts and an analysis based on logic and math.
• Critical : After presenting what you did, the report focuses on what the data means. Be on the lookout for sources of error and identify them. Use your understanding of error to determine how reliable your results are and gauge confidence in your conclusions.

Related Posts

Writing Studio

Writing a lab report: introduction and discussion section guide.

In an effort to make our handouts more accessible, we have begun converting our PDF handouts to web pages. Download this page as a PDF:   Writing a Lab Report Return to Writing Studio Handouts

Part 1 (of 2): Introducing a Lab Report

The introduction of a lab report states the objective of the experiment and provides the reader with background information. State the topic of your report clearly and concisely (in one or two sentences). Provide background theory, previous research, or formulas the reader should know. Usually, an instructor does not want you to repeat whatever the lab manual says, but to show your understanding of the problem.

Questions an Effective Lab Report Introduction Should Answer

What is the problem.

Describe the problem investigated. Summarize relevant research to provide context, key terms, and concepts so that your reader can understand the experiment.

Why is it important?

Review relevant research to provide a rationale for the investigation. What conflict, unanswered question, untested population, or untried method in existing research does your experiment address? How will you challenge or extend the findings of other researchers?

What solution (or step toward a solution) do you propose?

Briefly describe your experiment : hypothesis , research question , general experimental design or method , and a justification of your method (if alternatives exist).

Tips on Composing Your Lab Report’s Introduction

• Move from the general to the specific – from a problem in research literature to the specifics of your experiment.
• Engage your reader – answer the questions: “What did I do?” “Why should my reader care?”
• Clarify the links between problem and solution, between question asked and research design, and between prior research and the specifics of your experiment.
• Be selective, not exhaustive, in choosing studies to cite and the amount of detail to include. In general, the more relevant an article is to your study, the more space it deserves and the later in the introduction it appears.
• Ask your instructor whether or not you should summarize results and/or conclusions in the Introduction.
• “The objective of the experiment was …”
• “The purpose of this report is …”
• “Bragg’s Law for diffraction is …”
• “The scanning electron microscope produces micrographs …”

Part 2 (of 2): Writing the “Discussion” Section of a Lab Report

The discussion is the most important part of your lab report, because here you show that you have not merely completed the experiment, but that you also understand its wider implications. The discussion section is reserved for putting experimental results in the context of the larger theory. Ask yourself: “What is the significance or meaning of the results?”

Elements of an Effective Discussion Section

What do the results indicate clearly? Based on your results, explain what you know with certainty and draw conclusions.

Interpretation

What is the significance of your results? What ambiguities exist? What are logical explanations for problems in the data? What questions might you raise about the methods used or the validity of the experiment? What can be logically deduced from your analysis?

Tips on the Discussion Section

1. explain your results in terms of theoretical issues..

How well has the theory been illustrated? What are the theoretical implications and practical applications of your results?

For each major result:

• Describe the patterns, principles, and relationships that your results show.
• Explain how your results relate to expectations and to literature cited in your Introduction. Explain any agreements, contradictions, or exceptions.
• Describe what additional research might resolve contradictions or explain exceptions.

2. Relate results to your experimental objective(s).

If you set out to identify an unknown metal by finding its lattice parameter and its atomic structure, be sure that you have identified the metal and its attributes.

3. Compare expected results with those obtained.

If there were differences, how can you account for them? Were the instruments able to measure precisely? Was the sample contaminated? Did calculated values take account of friction?

4. Analyze experimental error along with the strengths and limitations of the experiment’s design.

Were any errors avoidable? Were they the result of equipment?  If the flaws resulted from the experiment design, explain how the design might be improved. Consider, as well, the precision of the instruments that were used.

5. Compare your results to similar investigations.

In some cases, it is legitimate to compare outcomes with classmates, not in order to change your answer, but in order to look for and to account for or analyze any anomalies between the groups. Also, consider comparing your results to published scientific literature on the topic.

The “Introducing a Lab Report” guide was adapted from the University of Toronto Engineering Communications Centre and University of Wisconsin-Madison Writing Center.

The “Writing the Discussion Section of a Lab Report” resource was adapted from the University of Toronto Engineering Communications Centre and University of Wisconsin-Madison Writing Center.

Last revised: 07/2008 | Adapted for web delivery: 02/2021

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A lab report documents the theory, methods, and results of your experiment to demonstrate your understanding of research and scientific methodology. In this article, we’ll tell you how to write a lab report with the help of some useful examples.

For many students, writing a lab report can be confusing: how to format it, what to include and not include, and so on. The questions are endless! Just remember that your lab report will allow others to reproduce your results and draw their own conclusions. This will help you write a lab report that’s well-formatted and organized.

In true Resource Center fashion, let’s start with the basics: What exactly is a lab report?

Need help creating a perfect lab report? Learn more

What is a lab report? 

A laboratory report is a document written to describe and analyze an experiment that addresses a scientific inquiry. A lab report helps you conduct an experiment and then systematically design a conclusion based on your hypothesis. 

Note: A lab report is not the same as a lab notebook. A notebook is a detailed log you keep throughout the study. A lab report is a concise summary that you submit after the study is done, usually for a final grade. 

A lab report typically follows this format:  

• Title 

Introduction 

• Equipment/Materials 
• Methods 
• Discussion 
• References 

This is a broad list of sections you might have to include in your lab report, but by no means is this compulsory or exhaustive. You should always refer to the course or university guidelines to understand the desired format. 

How to Write a Lab Report

A lab report should be clear, concise, and well-organized, and it should include all the necessary information for others to replicate your experiment. Since the lab report format is designed to serve this purpose, you must follow it to the bone while writing your report.

Let’s start with learning how to title a lab report.

Title  

The title of your lab report should:

• Be clear, direct, and informative.
• Include keywords that clarify your objectives and involved variables.
• Be under ten words (ideally).

It’s a good idea to avoid phrasing the title as a question. Remember, your title doesn’t have to be witty or clever, just descriptive and to the point. Here are a few title examples that can clarify this for you:

• Unraveling the genetic code through gel electrophoresis.
• Hot and cold: How temperature affects enzymes yeast cells
• Impervious alloys of Aluminium
• How fast does Hydrogen Peroxide decompose?
• The speed of growth: An Analysis of bacterial growth rates in different culture media

Analysis of DNA fragment lengths using gel electrophoresis

The effects of temperature on enzyme activity in yeast cells

Investigating the corrosion resistance of Aluminum alloys

Study of chemical kinetics through the decomposition of Hydrogen Peroxide

Quantifying bacterial growth rates in different culture media

While it’s not necessary to dedicate an entire page to the title, some universities might ask for a title page. If you’ve been asked to make this, include the following details:

• The experiment title 
• Your name and student details 
• Course and program details 
• Date and year of submission 

An abstract is a brief but comprehensive overview of the purpose, findings, and larger relevance of your experiment. It communicates the essential details of your study to your readers, whether it’s evaluators or peers.

Follow these tips to write a lab report abstract:

• Clearly state the topic of your experiment.
• Briefly describe the conditions of your study, the variables involved, and the method(s) used to collect data.
• Lay out the major findings of your study and your interpretations of them.
• Mention the relevance and importance of your study in brief.

An abstract is usually only a page long (typically between 100 and 250 words), so your writing must be concise and crisp.

Bonus tip: Although the abstract is the first section of your report, it’s best to write it toward the end. Much easier to summarize the report afte r it’s been written!

Lab report abstract example

This experiment aimed to investigate the corrosion resistance of two different aluminum alloys: 6061-T6 and 7075-T6. The experiment involved exposing samples of each alloy to a 3% NaCl solution for a period of 72 hours and then measuring the weight loss of the samples. The results showed that 6061-T6 had a weight loss of 0.10 g, while 7075-T6 had a weight loss of 0.25 g, indicating that 6061-T6 was more corrosion resistant. These findings suggest that the composition of the alloy has a significant impact on its resistance to corrosion. This information is important for industries that use aluminum alloys in environments that are prone to corrosion, such as marine applications or chemical processing. Further research could explore the specific mechanisms that contribute to the corrosion resistance of different aluminum alloys and could investigate the effects of other environmental factors on corrosion.

The lab report introduction provides your readers with background information on your experiment and its significance. It should be brief and to the point, so a few paragraphs is the maximum length recommended.

You can adopt either of two modes to write your introduction:

• Beginning with the research question and then adding context, ultimately closing with your purpose.
• Beginning with the broad topic and narrowing it down to your research question.

Follow these steps to write your lab report introduction:

• Begin with a brief overview of the broad research area and existing literature. 
• Include only essential background information and cite only highly relevant sources. 
• Clearly define any key terms or concepts that you’ll use in the report.
• State the specific purpose and objectives of your experiment.
• Mention the relevance and significance of your study.
• State a clear hypothesis and expected outcomes.
• Check with your instructor about adding the variables, results, and conclusions to the introduction.
• Refer to the university guidelines for instructions on labeling paragraphs in your introduction.
• Use the past tense when describing the purpose and other specifics of the experiment since it has already been carried out and is in the past. (“This experiment aimed to investigate the corrosion resistance of two different aluminum alloys.”)
• Use the present tense when describing the report, existing theories, and established facts. (“This information is important for industries that use aluminum alloys in environments prone to corrosion.”)

Make sure you use your own words rather than following a templatized format.

Lab report introduction example

Aluminum alloys are widely used in a variety of industrial applications due to their excellent strength-to-weight ratio, good corrosion resistance, and other desirable properties. However, the corrosion resistance of aluminum alloys can vary depending on their composition, and understanding the factors that contribute to corrosion resistance is crucial for their effective use in harsh environments. In this experiment, we aim to investigate the corrosion resistance of two different aluminum alloys: 6061-T6 and 7075-T6.

These alloys were selected because they are commonly used in industrial applications and have different compositions, with 6061-T6 containing magnesium and silicon, while 7075-T6 contains zinc and copper. By exposing samples of each alloy to a 3% NaCl solution and measuring the weight loss of the samples over time, we can determine which alloy is more corrosion-resistant and gain insight into the factors that contribute to their corrosion resistance. This information is important for industries that use aluminum alloys in harsh environments, such as marine and aerospace applications, and can contribute to the development of more effective corrosion-resistant materials.

The lab report methods section documents the methods, subjects, materials, and equipment you used to collect data. This is a record of the steps you followed and not the steps as they were prescribed.

Follow these tips to write a lab report method section:

• List all materials and equipment used in the experiment, including their material specifications such as weight or amount. (Ex: 5 ml of 3% NaCl solution)
• In the case of elaborate lists and sets of steps, you may include them in the appendix section and refer to them in the methods section. (Check this with your instructor!)
• Detail the procedures you used to carry out the experiment step-by-step, including apparatus setup, mixing of reagents, and other technical processes.
• Explain how you collected and recorded the data as well as the involved analytical methods and calculations.
• Use the past tense to write this section.
• Discuss the limitations and margins of error and how you tried to minimize them.
• Where relevant, mention the safety precautions and protective equipment used during the experiment.

Your methods section should be accurate enough for other researchers to follow the instructions and obtain results similar to yours.

Lab report method example

• Two aluminum alloy samples: 6061-T6 and 7075-T6
• 3% NaCl solution
• Two beakers
• Two stirring rods
• Digital scale
• Vernier caliper
• Cut four aluminum alloy samples, two from each type of alloy, each with dimensions of 1 cm x 1 cm x 0.2 cm.
• Clean the samples thoroughly using ethanol to remove any impurities or oils.
• Weigh each sample accurately using a digital scale and record the initial weight.
• Prepare a 3% NaCl solution by dissolving 30 g of NaCl in 1000 mL of deionized water.
• Pour 250 mL of the 3% NaCl solution into each beaker.
• Submerge two samples of each aluminum alloy in separate beakers containing the NaCl solution.
• Use the stirring rods to stir the solutions gently to ensure uniformity.
• Allow the samples to remain in the solutions for 72 hours at room temperature (25°C).
• After 72 hours, carefully remove each sample from the solution and rinse with deionized water to remove any remaining salt.
• Dry each sample using a lint-free cloth and measure its weight using the digital scale.
• Record the final weight of each sample.
• Calculate the weight loss of each sample by subtracting the final weight from the initial weight.
• Use a Vernier caliper to measure the thickness of each sample, and record these measurements.
• Calculate the corrosion rate for each sample by dividing the weight loss by the surface area of the sample and the time of immersion in the solution.

Data Collection:

Weight loss and thickness measurements were recorded for each sample after the 72-hour immersion period. Corrosion rates were calculated using the weight loss, surface area, and time of immersion.

The experiment was conducted in a well-ventilated area with appropriate personal protective equipment, including gloves and goggles. Care was taken when handling the NaCl solution to avoid contact with the skin or eyes.

Limitations:

The experiment was conducted under controlled conditions, which may not reflect real-world scenarios. The NaCl solution concentration used may not be representative of all environmental conditions that aluminum alloys may encounter in industrial applications. Further research could explore a wider range of environmental factors to more accurately predict the corrosion resistance of aluminum alloys.

The results section presents the findings of the experiment including the data you have collected and analyzed. In some cases, this section may be combined with the discussion section.

Put your findings into words and present relevant figures, tables, and graphs. You may also include the calculations you used to analyze the data.

Here are some guidelines on how to write a results section:

• Begin with a concise summary of your key findings in the form of a brief paragraph or bullet points.
• Present the data collected in the form of tables, graphs, or charts.
• Describe important data to highlight any patterns you have observed.
• Use descriptive statistics such as mean, median, and standard deviation, to summarize your data.

Add your raw data in the Appendices section and refer to it whenever required. Remember to use symbols and units of measurement correctly.

Lab report results example

The aluminum alloys tested have varying degrees of corrosion resistance. Table 1 shows the corrosion rates for each sample, calculated as the percentage weight loss over the duration of the experiment.

Table 1: Corrosion rates for aluminum alloy samples

Sample Corrosion rate (%)

As can be seen from Table 1, sample C had the lowest corrosion rate, indicating the highest resistance to corrosion among the four samples tested. Sample A had the highest corrosion rate, indicating the lowest corrosion resistance.

Figure 1 shows the corrosion morphology of the aluminum alloy samples after exposure to the saltwater solution for 7 days. The images were taken using scanning electron microscopy (SEM).

The SEM images show that sample C had the least amount of corrosion, with only small pits visible on the surface. Samples A and B showed more severe corrosion, with visible pitting and cracking. Sample D showed moderate corrosion, with some surface roughening and small pits.

In conclusion, the results of this experiment indicate that the corrosion resistance of aluminum alloys varies depending on the composition of the alloy. Sample C, which had the lowest corrosion rate and the least amount of corrosion morphology, showed the highest resistance to corrosion among the four samples tested. Further research could investigate the effect of different environmental conditions on the corrosion resistance of aluminum alloys.

The discussion section of a lab report is where you interpret and analyze the results of your experiment in the context of the research question or hypothesis. This is the most important part of the lab report because this is your contribution to your field of study.

Follow these guidelines to write your discussion section:

• Begin with a brief summary of the main findings of the experiment.
• Interpret the results and explain how they relate to your research question or hypothesis.
• Compare the results to previous research in the field and analyze how they support or oppose existing theories or models.
• Discuss any limitations or sources of error in the experiment and how they can be improved upon.
• If applicable, include any additional analysis such as post-hoc tests or follow-up experiments.

Your discussion section shouldn’t simply repeat the results but offer a critical interpretation and analysis of them. Furthermore, it should also reflect upon the methods and procedures undertaken and take stock of whether you applied processes most favorable for your subject.

Lab report discussion example

The investigation into the corrosion resistance of aluminum alloys has provided valuable insight into the behavior of these materials under various conditions. The results of the experiment indicated that the aluminum alloys tested had varying degrees of corrosion resistance depending on the specific alloy composition and environmental conditions.

Comparing the results to previous research in the field, the findings are consistent with the general understanding that aluminum alloys are susceptible to corrosion under certain circumstances. However, the exact mechanisms of corrosion and the specific factors that influence corrosion resistance are still subject to ongoing research.

One limitation of the experiment is the relatively short duration of exposure to the corrosive environment. Longer exposure times may have provided additional insights into the behavior of the aluminum alloys over time. Additionally, the use of only one type of corrosive environment may not accurately reflect the behavior of the materials in other environments.

The unexpected finding of pitting corrosion in Alloy B warrants further investigation to determine the underlying causes and potential solutions. Future research could also explore the effects of additional factors, such as temperature and humidity, on the corrosion resistance of aluminum alloys.

Overall, the results of this experiment demonstrate the importance of considering the specific composition and environmental conditions when evaluating the corrosion resistance of aluminum alloys. The findings have implications for the development of more durable and corrosion-resistant materials for various applications in industry and engineering.

The conclusion summarizes the experiment and its significance in your field of study. It’s usually one brief paragraph, and in some cases might be omitted altogether. Check with your instructor about whether or not you need to write a lab report conclusion.

Here’s how to write a lab report conclusion:

• State whether the experiment supported or opposed your hypothesis.
• Reflect upon the significance and implications of your study.
• Suggest avenues for future research.

Lab report conclusion example

The investigation into the corrosion resistance of aluminum alloys demonstrated that the aluminum alloys tested had varying degrees of corrosion resistance, depending on their specific composition and the nature of the corrosive environment. The results of the experiment are consistent with previous research in the field, and the findings support the notion that aluminum alloys are susceptible to corrosion under certain conditions.

The experiment also revealed some unexpected findings, such as the pitting corrosion observed in Alloy B. This finding warrants further investigation to determine the underlying causes and potential solutions.

The experiment was limited by the relatively short exposure time to the corrosive environment and the use of only one type of corrosive environment. Future research could explore the effects of longer exposure times and different corrosive environments on the corrosion resistance of aluminum alloys.

Overall, the results of this experiment provide important insights into the behavior of aluminum alloys and have implications for the development of more durable and corrosion-resistant materials for various applications in industry and engineering.

List all the sources you consulted while writing the lab report. Include the full bibliographic information in the appropriate format.

For lab reports in sciences and social sciences, the APA citation style is usually followed. Students of business, fine arts, and history will use Chicago style citations in their lab reports. In the rare event of a lab report under humanities, you’ll be expected to write your citations in MLA format .

Remember that failing to cite your sources is considered plagiarism and has serious consequences. Always give credit where credit is due!

Lab Report Example & Templates

A. basic lab report template, b. chemistry lab report example, c. example of good labeling.

The above examples accurately demonstrate the hallmarks of a good lab report. If you need help to perfect your lab report, you can consider taking our editing and proofreading services . Keep reading to perfect your writing skills! 

• The Top 5 Dos & Don’ts of Academic Writing | Useful Examples
• 10 Most Common Grammar Mistakes & How to Avoid Them
• 14 Punctuation Marks: Examples & Free Guide on How to Use

Frequently Asked Questions

What is the primary purpose of writing a lab report, what should a lab report look like, how to write a lab report for biology, how long is a lab report, what is the longest part of a lab report.

Found this article helpful?

6 comments on “ How to Write a Lab Report: Examples from Academic Editors ”

Good info. Lucky me I came across your blog by chance. I’ve saved it for later!

Hi there, I don’t leave comments a lot but I must say, the lab report results part was quite well-written. Keep up the good work!

It’s quite well-written but you can improve the images maybe. Anyway, keep up writing.

You’ve explained each lab report section so easily! I appreciate the tips and example combination!

Honestly, the lab report examples could be better. But great work, super easy to read and informative

This information on lab report writing is so useful! Thanks for all the templates and examples, super helpful!

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Complete Guide to Writing a Lab Report (With Example)

Students tend to approach writing lab reports with confusion and dread. Whether in high school science classes or undergraduate laboratories, experiments are always fun and games until the times comes to submit a lab report. What if we didn’t need to spend hours agonizing over this piece of scientific writing? Our lives would be so much easier if we were told what information to include, what to do with all their data and how to use references. Well, here’s a guide to all the core components in a well-written lab report, complete with an example.

Things to Include in a Laboratory Report

The laboratory report is simply a way to show that you understand the link between theory and practice while communicating through clear and concise writing. As with all forms of writing, it’s not the report’s length that matters, but the quality of the information conveyed within. This article outlines the important bits that go into writing a lab report (title, abstract, introduction, method, results, discussion, conclusion, reference). At the end is an example report of reducing sugar analysis with Benedict’s reagent.

The report’s title should be short but descriptive, indicating the qualitative or quantitative nature of the practical along with the primary goal or area of focus.

Following this should be the abstract, 2-3 sentences summarizing the practical. The abstract shows the reader the main results of the practical and helps them decide quickly whether the rest of the report is relevant to their use. Remember that the whole report should be written in a passive voice .

Introduction

The introduction provides context to the experiment in a couple of paragraphs and relevant diagrams. While a short preamble outlining the history of the techniques or materials used in the practical is appropriate, the bulk of the introduction should outline the experiment’s goals, creating a logical flow to the next section.

Some reports require you to write down the materials used, which can be combined with this section. The example below does not include a list of materials used. If unclear, it is best to check with your teacher or demonstrator before writing your lab report from scratch.

Step-by-step methods are usually provided in high school and undergraduate laboratory practicals, so it’s just a matter of paraphrasing them. This is usually the section that teachers and demonstrators care the least about. Any unexpected changes to the experimental setup or techniques can also be documented here.

The results section should include the raw data that has been collected in the experiment as well as calculations that are performed. It is usually appropriate to include diagrams; depending on the experiment, these can range from scatter plots to chromatograms.

The discussion is the most critical part of the lab report as it is a chance for you to show that you have a deep understanding of the practical and the theory behind it. Teachers and lecturers tend to give this section the most weightage when marking the report. It would help if you used the discussion section to address several points:

• Explain the results gathered. Is there a particular trend? Do the results support the theory behind the experiment?
• Highlight any unexpected results or outlying data points. What are possible sources of error?
• Address the weaknesses of the experiment. Refer to the materials and methods used to identify improvements that would yield better results (more accurate equipment, better experimental technique, etc.)  

Finally, a short paragraph to conclude the laboratory report. It should summarize the findings and provide an objective review of the experiment.

If any external sources were used in writing the lab report, they should go here. Referencing is critical in scientific writing; it’s like giving a shout out (known as a citation) to the original provider of the information. It is good practice to have at least one source referenced, either from researching the context behind the experiment, best practices for the method used or similar industry standards.

Google Scholar is a good resource for quickly gathering references of a specific style . Searching for the article in the search bar and clicking on the ‘cite’ button opens a pop-up that allows you to copy and paste from several common referencing styles.

Example: Writing a Lab Report

Title : Semi-Quantitative Analysis of Food Products using Benedict’s Reagent

Abstract : Food products (milk, chicken, bread, orange juice) were solubilized and tested for reducing sugars using Benedict’s reagent. Milk contained the highest level of reducing sugars at ~2%, while chicken contained almost no reducing sugars.

Introduction : Sugar detection has been of interest for over 100 years, with the first test for glucose using copper sulfate developed by German chemist Karl Trommer in 1841. It was used to test the urine of diabetics, where sugar was present in high amounts. However, it wasn’t until 1907 when the method was perfected by Stanley Benedict, using sodium citrate and sodium carbonate to stabilize the copper sulfate in solution. Benedict’s reagent is a bright blue because of the copper sulfate, turning green and then red as the concentration of reducing sugars increases.

Benedict’s reagent was used in this experiment to compare the amount of reducing sugars between four food items: milk, chicken solution, bread and orange juice. Following this, standardized glucose solutions (0.0%, 0.5%, 1.0%, 1.5%, 2.0%) were tested with Benedict’s reagent to determine the color produced at those sugar levels, allowing us to perform a semi-quantitative analysis of the food items.

Method : Benedict’s reagent was prepared by mixing 1.73 g of copper (II) sulfate pentahydrate, 17.30 g of sodium citrate pentahydrate and 10.00 g of sodium carbonate anhydrous. The mixture was dissolved with stirring and made up to 100 ml using distilled water before filtration using filter paper and a funnel to remove any impurities.

4 ml of milk, chicken solution and orange juice (commercially available) were measured in test tubes, along with 4 ml of bread solution. The bread solution was prepared using 4 g of dried bread ground with mortar and pestle before diluting with distilled water up to 4 ml. Then, 4 ml of Benedict’s reagent was added to each test tube and placed in a boiling water bath for 5 minutes, then each test tube was observed.

Next, glucose solutions were prepared by dissolving 0.5 g, 1.0 g, 1.5 g and 2.0 g of glucose in 100 ml of distilled water to produce 0.5%, 1.0%, 1.5% and 2.0% solutions, respectively. 4 ml of each solution was added to 4 ml of Benedict’s reagent in a test tube and placed in a boiling water bath for 5 minutes, then each test tube was observed.

Results : Food Solutions (4 ml) with Benedict’s Reagent (4 ml)

Glucose Solutions (4 ml) with Benedict’s Reagent (4 ml)

Semi-Quantitative Analysis from Data

Discussion : From the analysis of food solutions along with the glucose solutions of known concentrations, the semi-quantitative analysis of sugar levels in different food products was performed. Milk had the highest sugar content of 2%, with orange juice at 1.5%, bread at 0.5% and chicken with 0% sugar. These values were approximated; the standard solutions were not the exact color of the food solutions, but the closest color match was chosen.

One point of contention was using the orange juice solution, which conferred color to the starting solution, rendering it green before the reaction started. This could have led to the final color (and hence, sugar quantity) being inaccurate. Also, since comparing colors using eyesight alone is inaccurate, the experiment could be improved with a colorimeter that can accurately determine the exact wavelength of light absorbed by the solution.

Another downside of Benedict’s reagent is its inability to react with non-reducing sugars. Reducing sugars encompass all sugar types that can be oxidized from aldehydes or ketones into carboxylic acids. This means that all monosaccharides (glucose, fructose, etc.) are reducing sugars, while only select polysaccharides are. Disaccharides like sucrose and trehalose cannot be oxidized, hence are non-reducing and will not react with Benedict’s reagent. Furthermore, Benedict’s reagent cannot distinguish between different types of reducing sugars.

Conclusion : Using Benedict’s reagent, different food products were analyzed semi-quantitatively for their levels of reducing sugars. Milk contained around 2% sugar, while the chicken solution had no sugar. Overall, the experiment was a success, although the accuracy of the results could have been improved with the use of quantitative equipment and methods.

Reference :

• Raza, S. I., Raza, S. A., Kazmi, M., Khan, S., & Hussain, I. (2021). 100 Years of Glucose Monitoring in Diabetes Management.  Journal of Diabetes Mellitus ,  11 (5), 221-233.
• Benedict, Stanley R (1909). A Reagent for the Detection of Reducing Sugars.  Journal of Biological Chemistry ,  5 , 485-487.

Using this guide and example, writing a lab report should be a hassle-free, perhaps even enjoyable process!

About the Author

Sean is a consultant for clients in the pharmaceutical industry and is an associate lecturer at La Trobe University, where unfortunate undergrads are subject to his ramblings on chemistry and pharmacology.

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Formatting Science Reports

This section describes an organizational structure commonly used to report experimental research in many scientific disciplines, the IMRAD format: I ntroduction, M ethods, R esults, And D iscussion.

When and when not to use the IMRAD format

Although most scientific reports use the IMRAD format, there are some exceptions.

This format is usually not used in reports describing other kinds of research, such as field or case studies, in which headings are more likely to differ according to discipline. Although the main headings are standard for many scientific fields, details may vary; check with your instructor, or, if submitting an article to a journal, refer to the instructions to authors.

Developing a Title

Titles should.

• Describe contents clearly and precisely, so that readers can decide whether to read the report
• Provide key words for indexing

Titles should NOT

• Include wasted words such as “studies on,” “an investigation of”
• Use abbreviations and jargon
• Use “cute” language

Good Titles

The Relationship of Luteinizing Hormone to Obesity in the Zucker Rat

Poor Titles

An Investigation of Hormone Secretion and Weight in Rats Fat Rats: Are Their Hormones Different?

The Abstract

The guidelines below address issues to consider when writing an abstract.

What is the report about, in miniature and without specific details?

• State main objectives. (What did you investigate? Why?)
• Describe methods. (What did you do?)
• Summarize the most important results. (What did you find out?)
• State major conclusions and significance. (What do your results mean? So what?)

What to avoid:

• Do not include references to figures, tables, or sources.
• Do not include information not in report.

Additional tips:

• Find out maximum length (may vary from 50 to 300+ words).
• Process: Extract key points from each section. Condense in successive revisions.

The Introduction

Guidelines for effective scientific report introductions.

What is the problem?

• Describe the problem investigated.
• Summarize relevant research to provide context, key terms, and concepts so your reader can understand the experiment.

Why is it important?

• Review relevant research to provide rationale. (What conflict or unanswered question, untested population, untried method in existing research does your experiment address? What findings of others are you challenging or extending?)

What solution (or step toward a solution) do you propose?

• Briefly describe your experiment: hypothesis(es), research question(s); general experimental design or method; justification of method if alternatives exist.
• Move from general to specific: problem in real world/research literature –> your experiment.
• Engage your reader: answer the questions, “What did you do?” “Why should I care?”
• Make clear the links between problem and solution, question asked and research design, prior research and your experiment.
• Be selective, not exhaustive, in choosing studies to cite and amount of detail to include. (In general, the more relevant an article is to your study, the more space it deserves and the later in the Introduction it appears.)
• Ask your instructor whether to summarize results and/or conclusions in the Introduction.

Methods Section

Below are some questions to consider for effective methods sections in scientific reports.

How did you study the problem?

• Briefly explain the general type of scientific procedure you used.

What did you use?

(May be subheaded as Materials)

• Describe what materials, subjects, and equipment (chemicals, experimental animals, apparatus, etc.) you used. (These may be subheaded Animals, Reagents, etc.)

How did you proceed?

(May be subheaded as Methods or Procedures)

• Explain the steps you took in your experiment. (These may be subheaded by experiment, types of assay, etc.)
• Provide enough detail for replication. For a journal article, include, for example, genus, species, strain of organisms; their source, living conditions, and care; and sources (manufacturer, location) of chemicals and apparatus.
• Order procedures chronologically or by type of procedure (subheaded) and chronologically within type.
• Use past tense to describe what you did.
• Quantify when possible: concentrations, measurements, amounts (all metric); times (24-hour clock); temperatures (centigrade)
• Don’t include details of common statistical procedures.
• Don’t mix results with procedures.

Results Section

The section below offers some questions asked for effective results sections in scientific reports.

What did you observe?

For each experiment or procedure:

• Briefly describe experiment without detail of Methods section (a sentence or two).
• Representative: most common
• Best Case: best example of ideal or exception
• from most to least important
• from simple to complex
• organ by organ; chemical class by chemical class
• Use past tense to describe what happened.
• Don’t simply repeat table data; select .
• Don’t interpret results.
• Avoid extra words: “It is shown in Table 1 that X induced Y” –> “X induced Y (Table 1).”

Discussion Section

The table below offers some questions effective discussion sections in scientific reports address.

What do your observations mean?

• Summarize the most important findings at the beginning.

What conclusions can you draw?

For each major result:

• Describe the patterns, principles, relationships your results show.
• Explain how your results relate to expectations and to literature cited in your Introduction. Do they agree, contradict, or are they exceptions to the rule?
• Explain plausibly any agreements, contradictions, or exceptions.
• Describe what additional research might resolve contradictions or explain exceptions.

How do your results fit into a broader context?

• Suggest the theoretical implications of your results.
• Suggest practical applications of your results?
• Extend your findings to other situations or other species.
• Give the big picture: do your findings help us understand a broader topic?
• Move from specific to general: your finding(s) –> literature, theory, practice.
• Don’t ignore or bury the major issue. Did the study achieve the goal (resolve the problem, answer the question, support the hypothesis) presented in the Introduction?
• Give evidence for each conclusion.
• Discuss possible reasons for expected and unexpected findings.
• Don’t overgeneralize.
• Don’t ignore deviations in your data.
• Avoid speculation that cannot be tested in the foreseeable future.

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How to Write a Scientific Paper: Practical Guidelines

Edgard delvin.

1 Centre de recherche, CHU Sainte-Justine

2 Département de Biochimie, Université de Montréal, Montréal, Canada

Tahir S. Pillay

3 Department of Chemical Pathology, Faculty of Health Sciences, University of Pretoria

4 Division of Chemical Pathology, University of Cape Town

5 National Health Laboratory Service, CTshwane Academic Division, Pretoria, South Africa

Anthony Newman

6 Life Sciences Department, Elsevier, Amsterdam, The Netherlands

Precise, accurate and clear writing is essential for communicating in health sciences, as publication is an important component in the university criteria for academic promotion and in obtaining funding to support research. In spite of this, the development of writing skills is a subject infrequently included in the curricula of faculties of medicine and allied health sciences. Therefore clinical investigators require tools to fill this gap. The present paper presents a brief historical background to medical publication and practical guidelines for writing scientific papers for acceptance in good journals.

INTRODUCTION

A scientific paper is the formal lasting record of a research process. It is meant to document research protocols, methods, results and conclusions derived from an initial working hypothesis. The first medical accounts date back to antiquity. Imhotep, Pharaoh of the 3 rd Dynasty, could be considered the founder of ancient Egyptian medicine as he has been credited with being the original author of what is now known as the Edwin Smith Papyrus ( Figure 1 ). The Papyrus, by giving some details on cures and anatomical observations, sets the basis of the examination, diagnosis, treatment, and prognosis of numerous diseases. Closer to the Common Era, in 460 BCE, Hippocrates wrote 70 books on medicine. In 1020, the Golden age of the Muslim Culture, Ibn Sina, known as Avicenna ( Figure 2a ), recorded the Canon of medicine that was to become the most used medical text in Europe and Middle East for almost half a millennium. This was followed in the beginning of the 12 th Century bytheextensivetreatiseofMaimonides( Figure 2b ) (Moses ben Maimon) on Greek and Middle Eastern medicine. Of interest, by the end of the 11 th Century Trotula di Ruggiero, a woman physician, wrote several influential books on women’s ailment. A number of other hallmark treatises also became more accessible, thanks to the introduction of the printing press that allowed standardization of the texts. One example is the De Humani Corporis Fabrica by Vesalius which contains hundreds of illustrations of human dissection. Thomas A Lang provides an excellent concise history of scientific publications [ 1 ]. These were the days when writing and publishing scientific or philosophical works were the privilege of the few and hence there was no or little competition and no recorded peer reviewing system. Times have however changed, and contemporary scientists have to compose with an increasingly harsh competition in attracting editors and publishers attention. As an example, the number of reports and reviews on obesity and diabetes has increased from 400 to close to 4000/year and 50 to 600/year respectively over a period of 20 years ( Figure 3 ). The present article, essentially based on TA Lang’s guide for writing a scientific paper [ 1 ], will summarize the steps involved in the process of writing a scientific report and in increasing the likelihood of its acceptance.

The Edwin Smith Papyrus (≈3000 BCE)

Avicenna and Maimonides

Annual publication load in the field of obesity and diabetes over 20 years.

Reasons for publishing are varied. One may write to achieve a post-graduate degree, to obtain funding for pursuing research or for academic promotion. While all 3 reasons are perfectly legitimate, one must ask whether they are sufficient to be considered by editors, publishers and reviewers. Why then should the scientist write? The main reason is to provide to the scientific community data based on hypotheses that are innovative and thus to advance the understanding in a specific domain. One word of caution however, is that if a set of experiments has not been done or reported, it does not mean that it should be. It may simply reflect a lack of interest in it.

DECIDING ON PUBLISHING AND TARGETING THE JOURNAL

In order to assist with the decision process, pres-ent your work orally first to colleagues in your field who may be more experienced in publishing. This step will help you in gauging whether your work is publishable and in shaping the paper.

Targeting the journal, in which you want to present your data, is also a critical step and should be done before starting to write. One hint is to look for journals that have published similar work to yours, and that aims readers most likely to be interested in your research. This will allow your article to be well read and cited. These journals are also those that you are most likely to read on a regular basis and to cite abundantly. The next step is to decide whether you submit your manuscript to a top-ranking impact factor journal or to a journal of lower prestige. Although it is tempting to test the waters, or to obtain reviewers comments, be realistic about the contribution your work provides and submit to a journal with an appropriate rank.

Do not forget that each rejection delays publication and that the basin of reviewers within your specialty is shallow. Thus repeated submission to different journals could likely result in having your work submitted for review to the same re-viewer.

DECIDING ON THE TYPE OF MANUSCRIPT

There are several types of scientific reports: observational, experimental, methodological, theoretical and review. Observational studies include 1) single-case report, 2) collective case reports on a series of patients having for example common signs and symptoms or being followed-up with similar protocols, 3) cross-sectional, 4) cohort studies, and 5) case-control studies. The latter 3 could be perceived as epidemiological studies as they may help establishing the prevalence of a condition, and identify a defined population with and without a particular condition (disease, injury, surgical complication). Experimental reports deal with research that tests a research hypothesis through an established protocol, and, in the case of health sciences, formulate plausible explanations for changes in biological systems. Methodological reports address for example advances in analytical technology, statistical methods and diagnostic approach. Theoretical reports suggest new working hypotheses and principles that have to be supported or disproved through experimental protocols. The review category can be sub-classified as narrative, systematic and meta-analytic. Narrative reviews are often broad overviews that could be biased as they are based on the personal experience of an expert relying on articles of his or her own choice. Systematic reviews and meta-analyses are based on reproducible procedures and on high quality data. Researchers systematically identify and analyze all data collected in articles that test the same working hypothesis, avoiding selection bias, and report the data in a systematic fashion. They are particularly helpful in asking important questions in the field of healthcare and are often the initial step for innovative research. Rules or guidelines in writing such report must be followed if a quality systematic review is to be published.

For clinical research trials and systematic reviews or meta-analyses, use the Consort Statement (Consolidated Standards Of Reporting Trials) and the PRISMA Statement (Preferred Reporting Items for Systematic reviews and Meta-Analyses) respectively [ 2 , 3 ]. This assures the editors and the reviewers that essential elements of the trials and of the reviews were tackled. It also speeds the peer review process. There are several other Statements that apply to epidemiological studies [ 4 ], non-randomized clinical trials [ 5 ], diagnostic test development ( 6 ) and genetic association studies ( 7 ). The Consortium of Laboratory Medicine Journal Editors has also published guidelines for reporting industry-sponsored laboratory research ( 8 ).

INITIAL STEPS IN THE PROCESS OF WRITING A SCIENTIFIC DOCUMENT

Literature review is the initial and essential step before starting your study and writing the scientific report based on it. In this process use multiple databases, multiple keyword combinations. It will allow you to track the latest development in your field and thus avoid you to find out that someone else has performed the study before you, and hence decrease the originality of your study. Do not forget that high-ranking research journals publish results of enough importance and interest to merit their publication.

Determining the authorship and the order of authorship, an ethical issue, is the second essential step, and is unfortunately often neglected. This step may avoid later conflicts as, despite existing guidelines, it remains a sensitive issue owing to personal biases and the internal politics of institutions. The International Committee of Medical Editors has adopted the following guidelines for the biomedical sciences ( 9 ).

“Authorship credit should be based only on: 1) Substantial contributions to the conception and design, or acquisition of data, or analysis and interpretation of data; 2) Drafting the article or revising it critically for important intellectual content; and 3) Final approval of the version to be published. Conditions 1, 2 and 3 must be all met. Acquisition of funding, the collections of data, or general supervision of the research group, by themselves, do not justify authorship.” ( 9 , 10 )

The order of authorship should reflect the individual contribution to the research and to the publication, from most to least ( 11 ). The first author usually carries out the lead for the project reported. However the last author is often mistakenly perceived as the senior author. This is perpetuated from the European tradition and is discouraged. As there are divergent conventions among journals, the order of authorship order may or may not reflect the individual contributions; with the exception that the first author should be the one most responsible for the work.

WRITING EFFECTIVELY

Effective writing requires that the text helps the readers 1) understand the content and the context, 2) remember what the salient points are, 3) find the information rapidly and, 4) use or apply the information given. These cardinal qualities should be adorned with the precise usage of the language, clarity of the text, inclu-siveness of the information, and conciseness. Effective writing also means that you have to focus on the potential readers’ needs. Readers in science are informed individuals who are not passive, and who will formulate their own opinion of your writing whether or not the meaning is clear. Therefore you need to know who your audience is. The following 4 questions should help you writing a reader-based text, meaning written to meet the information needs of readers [ 12 ].

What do you assume your readers already know? In other words, which terms and concepts can you use without explanation, and which do you have to define?

What do they want to know? Readers in science will read only if they think they will learn something of value.

What do they need to know? Your text must contain all the information necessary for the reader to understand it, even if you think this information id obvious to them.

What do they think they know that is not so? Correcting misconceptions can be an important function of communication, and persuading readers to change their minds can be a challenging task.

WRITING THE SCIENTIFIC PAPER

Babbs and Tacker ’ s advice to write as much of the paper before performing the research project or experimental protocol may, at first sight, seem unexpected and counterintuitive [ 13 ], but in fact it is exactly what is being done when writing a research grant application. It will allow you to define the authorship alluded to before. The following section will briefly review the structure of the different sections of a manuscript and describe their purpose.

Reading the instructions to authors of the Journal you have decided to submit your manuscript is the first important step. They provide you with the specific requirements such as the way of listing the authors, type of abstract, word, figure or table limits and citation style. The Mulford Library of University of Toledo website contains instructions to authors for over 3000 journals ( http://mulford.meduoiho.edu/instr/ ).

The general organization of an article follows the IMRAD format (Introduction, Methods, Results, and Discussion). These may however vary. For instance, in clinical research or epidemiology studies, the methods section will include details on the subjects included, and there will be a statement of the limitation of the study. Although conclusions may not always be part of the structure, we believe that it should, even in methodological reports.

The tile page provides essential information so that the editor, reviewers, and readers will identify the manuscript and the authors at a glance as well as enabling them to classify the field to which the article pertains.

The title page must contain the following:

• The tile of the article – it is an important part of the manuscript as it is the most often read and will induce the interested readers to pursue further. Therefore the title should be precise, accurate, specific and truthful;
• Each author’s given name (it may be the full name or initials) and family name;
• Each author’s affiliation;
• Some journals ask for highest academic degree;
• A running title that is usually limited to a number of characters. It must relate to the full title;
• Key words that will serve for indexing;
• For clinical studies, the trial’s registration number;
• The name of the corresponding author with full contact information.

The abstract is also an important section of your manuscript. Importantly, the abstract is the part of the article that your peers will see when consulting publication databases such as PubMed. It is the advertisement to your work and will strongly influence the editor deciding whether it will be submitted to reviewers or not. It will also help the readers decide to read the full article. Hence it has to be comprehensible on its own. Writing an abstract is challenging. You have to carefully select the content and, while being concise, assure to deliver the essence of your manuscript.

Without going into details, there are 3 types of abstracts: descriptive, informative and structured. The descriptive abstract is particularly used for theoretical, methodological or review articles. It usually consists of a single paragraph of 150 words or less. The informative abstract, the most common one, contains specific information given in the article and, are organized with an introduction (background, objectives), methods, results and discussion with or without conclusion. They usually are 150 to 250 words in length. The structured abstract is in essence an informative abstract with sections labeled with headings. They may also be longer and are limited to 250 to 300 words. Recent technology also allows for graphical or even video abstracts. The latter are interesting in the context of cell biology as they enable the investigator to illustrate ex vivo experiment results (phagocytosis process for example).

Qualities of abstracts:

• Understood without reading the full paper. Shoul dcontain no abbreviations.lf abbreviations are used, they must be defined. This however removes space for more important information;
• Contains information consistent with the full report. Conclusions in the abstract must match those given in the full report;
• Is attractive and contains information needed to decide whether to read the full report.

Introduction

The introduction has 3 main goals: to establish the need and importance of your research, to indicate how you have filled the knowledge gap in your field and to give your readers a hint of what they will learn when reading your paper. To fulfil these goals, a four-part introduction consisting of a background statement, a problem statement, an activity statement and a forecasting statement, is best suited. Poorly defined background information and problem setting are the 2 most common weaknesses encountered in introductions. They stem from the false perception that peer readers know what the issue is and why the study to solve it is necessary. Although not a strict rule, the introduction in clinical science journals should target only references needed to establish the rationale for the study and the research protocol. This differ from more basic science or cell biology journals, for which a longer and elaborate introduction may be justified because the research at hand consists of several approaches each requiring background and justification.

The 4-part introduction consists of:

• A background statement that provides the context and the approach of the research;
• A problem statement that describes the nature, scope and importance of the problem or the knowledge gap;
• An activity statement, that details the research question, sets the hypothesis and actions undertaken for the investigation;
• A forecasting statement telling the readers whattheywillfìndwhen readingyourarticle [ 14 ].

Methods section

This section may be named “Materials and Methods”, “Experimental section” or “Patients and Methods” depending upon the type of journal. Its purpose to allow your readers to provide enough information on the methods used for your research and to judge on their adequacy. Although clinical and “basic” research protocols differ, the principles involved in describing the methods share similar features. Hence, the breadth of what is being studied and how the study can be performed is common to both. What differ are the specific settings. For example, when a study is conducted on humans, you must provide, up front, assurance that it has received the approval of you Institution Ethics Review Board (IRB) and that participants have provided full and informed consent. Similarly when the study involves animals, you must affirm that you have the agreement from your Institutional Animal Care and Use Committee (IACUC). These are too often forgotten, and Journals (most of them) abiding to the rules of the Committee on Publication Ethics (COPE) and World Association of Medical Editors (WAME) will require such statement. Although journals publishing research reports in more fundamental science may not require such assurance, they do however also follow to strict ethics rules related to scientific misconduct or fraud such as data fabrication, data falsification. For clinical research papers, you have to provide information on how the participants were selected, identify the possible sources of bias and confounding factors and how they were diminished.

In terms of the measurements, you have to clearly identify the materials used as well as the suppliers with their location. You should also be unambiguous when describing the analytical method. If the method has already been published, give a brief account and refer to the original publication (not a review in which the method is mentioned without a description). If you have modified it, you have to provide a detailed account of the modifications and you have to validate its accuracy, precision and repeatability. Mention the units in which results are reported and, if necessary, include the conversion factors [mass units versus “système international” (S.I.)]. In clinical research, surrogate end-points are often used as biomarkers. Under those circumstances, you must show their validity or refer to a study that has already shown that are valid.

In cases of clinical trials, the Methods section should include the study design, the patient selection mode, interventions, type of outcomes.

Statistics are important in assuring the quality of the research project. Hence, you should consult a biostatistician at the time of devising the research protocol and not after having performed the experiments or the clinical trial.

The components of the section on statistics should include:

• The way the data will be reported (mean, median, centiles for continuous data);
• Details on participant assignments to the different groups (random allocation, consecutive entry);
• Statistical comparison tools (parametric or non parametric statistics, paired or unpaired t-tests for normally distributed data and so on);
• The statistical power calculation when determining the sample size to obtain valid and significant comparisons together with the a level;
• The statistical software package used in the analysis.

Results section

The main purpose of the results section is to report the data that were collected and their relationship. It should also provide information on the modifications that have taken place because of unforeseen events leading to a modification of the initial protocol (loss of participants, reagent substitution, loss of data).

• Report results as tables and figures whenever possible, avoid duplication in the text. The text should summarize the findings;
• Report the data with the appropriate descriptive statistics;
• Report any unanticipated events that could affect the results;
• Report a complete account of observations and explanations for missing data (patient lost).

The discussion should set your research in context, reinforce its importance and show how your results have contributed to the further understanding of the problem posed. This should appear in the concluding remarks. The following organization could be helpful.

• Briefly summarize the main results of your study in one or two paragraphs, and how they support your working hypothesis;
• Provide an interpretation of your results and show how they logically fit in an overall scheme (biological or clinical);
• Describe how your results compare with those of other investigators, explain the differences observed;
• Discuss how your results may lead to a new hypothesis and further experimentation, or how they could enhance the diagnostic procedures.
• Provide the limitations of your study and steps taken to reduce them. This could be placed in the concluding remarks.

Acknowledgements

The acknowledgements are important as they identify and thank the contributors to the study, who do not meet the criteria as co-authors. They also include the recognition of the granting agency. In this case the grant award number and source is usually included.

Declaration of competing interests

Competing interests arise when the author has more than one role that may lead to a situation where there is a conflict of interest. This is observed when the investigator has a simultaneous industrial consulting and academic position. In that case the results may not be agreeable to the industrial sponsor, who may impose a veto on publication or strongly suggest modifications to the conclusions. The investigator must clear this issue before starting the contracted research. In addition, the investigator may own shares or stock in the company whose product forms the basis of the study. Such conflicts of interest must be declared so that they are apparent to the readers.

Acknowledgments

The authors thank Thomas A Lang, for his advice in the preparation of this manuscript.

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Writing a scientific lab report is significantly different from writing for other classes like philosophy, English, and history. The most prominent form of writing in biology, chemistry, and environmental science is the lab report, which is a formally written description of results and discoveries found in an experiment. College lab reports should emulate and follow the same formats as reports found in scholarly journals, such as Nature , Cell , and The American Journal of Biochemistry .

Report Format

Title: The title says what you did. It should be brief (aim for ten words or less) and describe the main point of the experiment or investigation.

• Example:  Caffeine Increases Amylase Activity in the Mealworm ( Tenebrio molitar).
• If you can, begin your title using a keyword rather than an article like “The” or “A.”

Abstract: An abstract is a very concise summary of the purpose of the report, data presented, and major conclusions in about 100 - 200 words.  Abstracts are also commonly required for conference/presentation submissions because they summarize all of the essential materials necessary to understand the purpose of the experiment. They should consist of a background sentence , an introduction sentence , your hypothesis/purpose of the experiment, and a sentence about the results and what this means.

Introduction: The introduction of a lab report defines the subject of the report, provides background information and relevant studies, and outlines scientific purpose(s) and/or objective(s).

• The introduction is a place to provide the reader with necessary research on the topic and properly cite sources used.
• Summarizes the current literature on the topic including primary and secondary sources.
• Introduces the paper’s aims and scope.
• States the purpose of the experiment and the hypothesis.

Materials and Methods: The materials and methods section is a vital component of any formal lab report. This section of the report gives a detailed account of the procedure that was followed in completing the experiment as well as all important materials used. (This includes bacterial strains and species names in tests using living subjects.)

• Discusses the procedure of the experiment in as much detail as possible.
• Provides information about participants, apparatus, tools, substances, location of experiment, etc.
• For field studies, be sure to clearly explain where and when the work was done.
• It must be written so that anyone can use the methods section as instructions for exact replications.
• Don’t hesitate to use subheadings to organize these categories.
• Practice proper scientific writing forms. Be sure to use the proper abbreviations for units. Example: The 50mL sample was placed in a 5ºC room for 48hrs.

Results: The results section focuses on the findings, or data, in the experiment, as well as any statistical tests used to determine their significance.

• Concentrate on general trends and differences and not on trivial details.
• Summarize the data from the experiments without discussing their implications (This is where all the statistical analyses goes.)
• Organize data into tables, figures, graphs, photographs, etc.  Data in a table should not be duplicated in a graph or figure. Be sure to refer to tables and graphs in the written portion, for example, “Figure 1 shows that the activity....”
• Number and title all figures and tables separately, for example, Figure 1 and Table 1 and include a legend explaining symbols and abbreviations. Figures and graphs are labeled below the image while tables are labeled above.

  Discussion: The discussion section interprets the results, tying them back to background information and experiments performed by others in the past.This is also the area where further research opportunities shold be explored.

• Interpret the data; do not restate the results.
• Observations should also be noted in this section, especially anything unusual which may affect your results.

For example, if your bacteria was incubated at the wrong temperature or a piece of equipment failed mid-experiment, these should be noted in the results section.

• Relate results to existing theories and knowledge.This can tie back to your introduction section because of the background you provided.
• Explain the logic that allows you to accept or reject your original hypotheses.
• Include suggestions for improving your techniques or design, or clarify areas of doubt for further research.

Acknowledgements and References: A references list should be compiled at the end of the report citing any works that were used to support the paper. Additionally, an acknowledgements section should be included to acknowledge research advisors/ partners, any group or person providing funding for the research and anyone outside the authors who contributed to the paper or research.

General Tips

• In scientific papers, passive voice is perfectly acceptable. On the other hand, using “I” or “we” is not.

          Incorrect: We found that caffeine increased amylase levels in Tenebrio molitar.  Correct: It was discovered that caffeine increased amylase levels in Tenebrio molitar.   

• It is expected that you use as much formal (bland) language and scientific terminology as you can. There should be no emphasis placed on “expressing yourself” or “keeping it interesting”; a lab report is not a narrative.
• In a lab report, it is important to get to the point. Be descriptive enough that your audience can understand the experiment, but strive to be concise.
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Writing a scientific paper.

• Writing a lab report
• INTRODUCTION

Writing a "good" results section

Figures and Captions in Lab Reports

"Results Checklist" from: How to Write a Good Scientific Paper. Chris A. Mack. SPIE. 2018.

Additional tips for results sections.

• LITERATURE CITED
• Bibliography of guides to scientific writing and presenting
• Peer Review
• Presentations
• Lab Report Writing Guides on the Web

This is the core of the paper. Don't start the results sections with methods you left out of the Materials and Methods section. You need to give an overall description of the experiments and present the data you found.

• Factual statements supported by evidence. Short and sweet without excess words
• Present representative data rather than endlessly repetitive data
• Discuss variables only if they had an effect (positive or negative)
• Use meaningful statistics
• Avoid redundancy. If it is in the tables or captions you may not need to repeat it

A short article by Dr. Brett Couch and Dr. Deena Wassenberg, Biology Program, University of Minnesota

• Present the results of the paper, in logical order, using tables and graphs as necessary.
• Explain the results and show how they help to answer the research questions posed in the Introduction. Evidence does not explain itself; the results must be presented and then explained. 
• Avoid: presenting results that are never discussed;  presenting results in chronological order rather than logical order; ignoring results that do not support the conclusions; 
• Number tables and figures separately beginning with 1 (i.e. Table 1, Table 2, Figure 1, etc.).
• Do not attempt to evaluate the results in this section. Report only what you found; hold all discussion of the significance of the results for the Discussion section.
• It is not necessary to describe every step of your statistical analyses. Scientists understand all about null hypotheses, rejection rules, and so forth and do not need to be reminded of them. Just say something like, "Honeybees did not use the flowers in proportion to their availability (X2 = 7.9, p<0.05, d.f.= 4, chi-square test)." Likewise, cite tables and figures without describing in detail how the data were manipulated. Explanations of this sort should appear in a legend or caption written on the same page as the figure or table.
• You must refer in the text to each figure or table you include in your paper.
• Tables generally should report summary-level data, such as means ± standard deviations, rather than all your raw data.  A long list of all your individual observations will mean much less than a few concise, easy-to-read tables or figures that bring out the main findings of your study.  
• Only use a figure (graph) when the data lend themselves to a good visual representation.  Avoid using figures that show too many variables or trends at once, because they can be hard to understand.

From:  https://writingcenter.gmu.edu/guides/imrad-results-discussion

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How to Write a Good Lab Conclusion in Science

Last Updated: June 18, 2024 Fact Checked

This article was co-authored by Bess Ruff, MA . Bess Ruff is a Geography PhD student at Florida State University. She received her MA in Environmental Science and Management from the University of California, Santa Barbara in 2016. She has conducted survey work for marine spatial planning projects in the Caribbean and provided research support as a graduate fellow for the Sustainable Fisheries Group. There are 10 references cited in this article, which can be found at the bottom of the page. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 1,768,930 times.

A lab report describes an entire experiment from start to finish, outlining the procedures, reporting results, and analyzing data. The report is used to demonstrate what has been learned, and it will provide a way for other people to see your process for the experiment and understand how you arrived at your conclusions. The conclusion is an integral part of the report; this is the section that reiterates the experiment’s main findings and gives the reader an overview of the lab trial. Writing a solid conclusion to your lab report will demonstrate that you’ve effectively learned the objectives of your assignment.

Outlining Your Conclusion

• Restate : Restate the lab experiment by describing the assignment.
• Explain : Explain the purpose of the lab experiment. What were you trying to figure out or discover? Talk briefly about the procedure you followed to complete the lab.
• Results : Explain your results. Confirm whether or not your hypothesis was supported by the results.
• Uncertainties : Account for uncertainties and errors. Explain, for example, if there were other circumstances beyond your control that might have impacted the experiment’s results.
• New : Discuss new questions or discoveries that emerged from the experiment.

• Your assignment may also have specific questions that need to be answered. Make sure you answer these fully and coherently in your conclusion.

Discussing the Experiment and Hypothesis

• If you tried the experiment more than once, describe the reasons for doing so. Discuss changes that you made in your procedures.
• Brainstorm ways to explain your results in more depth. Go back through your lab notes, paying particular attention to the results you observed. [3] X Trustworthy Source University of North Carolina Writing Center UNC's on-campus and online instructional service that provides assistance to students, faculty, and others during the writing process Go to source

• Start this section with wording such as, “The results showed that…”
• You don’t need to give the raw data here. Just summarize the main points, calculate averages, or give a range of data to give an overall picture to the reader.
• Make sure to explain whether or not any statistical analyses were significant, and to what degree, such as 1%, 5%, or 10%.

• Use simple language such as, “The results supported the hypothesis,” or “The results did not support the hypothesis.”

Demonstrating What You Have Learned

• If it’s not clear in your conclusion what you learned from the lab, start off by writing, “In this lab, I learned…” This will give the reader a heads up that you will be describing exactly what you learned.
• Add details about what you learned and how you learned it. Adding dimension to your learning outcomes will convince your reader that you did, in fact, learn from the lab. Give specifics about how you learned that molecules will act in a particular environment, for example.
• Describe how what you learned in the lab could be applied to a future experiment.

• On a new line, write the question in italics. On the next line, write the answer to the question in regular text.

• If your experiment did not achieve the objectives, explain or speculate why not.

Wrapping Up Your Conclusion

• If your experiment raised questions that your collected data can’t answer, discuss this here.

• Describe what is new or innovative about your research.
• This can often set you apart from your classmates, many of whom will just write up the barest of discussion and conclusion.

Finalizing Your Lab Report

Community Q&A

• Ensure the language used is straightforward with specific details. Try not to drift off topic. Thanks Helpful 1 Not Helpful 0
• Once again, avoid using personal pronouns (I, myself, we, our group) in a lab report. The first-person point-of-view is often seen as subjective, whereas science is based on objectivity. Thanks Helpful 1 Not Helpful 0
• If you include figures or tables in your conclusion, be sure to include a brief caption or label so that the reader knows what the figures refer to. Also, discuss the figures briefly in the text of your report. Thanks Helpful 1 Not Helpful 0

• Take care with writing your lab report when working in a team setting. While the lab experiment may be a collaborative effort, your lab report is your own work. If you copy sections from someone else’s report, this will be considered plagiarism. Thanks Helpful 4 Not Helpful 0

You Might Also Like

• ↑ https://phoenixcollege.libguides.com/LabReportWriting/introduction
• ↑ https://www.education.vic.gov.au/school/teachers/teachingresources/discipline/english/literacy/Pages/puttingittogether.aspx
• ↑ https://writingcenter.unc.edu/tips-and-tools/brainstorming/
• ↑ https://advice.writing.utoronto.ca/types-of-writing/lab-report/
• ↑ http://www.socialresearchmethods.net/kb/hypothes.php
• ↑ https://libguides.usc.edu/writingguide/conclusion
• ↑ https://libguides.usc.edu/writingguide/introduction/researchproblem
• ↑ http://writingcenter.unc.edu/handouts/scientific-reports/
• ↑ https://phoenixcollege.libguides.com/LabReportWriting/labreportstyle
• ↑ https://writingcenter.unc.edu/tips-and-tools/editing-and-proofreading/

About This Article

To write a good lab conclusion in science, start with restating the lab experiment by describing the assignment. Next, explain what you were trying to discover or figure out by doing the experiment. Then, list your results and explain how they confirmed or did not confirm your hypothesis. Additionally, include any uncertainties, such as circumstances beyond your control that may have impacted the results. Finally, discuss any new questions or discoveries that emerged from the experiment. For more advice, including how to wrap up your lab report with a final statement, keep reading. Did this summary help you? Yes No

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Many believe that a scientist’s most difficult job is not conducting an experiment but presenting the results in an effective and coherent way. Even when your methods and technique are sound and your notes are comprehensive, writing a report can be a challenge because organizing and communicating scientific findings requires patience and a thorough grasp of certain conventions. Having a clear understanding of the typical goals and strategies for writing an effective lab report can make the process much less troubling.

General Considerations

It is useful to note that effective scientific writing serves the same purpose that your lab report should. Good scientific writing explains:

• The goal(s) of your experiment
• How you performed the experiment
• The results you obtained
• Why these results are important

While it’s unlikely that you’re going to win the Nobel Prize for your work in an undergraduate laboratory course, tailoring your writing strategies in imitation of professional journals is easier than you might think, since they all follow a consistent pattern. However, your instructor has the final say in determining how your report should be structured and what should appear in each section. Please use the following explanations only to supplement your given writing criteria, rather than thinking of them as an indication of how all lab reports must be written.

In Practice

The Structure of a Report

The traditional experimental report is structured using the acronym “IMRAD” which stands for I ntroduction, M ethods, R esults and D iscussion. The “ A ” is sometimes used to stand for A bstract. For help writing abstracts, please see Sweetland’s resource entitled “What is an abstract, and how do I write one?”

Introduction: “What am I doing here?” The introduction should accomplish what any good introduction does: draw the reader into the paper. To simplify things, follow the “inverted pyramid” structure, which involves narrowing information from the most broad (providing context for your experiment’s place in science) to the most specific (what exactly your experiment is about). Consider the example below.

Most broad: “Caffeine is a mild stimulant that is found in many common beverages, including coffee.”

Less broad: “Common reactions to caffeine use include increased heart rate and increased respiratory rate.”

Slightly more specific (moving closer to your experiment): Previous research has shown that people who consume multiple caffeinated beverages per day are also more likely to be irritable.

Most specific (your experiment): This study examines the emotional states of college students (ages 18-22) after they have consumed three cups of coffee each day.

See how that worked? Each idea became slightly more focused, ending with a brief description of your particular experiment. Here are a couple more tips to keep in mind when writing an introduction:

• Include an overview of the topic in question, including relevant literature A good example: “In 1991, Rogers and Hammerstein concluded that drinking coffee improves alertness and mental focus (citation 1991).
• Explain what your experiment might contribute to past findings A good example: “Despite these established benefits, coffee may negatively impact mood and behavior. This study aims to investigate the emotions of college coffee drinkers during finals week.”
• Keep the introduction brief There’s no real advantage to writing a long introduction. Most people reading your paper already know what coffee is, and where it comes from, so what’s the point of giving them a detailed history of the coffee bean? A good example: “Caffeine is a psychoactive stimulant, much like nicotine.” (Appropriate information, because it gives context to caffeine—the molecule of study) A bad example: “Some of the more popular coffee drinks in America include cappuccinos, lattés, and espresso.” (Inappropriate for your introduction. This information is useless for your audience, because not only is it already familiar, but it doesn’t mention anything about caffeine or its effects, which is the reason that you’re doing the experiment.)
• Avoid giving away the detailed technique and data you gathered in your experiment A good example: “A sample of coffee-drinking college students was observed during end-of-semester exams.” ( Appropriate for an introduction ) A bad example: “25 college students were studied, and each given 10oz of premium dark roast coffee (containing 175mg caffeine/serving, except for Folgers, which has significantly lower caffeine content) three times a day through a plastic straw, with intervals of two hours, for three weeks.” ( Too detailed for an intro. More in-depth information should appear in your “Methods” or “Results” sections. )

Methods: “Where am I going to get all that coffee…?”

A “methods” section should include all the information necessary for someone else to recreate your experiment. Your experimental notes will be very useful for this section of the report. More or less, this section will resemble a recipe for your experiment. Don’t concern yourself with writing clever, engaging prose. Just say what you did, as clearly as possible. Address the types of questions listed below:

• Where did you perform the experiment? (This one is especially important in field research— work done outside the laboratory.)
• How much did you use? (Be precise.)
• Did you change anything about them? (i.e. Each 5 oz of coffee was diluted with 2 oz distilled water.)
• Did you use any special method for recording data? (i.e. After drinking coffee, students’ happiness was measured using the Walter Gumdrop Rating System, on a scale of 1-10.)
• Did you use any techniques/methods that are significant for the research? (i.e. Maybe you did a double blinded experiment with X and Y as controls. Was your control a placebo? Be specific.)
• Any unusual/unique methods for collecting data? If so, why did you use them?

After you have determined the basic content for your “methods” section, consider these other tips:

• Decide between using active or passive voice

There has been much debate over the use of passive voice in scientific writing. “Passive voice” is when the subject of a sentence is the recipient of the action.

• For example: Coffee was given to the students.

“Active voice” is when the subject of a sentence performs the action.

• For example: I gave coffee to the students.

The merits of using passive voice are obvious in some cases. For instance, scientific reports are about what is being studied, and not about YOU. Using too many personal pronouns can make your writing sound more like a narrative and less like a report. For that reason, many people recommend using passive voice to create a more objective, professional tone, emphasizing what was done TO your subject. However, active voice is becoming increasingly common in scientific writing, especially in social sciences, so the ultimate decision of passive vs. active voice is up to you (and whoever is grading your report).

• Units are important When using numbers, it is important to always list units, and keep them consistent throughout the section. There is a big difference between giving someone 150 milligrams of coffee and 150 grams of coffee—the first will keep you awake for a while, and the latter will put you to sleep indefinitely. So make sure you’re consistent in this regard.
• Don’t needlessly explain common techniques If you’re working in a chemistry lab, for example, and you want to take the melting point of caffeine, there’s no point saying “I used the “Melting point-ometer 3000” to take a melting point of caffeine. First I plugged it in…then I turned it on…” Your reader can extrapolate these techniques for him or herself, so a simple “Melting point was recorded” will work just fine.
• If it isn’t important to your results, don’t include it No one cares if you bought the coffee for your experiment on “3 dollar latte day”. The price of the coffee won’t affect the outcome of your experiment, so don’t bore your reader with it. Simply record all the things that WILL affect your results (i.e. masses, volumes, numbers of trials, etc).

Results: The only thing worth reading?

The “results” section is the place to tell your reader what you observed. However, don’t do anything more than “tell.” Things like explaining and analyzing belong in your discussion section. If you find yourself using words like “because” or “which suggests” in your results section, then STOP! You’re giving too much analysis.

A good example: “In this study, 50% of subjects exhibited symptoms of increased anger and annoyance in response to hearing Celine Dion music.” ( Appropriate for a “results” section—it doesn’t get caught up in explaining WHY they were annoyed. )

In your “results” section, you should:

• Display facts and figures in tables and graphs whenever possible. Avoid listing results like “In trial one, there were 5 students out of 10 who showed irritable behavior in response to caffeine. In trial two…” Instead, make a graph or table. Just be sure to label it so you can refer to it in your writing (i.e. “As Table 1 shows, the number of swear words spoken by students increased in proportion to the amount of coffee consumed.”) Likewise, be sure to label every axis/heading on a chart or graph (a good visual representation can be understood on its own without any textual explanation). The following example clearly shows what happened during each trial of an experiment, making the trends visually apparent, and thus saving the experimenter from having to explain each trial with words.

• Identify only the most significant trends. Don’t try to include every single bit of data in this section, because much of it won’t be relevant to your hypothesis. Just pick out the biggest trends, or what is most significant to your goals.

Discussion: “What does it all mean?”

The “discussion” section is intended to explain to your reader what your data can be interpreted to mean. As with all science, the goal for your report is simply to provide evidence that something might be true or untrue—not to prove it unequivocally. The following questions should be addressed in your “discussion” section:

• Is your hypothesis supported? If you didn’t have a specific hypothesis, then were the results consistent with what previous studies have suggested? A good example: “Consistent with caffeine’s observed effects on heart rate, students’ tendency to react strongly to the popping of a balloon strongly suggests that caffeine’s ability to heighten alertness may also increase nervousness.”
• Was there any data that surprised you? Outliers are seldom significant, and mentioning them is largely useless. However, if you see another cluster of points on a graph that establish their own trend, this is worth mentioning.
• Are the results useful? If you have no significant findings, then just say that. Don’t try to make wild claims about the meanings of your work if there is no statistical/observational basis for these claims—doing so is dishonest and unhelpful to other scientists reading your work. Similarly, try to avoid using the word “proof” or “proves.” Your work is merely suggesting evidence for new ideas. Just because things worked out one way in your trials, that doesn’t mean these results will always be repeatable or true.
• What are the implications of your work? Here are some examples of the types of questions that can begin to show how your study can be significant outside of this one particular experiment: Why should anyone care about what you’re saying? How might these findings affect coffee drinkers? Do your findings suggest that drinking coffee is more harmful than previously thought? Less harmful? How might these findings affect other fields of science? What about the effects of caffeine on people with emotional disorders? Do your findings suggest that they should or should not drink coffee?
• Any shortcomings of your work? Were there any flaws in your experimental design? How should future studies in this field accommodate for these complications. Does your research raise any new questions? What other areas of science should be explored as a result of your work?

Resources: Hogg, Alan. "Tutoring Scientific Writing." Sweetland Center for Writing. University of Michigan, Ann Arbor. 3/15/2011. Lecture. Swan, Judith A, and George D. Gopen. "The Science of Scientific Writing." American Scientist . 78. (1990): 550-558. Print. "Scientific Reports." The Writing Center . University of North Carolina, n.d. Web. 5 May 2011. http://www.unc.edu/depts/wcweb/handouts/lab_report_complete.html

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• Published: 05 August 2024

Personalizing driver safety interfaces via driver cognitive factors inference

• Emily S. Sumner   ORCID: orcid.org/0000-0003-1912-9640 1 , 2   na1 ,
• Jonathan DeCastro 1 , 2   na1 ,
• Jean Costa 1   na1 ,
• Deepak E. Gopinath 1 , 2   na1 ,
• Everlyne Kimani 1   na1 ,
• Shabnam Hakimi 1 ,
• Allison Morgan 1 ,
• Andrew Best 1 ,
• Hieu Nguyen 1 ,
• Daniel J. Brooks 1 , 2 ,
• Bassam ul Haq 1 ,
• Andrew Patrikalakis 1 ,
• Hiroshi Yasuda 1 ,
• Kate Sieck 1 ,
• Avinash Balachandran 1 ,
• Tiffany L. Chen 1   na1 &
• Guy Rosman 1 , 2   na1  

Scientific Reports volume  14 , Article number:  18058 ( 2024 ) Cite this article

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• Computer science
• Human behaviour

Recent advances in AI and intelligent vehicle technology hold the promise of revolutionizing mobility and transportation through advanced driver assistance systems (ADAS). Certain cognitive factors, such as impulsivity and inhibitory control have been shown to relate to risky driving behavior and on-road risk-taking. However, existing systems fail to leverage such factors in assistive driving technologies adequately. Varying the levels of these cognitive factors could influence the effectiveness and acceptance of ADAS interfaces. We demonstrate an approach for personalizing driver interaction via driver safety interfaces that are are triggered based on the inference of the driver’s latent cognitive states from their driving behavior. To accomplish this, we adopt a data-driven approach and train a recurrent neural network to infer impulsivity and inhibitory control from recent driving behavior. The network is trained on a population of human drivers to infer impulsivity and inhibitory control from recent driving behavior. Using data collected from a high-fidelity vehicle motion simulator experiment, we demonstrate the ability to deduce these factors from driver behavior. We then use these inferred factors to determine instantly whether or not to engage a driver safety interface. This approach was evaluated using leave-one-out cross validation using actual human data. Our evaluations reveal that our personalized driver safety interface that captures the cognitive profile of the driver is more effective in influencing driver behavior in yellow light zones by reducing their inclination to run through them.

Improvements in advanced driver safety assistance systems have the potential to save lives 1 , 2 . However, these safety systems could benefit from targeting the cause of individual drivers’ dangerous driving behavior, which is known to be affected by many different factors, including cognitive, social, and situational 3 , 4 , 5 . Among the cognitive factors that influence risky driving behavior are cognitive impulsivity , which is the tendency to act without thinking 6 , and inhibitory control , which is the ability to suppress goal-irrelevant stimuli and behavioral responses 7 . Risky driving has been associated with higher self-reported impulsivity 4 , 8 , 9 , 10 , 11 , and with poorer inhibitory control in relevant laboratory tasks 4 , 10 , 11 , 12 , 13 . A recent review has shown the relationship between impulsivity and speeding and other driving violations 14 . More recent work has emphasized that the relationship between impulsive processes and driving errors and violations is influenced by cognitive abilities and self-regulation 15 , 16 . Further, such effects are associated with both sensation seeking (a concept related to impulsivity) and age, with recent work demonstrating that higher sensation-seeking and younger age were predictive of the highest speed during driving on a virtual reality track 17 . These cognitive factors also influence individuals’ reactions to different types of interfaces 18 , 19 .

Paaver et al. 20 showed that even a brief classroom-style lesson on impulsivity and driving can prevent speeding. Although the significance of impulsivity and inhibitory control as risk factors for vehicle accidents has not yet been leveraged in ADAS interfaces, these concepts have been used to develop effective driver educational materials. While there are numerous driver safety interfaces available, there is a gap in the research regarding the influence of impulsivity and inhibitory control on drivers’ responses to these interfaces. More specifically, studies have not adequately explored how to tailor the deployment of these safety interfaces to individual drivers, taking into account their unique levels of impulsivity and inhibitory control. Such personalization is crucial, as it can determine the effectiveness of the interface in enhancing driver safety.

Thus, the efficacy of driver safety systems may vary due to individual differences in cognition. The design of human-machine interfaces (HMIs), with a focus on addressing specific cognitive characteristics, has the potential to enhance both their safety effectiveness and user acceptance 21 . Crucially, the ability to estimate cognitive characteristics from observed driver behavior lays the groundwork for more personalized and effective safety interventions.

Our goal is to build a driver safety system that leverages learned representations of individual drivers’ cognitive factors to personalize HMIs that result in safer driving outcomes. Such a system would allow us to fully separate the underlying reasons for personalization (i.e., the learned cognitive factors) from what specific HMI attributes are personalized as a result of those reasons. This approach, in turn, allows for the deployment of highly versatile safety systems - for instance, if a new HMI is developed, these can be integrated without additional re-training of the underlying representation. The neural representations of cognitive factors enable refinement of the estimated factors, as well as deployment of personalized safety intervention, at large scale.

In this paper, we present experimental evidence for how factors such as impulsivity and inhibitory control can influence people’s responses to driver safety interfaces and how the inference of such cognitive measures enables an approach for personalizing safety interfaces. We do so by constructing a neural network model that embeds driver behavior into a latent space that captures these factors; finally, we demonstrate the embedded representation’s utility for triggering the deployment of assistive driving interfaces targeted to inhibitory control and impulsivity. To our knowledge, we are the first to demonstrate driver assistance personalization in a high-fidelity simulator.

In this paper we contribute: (1) Experimental evidence of how impulsivity and inhibitory control relate to performance under different choices of driver safety systems on a new dataset collected in a large-scale, high-fidelity, driving simulator; (2) A neural network model capable of encoding individual cognitive factor differences based on recent driving behavior; and (3) A decision-making system capable of personalizing the activation of driver safety interface based on the inferred cognitive factors.

Related works

Our work is at the intersection of two active research areas: the role of cognitive factors in understanding driving behavior, and learning approaches that capture specific latent factors for HMIs.

Cognitive factors and driving behaviors Common approaches for assessing driving behavior commonly involve self-report surveys 22 , ticketed speeding violations 23 , or crash records 24 . While these measurements can be good indicators of risky driving behavior, self-report metrics such as these are not always reliable 25 , contain private information, and do not lend themselves to seamless integration into preventative use with drivers. Other studies have shown driving characteristics can be estimated by measuring reactions to predetermined unsafe events in a simulated driving task 12 .

Our work provides a comprehensive general approach (Fig. 1 ) to inferring latent cognitive factors from driving behavior logs via a neural network encoder, and uses a high-fidelity driving motion simulator where behavior is closer to real-world vehicles than in lower-fidelity simulators (e.g., bench set up with a steering wheel) (Fig. 3 c).

A conceptual overview of our framework. Latent factors embed cognitive measures from the driving behavior, and used to inform HMI choice(dashed lines). Solid line marked the observable driving behavior and personalized HMI.

In addition to measuring driving behavior, researchers often measure impulsivity and other behavioral and cognitive factors via tests and questionnaires 26 , 27 , 28 , 29 . However, for these cognitive factors to effectively enhance vehicle safety systems, they should be estimated in a scalable way and applied to the development of personalized assistive interfaces within vehicles. In our work, we adopt a data-driven approach to train a neural network model that estimates cognitive factors from driving behavior (as opposed to relying on tests and questionnaires) thereby lending itself to deployment at scale. This could lead to more accurate information about drivers and further lead to effective intervention design and deployment criteria.

Learning Latent Factors for Human-Machine Interfaces Since an intelligent vehicle is a robotic system, our approach also relates to efforts in personalizing interactions between humans and robots or other machines. Prior work in machine learning for HMIs and human-robot teaming has focused on various human-robot interaction modalities such as driver monitoring, optimal shared control laws, and design of assistive robot behaviors (see e.g. 30 , 31 , 32 , 33 ). However, these approaches for human-robot interactions typically do not explicitly consider individual differences in cognitive factors and therefore fall under the category of a “one-size-fits-all” design.

The same is true for modern-day driver assistance systems such as lane-departure warnings or forward-collision warnings. Typical interventions issued by such systems depend on an individual’s state and action history and manifest as corrections of unsafe or suboptimal human actions generated from a policy learned from a desired set of behaviors required of the system 34 . Such approaches have been found to over-fit to the average-case behavior of individuals in a population, leading to incorrect inference of the human’s state and poor generalizability 35 , 36 . Given both the safety risks and the high degree of individual variation in factors like impulsivity and inhibitory control, over-fitting can have potentially dire consequences for drivers 37 . Recent work has shown that learning latent representations summarizing human behavior can improve teaming and interaction with the human. For instance, work on dialog systems 38 , recommender systems 39 , 40 , and intent recognition for products and motion 41 , 42 have demonstrated that latent representations are capable of better predicting the user’s need for a given intervention and their reaction to that intervention. We posit that using this representation as a basis for deciding whether to interact and which modes of interaction to use should improve safety over “one-size-fits-all” decision schemes.

In this paper, we explore how to effectively personalize HMIs based on people’s impulsivity and inhibitory control. We posit that latent factors such as impulsivity and inhibitory control can be inferred in an automated manner from driving behavior and can inform choices of interactions with the drivers to benefit them at a large scale.

Computational model

We now proceed to describe our computational approach for encoding latent cognitive factors. The resulting neural network distills a human driver’s recent driving history down to a low-dimensional parameter space whose structure can be easily shaped via multiple cognitive measures in a semi-supervised manner. The model we use includes a context encoder whose input is a time-receding, fixed-window trajectory of driving behavior in a scenario and whose output is a low-dimensional latent vector. This latent representation is then coupled with a separate decision-making module that takes this latent vector as input and outputs a decision at each decision time-step; for instance, whether or not to present a particular HMI to the driver at the current time-step. The architecture is shown in Fig.  2 , with further details in the “ supplemental information ”. As a result of experimentation, we found that a two-dimensional latent vector provided sufficient capacity to capture relevant cognitive factors, yet allow direct interpretation of the learned trends in the representation without possible distortions introduced by dimensionality reduction schemes (e.g. t-distributed Stochastic Neighbor Embedding 43 ).

The context encoder is represented as a long short-term memory (LSTM) recurrent neural network 44 , \(q_{\psi }(z \mid \tau )\) , and defines the probability of latent vector z given a past trajectory \(\tau\) of the driver.

The hidden layer h is fed into two linear layers that output the mean and log-variance of the latent encoding 45 .

As driving actions do not directly relate to psychological traits, we leverage contrastive learning 46 , 47 to encourage the latent representation to conform to measured cognitive factors (we introduce the specific factors we use in the Results section). As decisions should be based on more than one cognitive factor, we consider our cognitive factor target to be a vector.

The context encoding model transforms a driver’s past driving history \(\tau\) to a latent vector z , and uses a decoder network \(p_{\theta }(a|z)\) to predict the driver’s action a at the current time-step. We set up the loss terms to encourage z to capture both the individual’s cognitive factors and reconstruction of driver actions, with the factors allowing for the downstream decision-making module to have awareness of any time-independent factors inherent to the individual driver, as well as driver actions allowing for awareness of the behaviors in a given situation. Any scene context information present in \(\tau\) will indirectly manifests in z through \(q_{\psi }(z \mid \tau )\) . Thus, we expect a weak dependence of predicted driver action on scene context. The overall loss used to train the encoder consists of three components:

\(L_1(a, z; \theta ) = -\mathbb {E}_z \log p_{\theta }(a \vert z)\) is the expected negative log likelihood of action a under the model (reconstruction loss) induced by the conditional distribution p over z , where z characterizes driving behavior up to time t and \(\theta\) represents the parameters of the action decoder network.

\(L_2(z,y;\psi)\) , a contrastive loss supervised using a vector of cognitive factor targets y 48 . For continuous-valued cognitive measures, this loss is

where \(\mathcal {Z}\) represents a training samples batch, where each independently-sampled \(z, z' \in \mathcal {Z}\) is a \(\vert Z \vert\) -dimensional latent vector induced by the LSTM context encoder with parameters \(\psi\) , \(y_{z}\) is a vector of batch-normalized cognitive measures associated with z , \(\ell (z, z')\) is a measure associated with two vectors z and \(z'\) (which we choose as their Euclidean distance, i.e.  \(\Vert z - z'\Vert\) ), and \(\epsilon\) controls the magnitude of dissimilarity of y -values in z -space, where a larger \(\epsilon\) enforces higher separation of \(\Vert z - z'\Vert\) for fixed \(\Vert y_{z} - y_{z'}\Vert\) .

\(L_3(z) = D_{KL}(q_{\psi }(z \mid \tau )\vert \mathcal {N}(0,I))\) , a Kullback-Leibler (KL)-regularization loss for the distribution of z , e.g. as in 49 , 50 . \(\mathcal {N}(0, I)\) is the unit-normal distribution of appropriate dimension.

These terms are combined into an overall training loss:

where \(\alpha _1\) , \(\alpha _2\) , and \(\alpha _3\) are the respective loss coefficients.

Overall system architecture, including context encoder, decoder for future state and action prediction, outputs of cognitive measures, and latent factors used for HMI selection and decision-making.

HMI Decision-Making : We evaluate the utility of the inferred latent factors model by marrying it with a decision rule for selecting the activation of the HMI. The decisions are defined via a simple classifier whose inputs are the inferred latent factors. The classifier is trained to optimize a criterion for HMI selection within the training data. We take the criterion for classification to be the difference in average speed between two conditions, with and without HMI, when the yellow light is active, (averaged across trajectories for a single subject). This criterion reflects the speed reduction induced in the subject when an HMI is presented to the driver. Therefore, for each subject, we have a single regression target and the decision maker is trained to map the latent factors inferred from that subject’s trajectory snippets around yellow light transitions to the corresponding regression target; essentially learning a many-to-one function. We use Support Vector Regression 51 with a polynomial kernel as our decision model.

Behavioral experiment

Our motion-simulator driving experiment was designed to address the following hypotheses:

People with different levels of cognitive factors should exhibit different driving behaviors.

People with different levels of cognitive factors should respond differently to HMIs.

Our model should infer individual differences in cognitive factors from driving behavior data.

When using our model of inferred cognitive factor differences to choose HMIs, and those choices should result in lower speeds when passing through traffic lights.

The goal of our experiments is to validate H1–H4 by performing the following: (1) constructing candidate HMIs using a simple hand-crafted decision rule to time the deployment of the HMI for alerting the driver when they were approaching a traffic light to influence their driving behavior (specifics can be found in Fig.  3 e, (2) data collection of unassisted, baseline driving behaviors from a variety of types of individual drivers in a simulated road setting involving traffic lights, (3) data collection of driving behaviors with the HMI assistance schemes, (4) utilizing the collected data for training a model that encodes cognitive traits, as measured by cognitive assessments, from driving behavior.

In post-hoc, retrospective, analysis of the data, we conducted: (5) post-hoc evaluation of the HMI effect on driver behavior on approach to traffic lights, (6) post-hoc evaluation of our encoding of cognitive traits with respect to cognitive assessments, and (7) post-hoc evaluation of individuals’ behavioral response with the provided HMIs and using the models. Due to the logistical constraints associated with including more participants in our study, we designed our experiments to use a single pool of subjects to address each tasks (1)–(7). Hence, we conduct a randomized study involving each candidate HMIs without using the cognitive inference model. Data collected from the study was used to train a neural network-based cognitive inference model. The model was validated using a leave-one-out cross-validation scheme with respect to a chosen behavior statistic (mean speed during yellow light phase), in retrospect, by averaging over trials in which the experimental condition matched the model’s decision.

Participants

Thirty-nine Northern California-based drivers aged 18 and older ( Mean age = 49, Female = 16, Non-binary = 1 ) were recruited to participate in our study via Fieldwork, a global market research firm. Participants were only invited to participate if they held an active driver’s license, were not pregnant, and were vaccinated for COVID-19. Further details can be found in the recruitment section in the “ supplemental information ”.

Half of the participants were between the ages of 18–22, the other half were over the age of 65. We chose to recruit these two age groups because previous research has shown significant differences in their levels of impulsivity, inhibitory control, and risk propensity. 52 Additionally, these two populations are at heightened risk of vehicle accidents 11 . We opted to start with these groups to determine if there is a detectable signal. While age-related differences are not discussed in this paper, additional analyses can be found in the “ supplemental information ”. We did not find any significant differences between these two populations in our analysis.

This research was reviewed, approved, and done according to the human-subject guidelines set by the Western Institutional Review Board-Copernicus Group (WCG) IRB protocol number 20221727. Participants filled out a consent form prior to participation and were compensated $150 for their two-hour participation.

Exclusion criteria

Participants were excluded from the analysis if they did not complete the study. Of the 39 participants, 7 participants did not complete the driving trials due to motion sickness. Of the 32 remaining participants, the data of 5 participants was excluded from the analysis due to technical difficulties with the motion simulator during testing. The final sample size was therefore 27 individuals.

Driving task

As illustrated in Fig.  3 d, participants drove on a looped road with traffic lights that randomly changed from green to yellow at varying times of arrival of the vehicle at the traffic light, inducing a zone of dilemma 53 (See Fig.  3 d). Each loop consisted of eight traffic lights, four of which would turn yellow. The driving time during the laps summed over all participants was 540 min, which has been shown to be sufficient for driver behavior estimation in similar driving conditions 54 . We collected four driving trials (laps) where participants interacted with different prototype driver safety interfaces and two baseline driving laps without the interfaces.

Motion simulator

Participants completed the driving portion of the task using our vehicle motion simulator (See Fig.  3 c 55 , 56 , 57 ). The motion simulator has a cabin with two car seats, a steering wheel, and pedals that resemble the front half of a vehicle. The cabin is supported by a 6 DOF Motion Platform 58 and actuated based on the simulated vehicle movement in a virtual traffic environment. The cabin is surrounded by a projection screen that shows the virtual traffic environment. The CARLA simulator controls the virtual traffic and renders high-fidelity visuals by Unreal Engine 59 . A control booth behind the cabin allows the experimenter to control the scenarios and monitor participant safety. Communication between the experimenter and participant is enabled through a headset that is connected to a microphone and speakers in the cabin.

Driver safety interfaces

Two types of warning interfaces were used: a) transverse markings, projected on the road the car was driving; and b) a 2D yellow circle, projected as if it appeared in a heads-up display. Figure  3 e shows the virtual scenario and both interface types. The first two laps had no interfaces. The purpose of the first baseline lap was for the participant to get acclimated to the simulator and get a feel for how it drives and not included in analysis. For each interface, we also manipulated a trigger condition that determined whether or not it was displayed. Each interface was displayed either when the vehicle approached the traffic light (185 meters away) or when the upcoming traffic light changed from green to yellow.

Impulsivity: To assess participants’ impulsivity 60 , we used the BIS/BAS scale and the UPPS-P scale. The BIS/BAS was used to measure both the behavioral inhibition system (BIS) and the behavioral activation system (BAS), while the UPPS-P was used to account for different facets of impulsivity 61 .

Inhibitory Control: We used the Go-No Go task 62 and the Stop Signal task 63 , 64 to measure response inhibition. Stop Signal task measures were as described by Verbruggen et al. 64 .

Self-reported Driving Behavior: To assess participants’ road errors and violations, we used the Manchester Driver Behavior Questionnaire (DBQ) 22 . It includes four sub-scales that measure driver errors (such as failing to check your mirrors), lapses (such as turning the wrong blinker on), aggressive violations (such as racing other vehicles on the street), and ordinary violations (such as ignoring the speed limit on the highway).

Driving Behavior in the Motion Simulator: We also captured driving behavior as participants drove in the motion simulator. We recorded their driving speed, acceleration, and response to yellow traffic lights.

( a ) Participant overview. ( b ) Set of surveys used to measure latent cognitive factors. ( c ) An illustration of the driving motion simulator used for data collection. ( d ) Driving task course overview. For each lap, four of the lights would transition from green to yellow to red; these were randomly selected for each trial. ( e ). Set of HMIs presented in the driving task. Participants would complete two baseline laps to start. The first baseline lap was considered practice to get the driver acclimated to the simulator and was not included in analysis. After the second baseline lap, the four HMI trials were randomized in the order they were presented to the driver.

The effect of different HMI types on the mean speed during the lap. “D” refers to a distance-based trigger of the HMI, where the HMI is presented when the vehicle enters within 185 meters of the traffic light, and “L” refers to a light-based trigger, where the HMI is presented at the moment the traffic light turns from green to yellow. Each box plot displays the median, interquartile range (IQR), and outliers for the mean speed during these conditions.

We analyzed the relationship between various aspects of impulsivity, inhibitory control, driving behavior, and responses to HMIs designed to encourage drivers to slow down. We then analyzed the performance of our model in inferring participants’ cognitive factors and predicting whether they should interact with a HMI to support driving goals.

Relationship between cognitive factors and driving behavior (H1)

To understand the relationship between the different cognitive factors and driving behavior when reacting to the yellow lights, we conducted a Bayesian correlation analysis using the JASP software 65 . For the analysis, we used the data from all of the driving laps – including the ones with HMIs presented. A table with all of the Bayesian correlations can be found in the “ supplemental information ” document. As shown in these tables, a number of significant correlations emerged.

The self-reported ordinary violations (errors such as speeding or staying close to another vehicle you are behind) measured in the DBQ 22 were (mean = 12.778, sd = 1.819) positively correlated with the mean speed at the yellow light (r = 0.4, BF10 = 9693) and the maximum speed when the yellow was active light (r = 0.54 BF10 = \(1.141\times 10^9\) ), indicating that drivers who reported higher levels of ordinary violations from the DBQ (mean = 13.556, sd = 4.348) were more likely to speed through yellow lights in this task.

We found several correlations between the BIS/BAS measures and driving behavior. In particular, BAS Fun Seeking mean = 11.704, sd = 2.165 was positively correlated with the mean speed at the active yellow light (r = 0.473, BF10 = \(1.700\times 10^6\) ) and the maximum speed at the yellow light (r = 0.31, BF10 = 99.19). These data suggest that individuals who have a higher desire for new and exciting experiences may be more likely to take risks while driving, such as speeding through yellow lights. BAS Reward Responsiveness (mean = 16.741, sd = 1.740) was also positively correlated with the maximum speed at an active yellow light (r = 0.29, BF10 = 39.63).

Similar to the BIS/BAS measures, various correlations emerged using the UPPS-P subscales. For instance, UPPS-P Positive Urgency (mean = 6.630, was positively correlated with the maximum speed at an active yellow light (r = 0.28, BF10 = 26.93), and UPPS-P Sensation Seeking (mean = 11.000, sd = 3.150) was positively correlated with the mean speed at the active yellow light (r = 0.29, BF10 = 42.89) and the maximum speed at the active yellow light (r = 0.47, BF10 = \(1.540\times 10^6\) ). These results are consistent with the results found for BAS Fun Seeking (mean = 11.704, sd = 2.165) and BAS Reward Responsiveness (mean = 16.741. sd = 1.740), which provides further evidence that people who desire fun, new and thrilling experiences are more likely to speed and take risks when reacting to traffic lights.

Multiple correlations also emerged using the measures from the Stop Signal task. For instance, the reaction time on go trials with a response (goRT_all, mean = 618.148, sd = 170.594) was negatively correlated with the mean speed at the yellow light (r = \(-\)  0.38, BF10 = 2933). This suggests that drivers with longer reaction times may be more likely to slow down at yellow lights rather than speeding through them.

Finally, we also found numerous correlations using the Go/No-Go measures. Among the correlations, the average response time (gonogo_average_rt, mean = 382.981, sd = 49.262) was negatively correlated with the mean speed at the yellow light (r = \(-\)  0.46, BF10 = 352747) and the maximum speed at the yellow light (r = \(-\)  0.40, BF10 = 9205), which is consistent with the reaction time results from the Stop Signal task (e.g. goRT_all).

Interaction plots showing how the presence of the HMI interacted with different measures. The lines represent different levels of the measures: +1 SD (High), Mean, and -1 SD (Low). From left to right, the measures are: ( a ) BAS Fun Seeking: Motivation to find novel rewards spontaneously; ( b ) SSRT: Stop Signal Reaction Time: Ability to inhibit a response; ( c ) UPPS-P Positive Urgency: Tendency to act impulsively due to positive affect; d) DBQ Ordinary Violations: Self-reported ordinary driving violations.

Impact of cognitive factors on people’s driving responses to the interfaces (H2)

We fitted separate linear mixed models to predict each driving behavior measure based on interface condition (Table  1 ). All conditions demonstrated a statistically significant and negative effect on the mean speed during the lap, as depicted in Fig.  4 .

To further understand how different factors affect drivers’ responses to HMI, we conducted a linear mixed models (LMM) analysis, using multiple LMMs to examine the effects of various factors, including the presence or absence of HMI ( HMI_presence ) and their potential interactions. Participant ID was used as a random effect to account for individual differences. The lmer function in the lme4 R package 66 was employed for predicting mean speed when yellow lights were active based on these variables as

where \((1 | \text {Participant})\) denotes the random intercept. The models were fitted using the Restricted Maximum Likelihood (REML) estimation method, and the t-tests utilized Satterthwaite’s approximation method.

For detailed statistical outcomes, please refer to Table 1 . For a visual representation of some interaction effects, please see Fig.  5 , which complements the textual analysis. Here, we highlight some key findings that were noted to have a strong effect:

BIS/BAS : The BAS Fun Seeking subscale showed a significant main effect of HMI presence ( \(\beta = -11.14\) , \(SE = 4.64\) , \(t = -2.4\) , \(p = 0.018\) ) and a significant interaction with BAS Fun Seeking ( \(\beta = 0.9\) , \(SE = 0.39\) , \(t = 2.31\) , \(p = 0.023\) ), suggesting that individuals with higher BAS Fun Seeking scores drove faster in the presence of HMI compared to those with lower scores. The fixed effects accounted for 22.5% of the variance ( \(R^2_m = 0.225\) ), while the combined fixed and random effects accounted for 75% ( \(R^2_c = 0.75\) ).

UPPS-P : The Positive Urgency subscale revealed a significant main effect of HMI presence ( \(\beta = -8.71\) , \(SE = 2.66\) , \(t = -3.28\) , \(p = 0.0014\) ) and a significant interaction with Positive Urgency ( \(\beta = 1.23\) , \(SE = 0.38\) , \(t = 3.22\) , \(p = 0.0017\) ), indicating that individuals with higher Positive Urgency scores drove faster in the presence of HMI. The fixed effects explained 2.2% of the variance ( \(R^2_m = 0.022\) ), while the combined fixed and random effects explained 76.4% ( \(R^2_c = 0.764\) ).

Go/No-Go Measures : The Go/No-Go Average Response Time measure showed no significant main effect of HMI presence ( \(\beta = -0.85\) , \(SE = 6.88\) , \(t = -0.124\) , \(p = 0.9019\) ), but a significant effect of response time ( \(\beta = -0.072\) , \(SE = 0.028\) , \(t = -2.57\) , \(p = 0.0139\) ), indicating that longer response times were associated with slower driving speeds. The interaction between HMI presence and response time was not significant ( \(\beta = 0.00017\) , \(SE = 0.018\) , \(t = 0.010\) , \(p = 0.9922\) ). The fixed effects explained 20.4% of the variance ( \(R^2_m = 0.204\) ), while the combined fixed and random effects explained 74.0% ( \(R^2_c = 0.740\) ).

Stop Signal Measures : The SSRT measure showed no significant main effects of HMI presence ( \(\beta = 3.69\) , \(SE = 2.29\) , \(t = 1.61\) , \(p = 0.1094\) ) or SSRT ( \(\beta = 0.0145\) , \(SE = 0.0131\) , \(t = 1.11\) , \(p = 0.2724\) ). However, a significant interaction between HMI presence and SSRT was observed ( \(\beta = -0.0147\) , \(SE = 0.0073\) , \(t = -2.01\) , \(p = 0.0471\) ), suggesting that individuals with higher SSRTs drove slower in the presence of HMI compared to those with lower SSRTs. The fixed effects explained 1.0% of the variance ( \(R^2_m = 0.010\) ), while the combined fixed and random effects explained 75.1% ( \(R^2_c = 0.751\) ).

Manchester DBQ : The DBQ Ordinary Violations subscale showed a significant main effect of HMI presence ( \(\beta = -6.99\) , \(SE = 2.76\) , \(t = -2.53\) , \(p = 0.0128\) ) and a significant interaction with Ordinary Violations from the DBQ ( \(\beta = 0.473\) , \(SE = 0.194\) , \(t = 2.44\) , \(p = 0.0164\) ), suggesting that individuals with higher Ordinary Violations on the DBQ scores drove faster in the presence of HMI. The fixed effects explained 16.4% of the variance ( \(R^2_m = 0.164\) ), while the combined fixed and random effects explained 75.2% ( \(R^2_c = 0.752\) ).

Computational model results: inferring inhibitory control and HMI choice from driving behavior (H3, H4)

Given the various measures collected in the study, we used stepwise regression to select the most important features for training our neural-network based cognitive factor inference model. We combined forward selection, starting with an empty model and adding the predictor that produced the largest increase in model fit, with backward elimination, removing the predictor that produced the smallest decrease in model fit until no further improvement was observed. By following this process, the stepwise regression yielded a set of four cognitive factors to be used in the model: UPPS-P - Positive Urgency, BAS Fun Seeking, goRT_all, and DBQ - Ordinary violations.

We adopt the learning approach described to infer cognitive factors based on the subjects’ driving during the experiment. As mentioned earlier, we use the same data to perform training and evaluate model inference. In order to fairly conduct the evaluation, we perform leave-one-out cross-validation over the 27 subjects, averaging model performance over 10 random seeds, and capture properties of the embedding and the resulting training decision criteria performance. We include a complete description of the training and evaluation steps and further findings in the “ supplemental information ”. The distribution of the inferred latent factors is shown in Fig.  6 a. Qualitatively, we observe that fairly strong clustering has emerged for each of the cognitive factors which indicates the effectiveness of the contrastive learning approach is effective. To quantify this further, we show in Table  2 the fit between the distribution of the selected cognitive and the inferred latent factors. Since there is no direct or linear mapping assumed in contrastive learning, we probed the uniformity of the inferred embedding. We used the KL distance between the cognitive measures and the inferred factors’ distribution. The results demonstrate the model’s ability to infer several variables interest centered around impulsivity and inhibitory control.

We next proceed to probe the efficacy of the resulting latent space to inform HMI adaptation to the subjects. We use leave-one-out to evaluate the decision classifier based on the inferred latent factors. From the test subject’s data, we extract trajectory snippets around the yellow light transitions. The segment of the trajectory before the transition is fed into the context encoder to generate an inferred latent factor. The decision classifier subsequently consumes this latent factor to produce the HMI decision. In order to evaluate the interface selection decisions by the decision classifier we compare them to fixed interface choice chosen optimally for all participants (“one-size-fits-all” approach). We then measure the participants’ behavior in terms of our chosen behavior statistic (mean average speed when yellow light was active) for the selected HMI choice (the classifier’s decision) for the withheld subject averaged over the trials in which the experimental condition matched the decision classifiers output (thereby treating the experiment as a within-subject randomized trial study).

We measure performance of the decision scheme with three metrics: mean yellow light speed, reporting mean ( \(\mu\) ) and standard deviation ( \(\sigma\) ) aggregated over individuals, along with a Cohen’s \(\kappa\) and Balanced Accuracy scores that measure, respectively, accuracy of interface selection scheme under an unbalanced dataset. When leveraging the latent factors to decide on an HMI choice, we achieve a balanced accuracy of 56% and a Cohen Kappa of 0.145 in selecting the optimal HMI for the specific driver, as shown in Table  3 , resulting in a reduction of 0.59 m/s in the mean speed throughout the yellow-phase of the traffic light. Additionally, in Fig.  6 b (left), we code each of the latents generated from the trajectory snippets according to the decision module’s predictions. In conjunction with Fig.  6 b (right), the trajectory snippets for which deployment of the HMI was the decision, we see that the average speed after the yellow light transitions is lower, showing the effectiveness of the HMI decision scheme. The color distribution in the different plots demonstrate how the embedding space captures both the driver traits as captured in the questionnaires (a), and the chosen interface decision and resulting driver speed at the yellow light interval (b).

Example embedding and decision module result based on training data from a 27-subject fold; ( a ) Embedding of participants’ past history trajectories with contrastive loss based on four factors: goRT all, UPPS-P Positive Urgency, DBQ Ordinary Violations, and BAS Fun. Colors mark low (red) to high (blue) measures; ( b ) Trained decision boundary (left) and average speed during the yellow light phase conditioned on the decision scheme (right), plotted on the latent embedding space \(z_0\) , \(z_1\) . Each point represents a unique time window over which the inference was run.

Limitations

Despite efforts to include a large sample for our study, our sample size was relatively small. Some of this is due to participant motion sickness which at times was quite severe participation had to be ended early. We highlight that this is due to various logistical limitations such as the high costs involved in running a high-fidelity motion simulator study, COVID-related restrictions in recruiting human subjects and the need to implement in-lab social distancing measures, and the technological setup involved with a high-fidelity simulator. We also reiterate that some exclusion of participants was necessary, given our prioritization of a sound dataset over a larger one. While our sample size is in line with what others use in driving simulator studies 67 , 68 , or machine-learning driving behavior research 69 , 70 , it is still a relatively small population. We limited our experiment to older and younger participants thinking there would be a larger effect between these two groups. Although this effect did not appear related to age, we found an effect independent of age. Future work should expand the sample to a larger and more representative sample to look at the generalization of these findings. Since our analysis shows promise, a follow-up examining the algorithm’s decisions in real-time would be warranted.

As traffic accidents and violations frequently occur due to poor impulsivity and inhibitory control, it is important to create driver safety systems that can overcome these cognitive limitations on a personalized level. In this work, we present an approach to infer the individual’s latent factor, the use it to decide when it is or is not appropriate to show a driver safety interface depending on someone’s inferred impulsivity and inhibitory control.

To create this approach, we conducted a driving study using a high-fidelity motion simulator to understand how cognitive factors affect people’s responses to driver safety interfaces. Our study revealed that the prototype interfaces had differing effects on drivers based on their level of impulsivity, as indicated by multiple self-reported and behavioral metrics. In particular, we observed that drivers with lower levels of impulsivity tended to slow down when exposed to the interfaces, while drivers with higher levels of impulsivity exhibited the opposite response. Indeed, previous research has shown that impulsive drivers are more likely to run yellow lights 71 , although yellow lights were designed to warn drivers that they may need to slow down. Our study is the first to show that vehicle safety interfaces may also lead to unintended driving behavior responses for some drivers based on their impulsivity.

Leveraging the data collected in the study, we trained an LSTM network that can infer cognitive traits and, based on these, decide whether or not to employ a driver safety interface. The results show that our decision-making scheme can infer latent factors that are compact, correlate with cognitive measures associated with impulsivity, and can be used effectively to select driver interfaces to improve driver behavior, resulting in lower speed at the zone of dilemma of yellow lights. Although previous work has shown the relationship between cognitive factors such as impulsivity and driving behavior, this is the first time a model is proposed and examined so as to make driver safety recommendations based on cognitive factor inferences conditioned on the driver’s behavior.

The suggested approach lends itself to fleet-scale, online, in-vehicle optimization of the interaction with the driver across the population. If deployed in such a manner, overall improvements in driver safety interfaces may lead to safer roads overall.

Data availability

Data and material will be made available upon request by emailing the corresponding authors.

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This work has been funded by Toyota Research Institute. All authors work for and receive compensation from Toyota Research Institute.

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These authors contributed equally: Emily S. Sumner, Jonathan DeCastro, Jean Costa, Deepak E. Gopinath, Everlyne Kimani, Tiffany Chen and Guy Rosman.

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Emily S. Sumner, Jonathan DeCastro, Jean Costa, Deepak E. Gopinath, Everlyne Kimani, Shabnam Hakimi, Allison Morgan, Andrew Best, Hieu Nguyen, Daniel J. Brooks, Bassam ul Haq, Andrew Patrikalakis, Hiroshi Yasuda, Kate Sieck, Avinash Balachandran, Tiffany L. Chen & Guy Rosman

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E.S., J.D., J.C., D.G., E.K., S.H., A.M., A.B., D.B., H.Y., K.S., T.L.C., A.B., and G.R. designed the research. E.S., J.D., J.C., E.G., E.K., A.M., A.B., H.N., D.B., and H.Y. performed the research. J.D., D.G., H.N., B.H., A.P., and D.B. designed analytic tools. J.D., D.G., J.C., and E.K. analyzed the data. E.S., J.D., J.C., D.G., E.K., A.M., H.Y., T.L.C. and G.R. wrote the paper. All authors reviewed the manuscript.

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Understanding Science

How science REALLY works...

• Understanding Science 101
• Misconceptions

Scientific ideas can be tested through both experiments and other sorts of studies. Both provide important sources of evidence.

Misconception:  Experiments are a necessary part of the scientific process. Without an experiment, a study is not rigorous or scientific.

Correction:  Scientific testing involves more than just experiments. There are many valid ways to test scientific ideas and the appropriate method depends on many factors.  Read more about it.

Tactics for testing ideas

Experiments are one way to test some sorts of ideas, but science doesn’t live on experiment alone. There are many other ways to scientifically test ideas too…

What are experiments?

An experiment is a test that involves manipulating some factor in a system in order to see how that affects the outcome. Ideally, experiments also involve controlling as many other factors as possible in order to isolate the cause of the experimental results. Experiments can be simple tests set up in a lab, like rolling a ball down different inclines to see how the angle affects the rolling time. But large-scale experiments can also be performed out in the real world. For example, classic experiments in ecology involved removing a species of barnacles from intertidal rocks on the Scottish coast to see how that would affect other barnacle species over time. But whether they are large- or small-scale, performed in the lab or in the field, and require years or mere milliseconds to complete, experiments are distinguished from other sorts of tests by their reliance on the intentional manipulation of some factors and, ideally, the control of others.

Beyond experiments: Observational studies and natural experiments

Some aspects of the natural world aren’t manipulable, and hence can’t be studied with direct experiments. We simply can’t go back in time and introduce finches to three separate island groups to see how they evolve. We can’t move the planets around to see how their orbits would be altered by a new configuration. And we can’t cause volcanoes to erupt in order to investigate how they affect the ecosystems that surround them. Other times, it would be unethical to perform an experiment – for example, to investigate the effect of maternal alcohol consumption on babies.

In such cases, we can still figure out what expectations a hypothesis generates and make observations to test the idea. For example, we can’t actually experiment on distant stars in order to test ideas about which nuclear reactions occur within them, but we can test those ideas by building sensors that allow us to observe what forms of radiation the stars emit. Similarly, we can’t perform experiments to test ideas about what T. rex ate, but we can test those ideas by making detailed observations of their fossilized teeth and comparing those to the teeth of modern organisms that eat different foods. And of course, many ideas can be tested by both experiment and through straightforward observation. For example, we can test ideas about how chlorofluorocarbons interact with the ozone layer by performing chemical experiments in a lab and through observational studies of the atmosphere.

In some cases, we get lucky and are able to take advantage of a natural experiment . Natural experiments occur when the universe, in a sense, performs an experiment for us — that is, the relevant experimental set-up already exists, and all we have to do is observe the results. For example, researchers in England wanted to know if a program to improve the health and well-being of young children and their families was effective. Enrolling some children in the program and randomly excluding others to create a controlled experiment would be unethical. However, for other reasons, the program was rolled out in some geographic areas, but not in others. This set up a natural experiment that the researchers could take advantage of by comparing outcomes in families who received the program with outcomes in similar families who did not receive the program. Analyzing the results of this natural experiment suggested that the program helped children develop socially, encouraged families to build better learning environments for their kids, and discouraged poor parenting.

• Take a sidetrip

To learn how a natural experiment provides support for the  theory  of general relativity, take an advanced side trip to  Illuminating relativity: Experimenting with the stars .

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What happens when you can’t do an experiment? There are plenty of other ways to test scientific ideas. To see how observational studies factor into the process of science, check out these stories:

• Asteroids and dinosaurs
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• Here, we’ve talked about the different ways to test scientific ideas with evidence, but what makes a fair test? To learn more, take an advanced side trip to  Fair tests: A do-it-yourself guide .
• Visit the Visionlearning website for  advanced material on experimentation  and other methods of testing scientific ideas, like  description ,  comparison , and  modeling .

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Oxygen spillover from ruo2 to moo3 enhances activity and durability of ruo2 for acidic oxygen evolution.

Trade-off between activity and durability of acidic oxygen evolution reaction (OER) catalysts is of key concern in the field of electrocatalysis. RuO2 delivers good activity but displays poor stability due to the over-oxidation and consequent leachability of surface ruthenium species. Herein, we report an oxygen spillover strategy by designing RuO2/MoO3 catalysts with abundant and intimate interfaces to enable spillover of the reactive *O intermediate from RuO2 to MoO3 and thereby suppress over-oxidation and dissolution of RuO2, delivering both high activity and stability of Ru-based electrocatalysts. RuO2/MoO3 catalysts exhibited a significantly low overpotential of 167 mV at 10 mA cm−2 and negligible degradation of OER performance in 0.5 M H2SO4 within a period of 300 h. Experimental evidences (in-situ Raman spectra, cyclic voltammetry analysis, operando Fourier transformed infrared spectroscopy, etc.) and theoretical calculations demonstrated the occurrence of oxygen spillover from RuO2 to MoO3 and the subsequent participation of lattice oxygen of MoO3 instead of RuO2 for the steps of the release of oxygen, generation of oxygen vacancy and rehabilitation of lattice oxygen during acidic OER. This study provides a unique approach of oxygen spillover to solve the dilemma of activity and stability of Ru-based OER electrocatalysts.

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W. Gou, S. Zhang, Y. Wang, X. Tan, L. Liao, Z. Qi, M. Xie, Y. Ma, Y. Su and Y. Qu, Energy Environ. Sci. , 2024, Accepted Manuscript , DOI: 10.1039/D4EE02549K

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Researchers create new treatment and vaccine for flu and various coronaviruses

Team develops two nasal sprays -- an immune activator and a new vaccine -- to prevent virus transmission.

A team of researchers, led by the University of Houston, has discovered two new ways of preventing and treating respiratory viruses. In back-to-back papers in Nature Communications , the team -- from the lab of Navin Varadarajan, M.D. Anderson Professor of William A. Brookshire Chemical and Biomolecular Engineering -- reports the development and validation of NanoSTING, a nasal spray, as a broad-spectrum immune activator for controlling infection against multiple respiratory viruses; and the development of NanoSTING-SN, a pan-coronavirus nasal vaccine, that can protect against infection and disease by all members of the coronavirus family.

NanoSTING Therapeutic HIGHLIGHTS

• NanoSTING, a nasal spray, can prevent multiple respiratory viruses by activating the immune system and preventing infection from viruses. It can also protect against SARS-CoV-2 reinfection.
• A single intranasal dose of the NanoSTING has proven effective against strains of SARS-CoV-2 and the flu virus.
• NanoSTING is complementary to vaccines and enables cells to be in a heightened state of alert to prevent attack from respiratory viruses.

NanoSTING-NS Pan-coronavirus Vaccine HIGHLIGHTS

• UH researchers have developed NanoSTING-SN, a nasal vaccine that prevents transmission to the unvaccinated and fights multiple COVID variants.
• NanoSTING-SN provides the exciting potential towards a universal coronavirus vaccine and may end the cycle of onward transmission and viral evolution in immunocompromised people.
• Intramuscular vaccines prevent disease but are less efficient in preventing infections. NanoSTING-SN can provide improved protection against transmission for COVID variants and related sarbecoviruses.

NanoSTING is a special formula that uses tiny fat droplets to deliver an immune-boosting ingredient called cGAMP. This formula helps the body's cells stay on high alert to prevent attack from respiratory viruses.

"Using multiple models, the team demonstrated that a single treatment with NanoSTING not only protects against pathogenic strains of SARS-CoV-2 but also prevents transmission of highly transmissible variants like the Omicron variants," reports Varadarajan. "Delivery of NanoSTING to the nose ensures that the immune system is activated in the nasal compartment and this in turn prevents infection from viruses."

As the recent COVID19 pandemic illustrated, the development of off-the-shelf treatments that counteract respiratory viruses is a largely unsolved problem with a huge impact on human lives.

"Our results showed that intranasal delivery of NanoSTING, is capable of eliciting beneficial type I and type III interferon responses that are associated with immune protection and antiviral benefit," reports first author and postdoctoral associate, Ankita Leekha.

The authors further show that NanoSTING can protect against both Tamiflu sensitive and resistant strains of influenza, underscoring its potential as a broad-spectrum therapeutic.

"The ability to activate the innate immune system presents an attractive route to armoring humans against multiple respiratory viruses, viral variants and also minimizing transmission to vulnerable people," said Leekha. "The advantage of NanoSTING is that only one dose is required unlike the antivirals like Tamiflu that require 10 doses."

The mechanism of action of NanoSTING is complementary to vaccines, monoclonal antibodies and antivirals, the authors noted.

Nano STING-SN

Despite the successful implementation of multiple vaccines against SARS-CoV-2, these vaccines need constant updates due to viral evolution, plus the current generation of vaccines only offers limited protection against transmission of SARS-CoV-2.

Enter NanoSTING-SN, a multi-antigen, intranasal vaccine, that eliminates virus replication in both the lungs and the nostrils and has the ability to protect against multiple coronaviruses and variants.

"Using multiple preclinical models, the team demonstrated that the vaccine candidate protects the primary host from disease when challenged with highly pathogenic variants. Significantly, the vaccine also prevents transmission of highly transmissible variants like the Omicron variants to vaccine-naïve hosts," reports Varadarajan.

The authors further show that the nasal vaccine was 100% effective at preventing transmission of the Omicron VOCs to unvaccinated hosts.

"The ability to protect against multiple coronaviruses and variants provides the exciting potential towards a universal coronavirus vaccine," said Leekha. "The ability to prevent infections and transmission might finally end this cycle of onward transmission and viral evolution in immunocompromised people."

The research was conducted by a collaborative team at UH including Xinli Liu, College of Pharmacy and Vallabh E. Das, College of Optometry along with Brett L. Hurst of Utah State University and consultation from AuraVax Therapeutics, a spinoff from Varadarajan's Single Cell Lab at UH, which is developing NanoSTING.

Funding for the studies was provided by NIH (R01GM143243), Owens Foundation, and AuraVax Therapeutics.

• Infectious Diseases
• COVID and SARS
• Cold and Flu
• HIV and AIDS
• Immune System
• Human parainfluenza viruses
• Severe acute respiratory syndrome
• Nasal congestion
• Common cold
• Flu vaccine
• Yellow fever
• Immune system

Story Source:

Materials provided by University of Houston . Original written by Laurie Fickman. Note: Content may be edited for style and length.

Journal References :

• Ankita Leekha, Arash Saeedi, Monish Kumar, K. M. Samiur Rahman Sefat, Melisa Martinez-Paniagua, Hui Meng, Mohsen Fathi, Rohan Kulkarni, Kate Reichel, Sujit Biswas, Daphne Tsitoura, Xinli Liu, Laurence J. N. Cooper, Courtney M. Sands, Vallabh E. Das, Manu Sebastian, Brett L. Hurst, Navin Varadarajan. An intranasal nanoparticle STING agonist protects against respiratory viruses in animal models . Nature Communications , 2024; 15 (1) DOI: 10.1038/s41467-024-50234-y
• Ankita Leekha, Arash Saeedi, K M Samiur Rahman Sefat, Monish Kumar, Melisa Martinez-Paniagua, Adrian Damian, Rohan Kulkarni, Kate Reichel, Ali Rezvan, Shalaleh Masoumi, Xinli Liu, Laurence J. N. Cooper, Manu Sebastian, Courtney M. Sands, Vallabh E. Das, Nimesh B. Patel, Brett Hurst, Navin Varadarajan. Multi-antigen intranasal vaccine protects against challenge with sarbecoviruses and prevents transmission in hamsters . Nature Communications , 2024; 15 (1) DOI: 10.1038/s41467-024-50133-2

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Fentanyl’s deadly chemistry: How rogue labs make opioids

The illicit synthetic opioid industry is built on surprisingly simple chemistry. Here’s the science behind fentanyl, and how underworld “cooks” put it to work.

By DAISY CHUNG , LAURA GOTTESDIENER and DRAZEN JORGIC

Filed July 25, 2024, 9 a.m. GMT

Fentanyl Chemistry 101

Fentanyl is a synthetic drug. That means it’s not created from plants like marijuana or cocaine, but rather entirely from chemicals.

Fentanyl can be easy to make using compounds known as “precursors.” These are ready-made building blocks created from common industrial chemicals. Certain types of precursors are particularly prized by illicit fentanyl producers because they function as shortcuts to making the finished product. One senior U.S. administration official compared it to using “premixed brownie batter” versus trying to whip up a batch from scratch.

To make this harder for criminals to pull off, governments around the world strictly regulate a few of these key precursors. The U.S. government controls a couple of them as tightly as cocaine, methamphetamine and even finished fentanyl itself.

So, unscrupulous chemical sellers and illicit fentanyl producers have resorted to some creative chemistry to get around these strictures.

Understanding these chemistry tricks, it’s easy to see how illicit fentanyl producers have a big advantage. Every time a chemical is regulated, they can simply shift to an alternative to evade law enforcement.

It isn’t just the simple chemistry that assists illicit producers. Their supply chain is simple, too. Illicit fentanyl producers receive many of their chemicals the same way ordinary online shoppers receive all sorts of legal merchandise: by mail from China. A Reuters investigation published today reveals how easy it is to buy these chemicals .

Fentanyl is so potent, and each tablet contains such a tiny dose, that just a small amount of precursor chemicals can make a massive amount of illicit pills.

This means sellers can hide these chemicals in small boxes, often with false shipping labels.

Reuters purchased a dozen chemicals that independent chemists said could be used to make fentanyl. Many of these substances arrived in packages that listed the contents as cheap consumer goods: a doorknob, an adapter, hair accessories, typewriter parts.

With millions of packages flying around the world daily, authorities are hard-pressed to find the ones containing fentanyl chemicals.

Initial processing

Once illicit fentanyl makers get their hands on the necessary precursors, they can synthesize fentanyl in crude labs in less than a day.

A reporter traveled in February to Mexico’s Sinaloa state, home of the powerful Sinaloa Cartel, to speak with a freelance fentanyl producer about his craft. He operated in a poor neighborhood on the edge of the state capital Culiacán, an area controlled by the cartel that’s dotted with stash houses. Lookouts clutching two-way radios stood by the side of the dirt road leading to the house.

He said whipping up the drug was as easy as “making chicken soup.”

This cook, who left school at age 12, got his start as an assistant to another producer. Fentanyl recipes are prized assets, he said. His mentor was stingy with information and forbade him from taking notes. But within six months the apprentice had memorized all the steps and went into business for himself. He said he sourced his chemicals from local brokers, who took orders on WhatsApp and delivered within hours. He’s since exited the trade due to threats from the cartel chieftains, who have barred freelance producers from manufacturing fentanyl in Sinaloa.

Virtually all the illicit fentanyl trafficked to the U.S. is produced in Mexico, according to U.S. authorities. Historically, the state of Sinaloa has been the epicenter of production, though crime syndicates in other regions of Mexico have entered the trade too. Traffickers in Sinaloa operate open-air labs in rural areas such as forests or remote ranches. They’ve also set up ventilated laboratories inside apartments and houses in cities such as Culiacán.

The most common way of making illicit fentanyl at the moment is known as the one-pot Gupta method . It’s named after an Indian scientist, Dr. Pradeep Kumar Gupta, who helped develop a streamlined process for synthesizing medical-grade fentanyl, an analgesic used in operating rooms worldwide. Makers of street fentanyl have put their own spins on the technique. However, the name has stuck. (Gupta couldn’t be reached for comment.)

Gupta’s original method requires just three steps . The whole process takes place at room temperature and there’s no specialized lab equipment required.

His technique could also be used for the synthesis of thousands of different types of fentanyl analogs.

The Sinaloa cook told Reuters how he made fentanyl. His description of the process indicates that he was able take a shortcut and start with Step 3, according to Dr. Holmes, the Doane University chemist.

That’s because one of the chemicals the cook sourced from local brokers was something he called “El 400.” Holmes, who reviewed the cook’s process at Reuters’ request, said “El 400” is likely the immediate precursor 4-ANPP.

While that substance is tightly regulated internationally, some illegal producers can still find ways to obtain it, and thereby skip the first two synthesis steps in the three-step version of the Gupta method.

On the ground with a cook

Below is a depiction of how the cook performed Step 3 to yield fentanyl. (Reuters is withholding the names of some of the chemicals he used, to avoid providing detailed instructions and other information that could aid in synthesizing the drug.)

Post-production

The resulting paste is dried, ground into a fine powder, then carefully weighed and packaged into 1 kg bags for transport to a post-production laboratory.

In 2023, U.S. authorities seized nearly 116 million fentanyl pills, according to a National Institutes of Health-backed research paper published in May.

But hundreds of millions more likely ended up on American streets.

In a 2023 indictment targeting the sons of the jailed Sinaloa cartel kingpin, Joaquin “El Chapo” Guzman, U.S. officials estimated that $1,000 worth of fentanyl precursors can yield profits that are up to 800 times their original investment. With such economic incentives, said a U.S. federal investigator, few expect the flow of fentanyl to U.S. streets to stop any time soon.

Fentanyl Express: Deadly Chemistry

By Daisy Chung, Laura Gottesdiener and Drazen Jorgic

Additional reporting by Kristina Cooke

Graphics by Daisy Chung

Edited by Feilding Cage and Marla Dickerson

Dr. Andrea Holmes, professor of chemistry at Doane University in Nebraska

Dr. Alex J. Krotulski, director of toxicology and chemistry at the Center for Forensic Science Research and Education

The DEA’s Fentanyl Profiling Program

International Journal of Drug Policy

The International Narcotics Control Board

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