Purpose: Students will work in groups to evaluate bias in scientific research and engineering projects and to develop guidelines for minimizing potential biases.

Procedural overview: After reading the Science News for Students article “Think you’re not biased? Think again,” students will discuss types of bias in scientific research and how to identify it. Students will then search the Science News archive for examples of different types of bias in scientific and medical research. Students will read the National Institute of Health’s Policy on Sex as a Biological Variable and analyze how this policy works to reduce bias in scientific research on the basis of sex and gender. Based on their exploration of bias, students will discuss the benefits and limitations of research guidelines for minimizing particular types of bias and develop guidelines of their own.

Approximate class time: 2 class periods




How Bias Affects Scientific Research student guide

Computer with access to the Science News archive

Interactive meeting and screen-sharing application for virtual learning (optional)

Directions for teachers:


One of the guiding principles of scientific inquiry is objectivity. Objectivity is the idea that scientific questions, methods and results should not be affected by the personal values, interests or perspectives of researchers. However, science is a human endeavor, and experimental design and analysis of information are products of human thought processes. As a result, biases may be inadvertently introduced into scientific processes or conclusions.

In scientific circles, bias is described as any systematic deviation between the results of a study and the “truth.” Bias is sometimes described as a tendency to prefer one thing over another, or to favor one person, thing or explanation in a way that prevents objectivity or that influences the outcome of a study or the understanding of a phenomenon. Bias can be introduced in multiple points during scientific research — in the framing of the scientific question, in the experimental design, in the development or implementation of processes used to conduct the research, during collection or analysis of data, or during the reporting of conclusions.

Researchers generally recognize several different sources of bias, each of which can strongly affect the results of STEM research. Three types of bias that often occur in scientific and medical studies are researcher bias, selection bias and information bias.

Researcher bias occurs when the researcher conducting the study is in favor of a certain result. Researchers can influence outcomes through their study design choices, including who they choose to include in a study and how data are interpreted. Selection bias can be described as an experimental error that occurs when the subjects of the study do not accurately reflect the population to whom the results of the study will be applied. This commonly happens as unequal inclusion of subjects of different races, sexes or genders, ages or abilities. Information bias occurs as a result of systematic errors during the collection, recording or analysis of data.

When bias occurs, a study’s results may not accurately represent phenomena in the real world, or the results may not apply in all situations or equally for all populations. For example, if a research study does not address the full diversity of people to whom the solution will be applied, then the researchers may have missed vital information about whether and how that solution will work for a large percentage of a target population.

Bias can also affect the development of engineering solutions. For example, a new technology product tested only with teenagers or young adults who are comfortable using new technologies may have user experience issues when placed in the hands of older adults or young children.

Want to make it a virtual lesson? Post the links to the Science News for Students article “Think you’re not biased? Think again,” and the National Institutes of Health information on sickle-cell disease. A link to additional resources can be provided for the students who want to know more. After students have reviewed the information at home, discuss the four questions in the setup and the sickle-cell research scenario as a class. When the students have a general understanding of bias in research, assign students to breakout rooms to look for examples of different types of bias in scientific and medical research, to discuss the Science News article “Biomedical studies are including more female subjects (finally)” and the National Institute of Health’s Policy on Sex as a Biological Variable and to develop bias guidelines of their own. Make sure the students have links to all articles they will need to complete their work. Bring the groups back together for an all-class discussion of the bias guidelines they write.

The setup

Assign the Science News for Students article “Think you’re not biased? Think again” as homework reading to introduce students to the core concepts of scientific objectivity and bias. Request that they answer the first two questions on their guide before the first class discussion on this topic. In this discussion, you will cover the idea of objective truth and introduce students to the terminology used to describe bias. Use the background information to decide what level of detail you want to give to your students.

As students discuss bias, help them understand objective and subjective data and discuss the importance of gathering both kinds of data. Explain to them how these data differ. Some phenomena — for example, body temperature, blood type and heart rate — can be objectively measured. These data tend to be quantitative. Other phenomena cannot be measured objectively and must be considered subjectively. Subjective data are based on perceptions, feelings or observations and tend to be qualitative rather than quantitative. Subjective measurements are common and essential in biomedical research, as they can help researchers understand whether a therapy changes a patient’s experience. For instance, subjective data about the amount of pain a patient feels before and after taking a medication can help scientists understand whether and how the drug works to alleviate pain. Subjective data can still be collected and analyzed in ways that attempt to minimize bias.

Try to guide student discussion to include a larger context for bias by discussing the effects of bias on understanding of an “objective truth.” How can someone’s personal views and values affect how they analyze information or interpret a situation?

To help students understand potential effects of biases, present them with the following scenario based on information from the National Institutes of Health:

Sickle-cell disease is a group of inherited disorders that cause abnormalities in red blood cells. Most of the people who have sickle-cell disease are of African descent; it also appears in populations from the Mediterranean, India and parts of Latin America. Males and females are equally likely to inherit the condition. Imagine that a therapy was developed to treat the condition, and clinical trials enlisted only male subjects of African descent. How accurately would the results of that study reflect the therapy’s effectiveness for all people who suffer from sickle-cell disease?

In the sickle-cell scenario described above, scientists will have a good idea of how the therapy works for males of African descent. But they may not be able to accurately predict how the therapy will affect female patients or patients of different races or ethnicities. Ask the students to consider how they would devise a study that addressed all the populations affected by this disease.

Before students move on, have them answer the following questions. The first two should be answered for homework and discussed in class along with the remaining questions.

1.What is bias?

In common terms, bias is a preference for or against one idea, thing or person. In scientific research, bias is a systematic deviation between observations or interpretations of data and an accurate description of a phenomenon.

2. How can biases affect the accuracy of scientific understanding of a phenomenon? How can biases affect how those results are applied?

Bias can cause the results of a scientific study to be disproportionately weighted in favor of one result or group of subjects. This can cause misunderstandings of natural processes that may make conclusions drawn from the data unreliable. Biased procedures, data collection or data interpretation can affect the conclusions scientists draw from a study and the application of those results. For example, if the subjects that participate in a study testing an engineering design do not reflect the diversity of a population, the end product may not work as well as desired for all users.

3. Describe two potential sources of bias in a scientific, medical or engineering research project. Try to give specific examples.

Researchers can intentionally or unintentionally introduce biases as a result of their attitudes toward the study or its purpose or toward the subjects or a group of subjects. Bias can also be introduced by methods of measuring, collecting or reporting data. Examples of potential sources of bias include testing a small sample of subjects, testing a group of subjects that is not diverse and looking for patterns in data to confirm ideas or opinions already held.

4. How can potential biases be identified and eliminated before, during or after a scientific study?

Students should brainstorm ways to identify sources of bias in the design of research studies. They may suggest conducting implicit bias testing or interviews before a study can be started, developing guidelines for research projects, peer review of procedures and samples/subjects before beginning a study, and peer review of data and conclusions after the study is completed and before it is published. Students may focus on the ideals of transparency and replicability of results to help reduce biases in scientific research.

Obtain and evaluate information about bias

Students will now work in small groups to select and analyze articles for different types of bias in scientific and medical research. Students will start by searching the Science News or Science News for Students archives and selecting articles that describe scientific studies or engineering design projects. If the Science News or Science News for Students articles chosen by students do not specifically cite and describe a study, students should consult the Citations at the end of the article for links to related primary research papers. Students may need to read the methods section and the conclusions of the primary research paper to better understand the project’s design and to identify potential biases. Do not assume that every scientific paper features biased research.

Student groups should evaluate the study or engineering design project outlined in the article to identify any biases in the experimental design, data collection, analysis or results. Students may need additional guidance for identifying biases. Remind them of the prior discussion about sources of bias and task them to review information about indicators of bias. Possible indicators include extreme language such as all, none or nothing; emotional appeals rather than logical arguments; proportions of study subjects with specific characteristics such as gender, race or age; arguments that support or refute one position over another and oversimplifications or overgeneralizations. Students may also want to look for clues related to the researchers’ personal identity such as race, religion or gender. Information on political or religious points of view, sources of funding or professional affiliations may also suggest biases.

Students should also identify any deliberate attempts to reduce or eliminate bias in the project or its results. Then groups should come back together and share the results of their analysis with the class.

If students need support in searching the archives for appropriate articles, encourage groups to brainstorm search terms that may turn up related articles. Some potential search terms include bias, study, studies, experiment, engineer, new device, design, gender, sex, race, age, aging, young, old, weight, patients, survival or medical.

If you are short on time or students do not have access to the Science News or Science News for Students archive, you may want to provide articles for students to review. Some suggested articles are listed in the additional resources below.

Once groups have selected their articles, students should answer the following questions in their groups.

1. Record the title and URL of the article and write a brief summary of the study or project.

Answers will vary, but students should accurately cite the article evaluated and summarize the study or project described in the article. Sample answer: We reviewed the Science News article “Even brain images can be biased,” which can be found at www.sciencenews.org/blog/scicurious/even-brain-images-can-be-biased. This article describes how scientific studies of human brains that involve electronic images of brains tend to include study subjects from wealthier and more highly educated households and how researchers set out to collect new data to make the database of brain images more diverse.

2. What sources of potential bias (if any) did you identify in the study or project? Describe any procedures or policies deliberately included in the study or project to eliminate biases.

The article “Even brain images can be biased” describes how scientists identified a sampling bias in studies of brain images that resulted from the way subjects were recruited. Most of these studies were conducted at universities, so many college students volunteer to participate, which resulted in the samples being skewed toward wealthier, educated, white subjects. Scientists identified a database of pediatric brain images and evaluated the diversity of the subjects in that database. They found that although the subjects in that database were more ethnically diverse than the U.S. population, the subjects were generally from wealthier households and the parents of the subjects tended to be more highly educated than average. Scientists applied statistical methods to weight the data so that study samples from the database would more accurately reflect American demographics.

3. How could any potential biases in the study or design project have affected the results or application of the results to the target population?

Scientists studying the rate of brain development in children were able to recognize the sampling bias in the brain image database. When scientists were able to apply statistical methods to ensure a better representation of socioeconomically diverse samples, they saw a different pattern in the rate of brain development in children. Scientists learned that, in general, children’s brains matured more quickly than they had previously thought. They were able to draw new conclusions about how certain factors, such as family wealth and education, affected the rate at which children’s brains developed. But the scientsits also suggested that they needed to perform additional studies with a deliberately selected group of children to ensure true diversity in the samples.


In this phase, students will review the Science News article “Biomedical studies are including more female subjects (finally)” and the NIH Policy on Sex as a Biological Variable, including the “guidance document.” Students will identify how sex and gender biases may have affected the results of biomedical research before NIH instituted its policy. The students will then work with their group to recommend other policies to minimize biases in biomedical research.

To guide their development of proposed guidelines, students should answer the following questions in their groups.

1. How have sex and gender biases affected the value and application of biomedical research?

Gender and sex biases in biomedical research have diminished the accuracy and quality of research studies and reduced the applicability of results to the entire population. When girls and women are not included in research studies, the responses and therapeutic outcomes of approximately half of the target population for potential therapies remain unknown.

2. Why do you think the NIH created its policy to reduce sex and gender biases?

In the guidance document, the NIH states that “There is a growing recognition that the quality and generalizability of biomedical research depends on the consideration of key biological variables, such as sex.” The document goes on to state that many diseases and conditions affect people of both sexes, and restricting diversity of biological variables, notably sex and gender, undermines the “rigor, transparency, and generalizability of research findings.”

3. What impact has the NIH Policy on Sex as a Biological Variable had on biomedical research?

The NIH’s policy that sex is factored into research designs, analyses and reporting tries to ensure that when developing and funding biomedical research studies, researchers and institutes address potential biases in the planning stages, which helps to reduce or eliminate those biases in the final study. Including females in biomedical research studies helps to ensure that the results of biomedical research are applicable to a larger proportion of the population, expands the therapies available to girls and women and improves their health care outcomes.

4. What other policies do you think the NIH could institute to reduce biases in biomedical research? If you were to recommend one set of additional guidelines for reducing bias in biomedical research, what guidelines would you propose? Why?

Students could suggest that the NIH should have similar policies related to race, gender identity, wealth/economic status and age. Students should identify a category of bias or an underserved segment of the population that they think needs to be addressed in order to improve biomedical research and health outcomes for all people and should recommend guidelines to reduce bias related to that group. Students recommending guidelines related to race might suggest that some populations, such as African Americans, are historically underserved in terms of access to medical services and health care, and they might suggest guidelines to help reduce the disparity. Students might recommend that a certain percentage of each biomedical research project’s sample include patients of diverse racial and ethnic backgrounds.

5. What biases would your suggested policy help eliminate? How would it accomplish that goal?

Students should describe how their proposed policy would address a discrepancy in the application of biomedical research to the entire human population. Race can be considered a biological variable, like sex, and race has been connected to higher or lower incidence of certain characteristics or medical conditions, such as blood types or diabetes, which sometimes affect how the body reponds to infectious agents, drugs, procedures or other therapies. By ensuring that people from diverse racial and ethnic groups are included in biomedical research studies, scientists and medical professionals can provide better medical care to members of those populations.

Class discussion about bias guidelines

Allow each group time to present its proposed bias-reducing guideline to another group and to receive feedback. Then provide groups with time to revise their guidelines, if necessary. Act as a facilitator while students conduct the class discussion. Use this time to assess individual and group progress. Students should demonstrate an understanding of different biases that may affect patient outcomes in biomedical research studies and in practical medical settings. As part of the group discussion, have students answer the following questions.

1. Why is it important to identify and eliminate biases in research and engineering design?

The goal of most scientific research and engineering projects is to improve the quality of life and the depth of understanding of the world we live in. By eliminating biases, we can better serve the entirety of the human population and the planet.

2. Were there any guidelines that were suggested by multiple groups? How do those actions or policies help reduce bias?

Answers will depend on the guidelines developed and recommended by other groups. Groups could suggest policies related to race, gender identity, wealth/economic status and age. Each group should clearly identify how its guidelines are designed to reduce bias and improve the quality of human life.

3. Which guidelines developed by your classmates do you think would most reduce the effects of bias on research results or engineering designs? Support your selection with evidence and scientific reasoning.

Answers will depend on the guidelines developed and recommended by other groups. Students should agree that guidelines that minimize inequities and improve health care outcomes for a larger group are preferred. Guidelines addressing inequities of race and wealth/economic status are likely to expand access to improved medical care for the largest percentage of the population. People who grow up in less economically advantaged settings have specific health issues related to nutrition and their access to clean water, for instance. Ensuring that people from the lowest economic brackets are represented in biomedical research improves their access to medical care and can dramatically change the length and quality of their lives.

Possible extension

Challenge students to honestly evaluate any biases they may have. Encourage them to take an Implicit Association Test (IAT) to identify any implicit biases they may not recognize. Harvard University has an online IAT platform where students can participate in different assessments to identify preferences and biases related to sex and gender, race, religion, age, weight and other factors. You may want to challenge students to take a test before they begin the activity, and then assign students to take a test after completing the activity to see if their preferences have changed. Students can report their results to the class if they want to discuss how awareness affects the expression of bias.

Additional resources

If you want additional resources for the discussion or to provide resources for student groups, check out the links below.

Additional Science News articles:

Even brain images can be biased

Data-driven crime prediction fails to erase human bias

What we can learn from how a doctor’s race can affect Black newborns’ survival

Bias in a common health care algorithm disproportionately hurts black patients

Female rats face sex bias too

There’s no evidence that a single ‘gay gene’ exists

Positive attitudes about aging may pay off in better health

What male bias in the mammoth fossil record says about the animal’s social groups

The man flu struggle might be real, says one researcher

Scientists may work to prevent bias, but they don’t always say so

The Bias Finders

Showdown at Sex Gap

University resources:

Project Implicit (Take an Implicit Association Tests)

Catalogue of Bias

Understanding Health Research