Educational tests are considered “Biased” if a test design, or the way results are interpreted and used, systematically disadvantages certain groups of students over others, such as students of color, students from lower-income backgrounds, students who are not proficient in the English language, or students who are not fluent in certain cultural customs and traditions. Identifying test bias requires that test developers and educators determine why one group of students tends to do better or worse than another group on a particular test. For example, is it because of the characteristics of the group members, the environment in which they are tested, or the characteristics of the test design and questions? As student populations in public schools become more diverse, and tests assume more central roles in determining individual success or access to opportunities, the question of bias—and how to eliminate it—has grown in importance.
There are a few general categories of test bias:
- Construct-validity bias (refers to whether a test accurately measures what it was designed to measure.)
- Content-validity bias (occurs when the content of a test is comparatively more difficult for one group of students than for others.)
- Predictive-validity bias (refers to a test’s accuracy in predicting how well a certain student group will perform in the future.)
Test bias is closely related to the issue of test fairness—i.e., do the social applications of test results have consequences that unfairly advantage or disadvantage certain groups of students? College-admissions exams often raise concerns about both test bias and test fairness, given their significant role in determining access to institutions of higher education, especially elite colleges and universities. For example, female students tend to score lower than males (possibly because of gender bias in test design), even though female students tend to earn higher grades in college on average (which possibly suggests evidence of predictive-validity bias).
Reform
As with measurement error, some degree of bias and unfairness in testing may be unavoidable. The inevitability of test bias and unfairness are among the reasons that many test developers and testing experts caution against making important educational decisions based on a single test result. The Standards for Educational and Psychological Testing—a set of proposed guidelines jointly developed by the American Educational Research Association, American Psychological Association, and the National Council on Measurement in Education—include a recommendation that “in elementary or secondary education, a decision or characterization that will have a major impact on a test taker should not automatically be made on the basis of a single score.
Given the fact that test results continue to be widely used when making important decisions about students, test developers and experts have identified a number of strategies that can reduce, if not eliminate, test bias and unfairness. A few representative examples include:
- Striving for diversity in test-development staffing, and training test developers and scorers to be aware of the potential for cultural, linguistic, and socioeconomic bias.
- Having test materials reviewed by experts trained in identifying cultural bias and by representatives of culturally and linguistically diverse subgroups.
- Ensuring that norming processes and sample sizes used to develop norm-referenced tests are inclusive of diverse student subgroups and large enough to constitute a representative sample.
- Eliminating items that produce the largest racial and cultural performance gaps, and selecting items that produce the smallest gaps—a technique known as “the golden rule.” (This particular strategy may be logistically difficult to achieve, however, given the number of racial, ethnic, and cultural groups that may be represented in any given testing population).
- Screening for and eliminating items, references, and terms that are more likely to be offensive to certain groups.
- Translating tests into a test taker’s native language or using interpreters to translate test items.
- Including more “performance-based” items to limit the role that language and word-choice plays in test performance.
- Using multiple assessment measures to determine academic achievement and progress, and avoiding the use of test scores, in exclusion of other information, to make important decisions about students.
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