A test bias is typified by a negative interpretation of an evaluation, such that it places a particular group of students at a disadvantage. These groups may include students from lower-income backgrounds, students of color, students who aren’t fluent in certain cultural traditions and customs, or students who aren’t proficient in the English language. To identify test bias, educators and test developers need to determine why a particular group of students tends to do worse or better compared to another group on a specific test. For instance, is it the characteristics of the test questions and design, the environment in which they’re tested, or the characteristics of that group members? With student populations in public schools becoming more diverse and tests assuming more central roles in assessing students’ individual success or access to opportunities, the matter of bias and ways to eliminate it has become even more important.

Test biases are divided into a few general categories. These include:

Construct-validity bias: This stands for whether a test appropriately assesses what it was designed to assess. For instance, on an intelligence test, students who’re learning English will likely face words they’ve not learned, and consequently, the test results might reflect their relatively poor English language skills instead of their intellectual or academic abilities.

Content-validity bias: This occurs when a test’s content is comparatively more difficult for a particular group of students than for others. It may occur when members of a particular student subgroup, such as several minority groups, haven’t received the same opportunity to learn the materials that are being tested. It may also occur when questions are worded in manners that are unknown to particular students because of cultural or linguistic differences or when scoring is unfair to a particular group. A sub-category of content-validity bias is item-selection bias. Item-selection bias refers to the utilization of individual test items that are more appropriate for the language and cultural experiences of one group.

Predictive-validity bias: This refers to the accuracy of a test in predicting how well a particular student group will do in the future. For instance, a test would be recognized as “unbiased” if it predicted future test and academic performance equally well for every group of students.

Test bias is closely associated with the issue of test fairness. Often, college admissions exams raise concerns about both test fairness and test bias, given their crucial roles in deciding access to institutions of higher education, particularly elite universities and colleges.