Can test metadata help schools measure social-emotional learning?
Consortium for Policy Research in Education Knowledge Hub podcast
Social-emotional learning (SEL) competencies like self-efficacy and conscientiousness can be predictive of long-term academic achievement. But they can also be difficult to measure. In a new study led by NWEA’s James Soland, researchers investigated whether assessment metadata – the way students approach tests and surveys – can provide useful SEL data to schools and educators. Soland joins CPRE research specialist Tesla DuBois to discuss his findings, their implications, and the promise and limitations of student metadata in general.See More
Most previous research involving the study of response times has been conducted using locally developed instruments. The purpose of the current study was to examine the amount of rapid-guessing behavior within a commercially available, low-stakes instrument.
By: Steven Wise, J. Carl Setzer, Jill R. van den Heuvel, Guangming Ling
This integrative review examines the motivational benefits of computerized adaptive tests (CATs), and demonstrates that they can have important advantages over conventional tests in both identifying instances when examinees are exhibiting low effort, and effectively addressing the validity threat posed by unmotivated examinees.
By: Steven Wise
In this article, the authors explain how CAT provides a more precise, accurate picture of the achievement levels of both low-achieving and high-achieving students by adjusting questions as the testing goes along. The immediate, informative test results enable teachers to differentiate instruction to meet individual students’ current academic needs.
By: Edward Freeman
This study examined the utility of response time-based analyses in understanding the behavior of unmotivated test takers. For an adaptive achievement test, patterns of observed rapid-guessing behavior and item response accuracy were compared to the behavior expected under several types of models that have been proposed to represent unmotivated test taking behavior.
The growing presence of computer-based testing has brought with it the capability to routinely capture the time that test takers spend on individual test items. This, in turn, has led to an increased interest in potential applications of response time in measuring intellectual ability and achievement. Goldhammer (this issue) provides a very useful overview of much of the research in this area, and he provides a thoughtful analysis of the speed-ability trade-off and its impact on measurement.
By: Steven Wise
Whenever the purpose of measurement is to inform an inference about a student’s achievement level, it is important that we be able to trust that the student’s test score accurately reflects what that student knows and can do. Such trust requires the assumption that a student’s test event is not unduly influenced by construct-irrelevant factors that could distort his score. This article examines one such factor—test-taking motivation—that tends to induce a person-specific, systematic negative bias on test scores.
By: Steven Wise
This study examined the utility of response time‐based analyses in understanding the behavior of unmotivated test takers. For the data from an adaptive achievement test, patterns of observed rapid‐guessing behavior and item response accuracy were compared to the behavior expected under several types of models that have been proposed to represent unmotivated test taking behavior.