Chained computerized adaptive testing for the Force Concept Inventory
Jun-ichiro Yasuda, Michael M. Hull, Naohiro Mae, Kentaro Kojima

TL;DR
This paper introduces Chain-CAT, a novel adaptive testing method that links multiple short assessments during a course to monitor student understanding more frequently and efficiently than traditional pre-post tests.
Contribution
The paper develops and evaluates Chain-CAT, a new adaptive testing algorithm that improves efficiency by linking sequential assessments using collateral information.
Findings
Collateral information enhances test efficiency.
Overall test length can be shorter than traditional pre-post assessments.
Chain-CAT achieves comparable efficiency with only 5-item tests repeated 9 times.
Abstract
Although conceptual assessment tests are commonly administered at the beginning and end of a semester, this pre-post approach has inherent limitations. Specifically, education researchers and instructors have limited ability to observe the progression of student conceptual understanding throughout the course. Furthermore, instructors are limited in the usefulness of the feedback they can give to the students involved. To address these challenges, we propose an alternative approach that leverages computerized adaptive testing (CAT) and increasing the frequency of CAT-based assessments during the course, while reducing the test length per administration, thus keeping or decreasing the total number of test items administered throughout the course. The feasibility of this idea depends on how far the test length per administration can be reduced without compromising the test accuracy and…
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Taxonomy
TopicsScientific Measurement and Uncertainty Evaluation · Mechanics and Biomechanics Studies · Aerospace and Aviation Technology
