PERC 2024 Abstract Detail Page
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| Abstract Title: | Designing a computerized adaptive testing chain for the Force Concept Inventory |
|---|---|
| Abstract Type: | Contributed Poster Presentation |
| Abstract: | The use of computer adaptive testing (CAT)-based assessment tests has inherent issues associated with the pre- and post-paradigm, such as the limited ability to observe the progression of student conceptual understanding throughout the course. To address these issues, we propose increasing the frequency of CAT-based assessments during the course, while reducing the test length per administration, thus decreasing the total number of test items during the course. The feasibility of this idea depends on how far the test length per administration can be reduced. To reach this goal, we designed a CAT algorithm, which we call Chain-CAT. This algorithm sequentially links the results of each CAT administration using collateral information. We analyzed the advantages of this algorithm by numerical simulations. Although preliminary, we found that collateral information significantly improved the test efficiency, and the total test length could be shorter than the pre-post method. |
| Session Time: | Poster Session 1 |
| Poster Number: | A03 |
| Contributed Paper Record: | Contributed Paper Information |
| Contributed Paper Download: | Download Contributed Paper |
Author/Organizer Information | |
| Primary Contact: |
Jun-ichiro Yasuda Nagoya University Nagoya, Non U.S. 464-8601 Phone: +81-52-789-5385 |
| Co-Author(s) and Co-Presenter(s) |
Michael M. Hull, University of Alaska Fairbanks Kentaro Kojima, Kyushu University |
Contributed Poster | |
| Contributed Poster: | Download the Contributed Poster |
