Speaker
Haruko Uematsu
Description
This study explores the feasibility of Chain-CAT, a Computer Adaptive Testing (CAT) approach integrated into the pre-post assessment paradigm in educational contexts. We propose increasing CAT frequency while shortening per-test duration and reducing the total number of items. Utilizing collateral information in CAT algorithms, specifically Bayesian-based proficiency estimation, facilitates efficient testing. A preliminary investigation involving FCI-CAT implementation and interviews suggests potential for Chain-CAT to accurately measure Newtonian mechanical thinking and aid in assessing conceptual understanding progression.
| How would you like to present your contribution? | Live in Kraków (time slot to be allotted based on the programme) |
|---|---|
| Target education level | University |
| Category | Formal Education |
Author
Haruko Uematsu
Co-authors
Jun-ichiro Yasuda
Kentaro Kojima
Michael M. Hull
Naohiro Mae
Taku Nakamura
