PERC 2022 Abstract Detail Page
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| Abstract Title: | Analyzing Multiple-Choice-Multiple-Response Items Using Item Response Theory |
|---|---|
| Abstract Type: | Contributed Poster Presentation |
| Abstract: | Multiple-choice-multiple-response (MCMR) items allow students to select as many responses as they think are correct to a given question stem. Using MCMR items can provide researchers and instructors with a richer and more complete picture of what students do and do not understand about a particular topic. Interpreting students' MCMR responses is more nuanced than it is for single-response items. Unfortunately, many typical analyses of data from multiple-choice tests assume dichotomously-scored items, which eliminates the possibility of incorporating the rich information from students' response patterns to MCMR items. We present a methodology for using a combination of item response theory models to analyze data from MCMR items. These methods could be applied to inform scoring models that incorporate partial credit for various response patterns. |
| Session Time: | Poster Session 3 |
| Poster Number: | III-34 |
| Contributed Paper Record: | Contributed Paper Information |
| Contributed Paper Download: | Download Contributed Paper |
Author/Organizer Information | |
| Primary Contact: |
Trevor I Smith Rowan University Glassboro, NJ 08028 |
| Co-Author(s) and Co-Presenter(s) |
Philip Eaton, Stockton University Suzanne White Brahmia, University of Washington Alexis Olsho, United States Air Force Academy Charlotte Zimmerman, University of Washington Andrew Boudreaux, Western Washington University |
