Examinees' Rapid-Guessing Patterns in Computerized Adaptive Testing for Interim Assessment: From Hierarchical Clustering
Abstract
Interim assessment is frequently administered via computerized adaptive testing (CAT), offering direct support to teaching and learning. This study attempted to fill a vital knowledge gap about the nuanced landscape of examinees' rapid-guessing patterns in CAT in the interim assessment context. We analyzed a sample of 146,519 examinees in Grades 1-8 who participated in a widely used CAT, using hierarchical clustering, a robust data science methodology for uncovering insights in data. We found that examinees' rapid-guessing patterns varied across item positions, content domains, chronological grades, examinee clusters, and examinees' overall rapid-guessing level on the test, suggesting a nuanced interplay between testing features and examinees' behavior. Our study contributes to the literature on rapid guessing in CATs for interim assessment, offering a comprehensive and nuanced pattern analysis and demonstrating the application of hierarchical clustering to process data analysis in testing.
- Publication:
-
arXiv e-prints
- Pub Date:
- August 2024
- DOI:
- 10.48550/arXiv.2408.11716
- arXiv:
- arXiv:2408.11716
- Bibcode:
- 2024arXiv240811716K
- Keywords:
-
- Statistics - Applications
- E-Print:
- preprint, NCME conference paper, 37 pages (excluding references)