Examinees' Rapid-Guessing Patterns in Computerized Adaptive Testing for Interim Assessment: From Hierarchical Clustering

Fuente: arXiv
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Main Authors: Kaptur, Dandan Chen, Patton, Elizabeth, Rome, Logan
Format: Preprint
Published: 2024
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author Kaptur, Dandan Chen
Patton, Elizabeth
Rome, Logan
author_facet Kaptur, Dandan Chen
Patton, Elizabeth
Rome, Logan
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2408_11716
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Examinees' Rapid-Guessing Patterns in Computerized Adaptive Testing for Interim Assessment: From Hierarchical Clustering
Kaptur, Dandan Chen
Patton, Elizabeth
Rome, Logan
Applications
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.
title Examinees' Rapid-Guessing Patterns in Computerized Adaptive Testing for Interim Assessment: From Hierarchical Clustering
topic Applications
url https://arxiv.org/abs/2408.11716