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Integrating a Statistical Topic Model and a Diagnostic Classification Model for Analyzing Items in a Mixed Format Assessment
Journal article   Open access   Peer reviewed

Integrating a Statistical Topic Model and a Diagnostic Classification Model for Analyzing Items in a Mixed Format Assessment

Hye-Jeong Choi, Seohyun Kim, Allan S. Cohen, Jonathan Templin and Yasemin Copur-Gencturk
Frontiers in psychology, Vol.11, 579199
02/09/2021
DOI: 10.3389/fpsyg.2020.579199
PMCID: PMC7899971
PMID: 33633622
url
https://doi.org/10.3389/fpsyg.2020.579199View
Published (Version of record) Open Access

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Abstract

Selected response items and constructed response (CR) items are often found in the same test. Conventional psychometric models for these two types of items typically focus on using the scores for correctness of the responses. Recent research suggests, however, that more information may be available from the CR items than just scores for correctness. In this study, we describe an approach in which a statistical topic model along with a diagnostic classification model (DCM) was applied to a mixed item format formative test of English and Language Arts. The DCM was used to estimate students’ mastery status of reading skills. These mastery statuses were then included in a topic model as covariates to predict students’ use of each of the latent topics in their written answers to a CR item. This approach enabled investigation of the effects of mastery status of reading skills on writing patterns. Results indicated that one of the skills, Integration of Knowledge and Ideas, helped detect and explain students’ writing patterns with respect to students’ use of individual topics.
 Psychology diagnostic classification model mixed format test statistical topic models structural topic model text analysis

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