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- W3045470237 abstract "Topic models were used to detect the latent thematic structure of examinees’ answers to constructed-response items. Results for two different topic models, latent Dirichlet allocation (LDA) and supervised LDA, were compared for their utility in detecting different latent thematic patterns in examinees’ responses on US History and Economics tests. LDA and sLDA results suggested both a four-topic model for the US History item and a three-topic model for the Economics item. For the US History item, Topic 1 consisted of use of everyday language and was negatively correlated with the rubric-based score. Topic 4, use of academic language focusing on government and politics, was positively correlated with the score. For the Economics test, Topic 3 consisted of use of technical vocabulary and had a positive correlation with item score. Complete results are discussed in the paper." @default.
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- W3045470237 date "2020-01-01" @default.
- W3045470237 modified "2023-10-01" @default.
- W3045470237 title "Topic Modeling of Constructed-Response Answers on Social Study Assessments" @default.
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- W3045470237 doi "https://doi.org/10.1007/978-3-030-43469-4_20" @default.
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