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Jordan M. Wheeler; Allan S. Cohen; Shiyu Wang – Journal of Educational and Behavioral Statistics, 2024
Topic models are mathematical and statistical models used to analyze textual data. The objective of topic models is to gain information about the latent semantic space of a set of related textual data. The semantic space of a set of textual data contains the relationship between documents and words and how they are used. Topic models are becoming…
Descriptors: Semantics, Educational Assessment, Evaluators, Reliability
Conijn, Rianne; Kahr, Patricia; Snijders, Chris – Journal of Learning Analytics, 2023
Ethical considerations, including transparency, play an important role when using artificial intelligence (AI) in education. Explainable AI has been coined as a solution to provide more insight into the inner workings of AI algorithms. However, carefully designed user studies on how to design explanations for AI in education are still limited. The…
Descriptors: Ethics, Writing Evaluation, Artificial Intelligence, Essays

Wilson, Mark; Adams, Raymond J. – Journal of Educational Statistics, 1993
A marginal maximum likelihood estimation algorithm is presented for the ordered partition model of M. Wilson that does not require the set of available responses to be fully ordered. The model and its estimation algorithm are illustrated in a comparison of alternative scoring schemes for open-ended science items. (SLD)
Descriptors: Algorithms, Comparative Analysis, Elementary Secondary Education, Equations (Mathematics)

Clauser, Brian E.; Margolis, Melissa J.; Clyman, Stephen G.; Ross, Linette P. – Journal of Educational Measurement, 1997
Research on automated scoring is extended by comparing alternative automated systems for scoring a computer simulation of physicians' patient management skills. A regression-based system is more highly correlated with experts' evaluations than a system that uses complex rules to map performances into score levels, but both approaches are feasible.…
Descriptors: Algorithms, Automation, Comparative Analysis, Computer Assisted Testing
Schnipke, Deborah L.; Reese, Lynda M. – 1997
Two-stage and multistage test designs provide a way of roughly adapting item difficulty to test-taker ability. All test takers take a parallel stage-one test, and, based on their scores, they are routed to tests of different difficulty levels in subsequent stages. These designs provide some of the benefits of standard computerized adaptive testing…
Descriptors: Ability, Adaptive Testing, Algorithms, Comparative Analysis