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Husni Almoubayyed; Stephen E. Fancsali; Steve Ritter – Grantee Submission, 2023
Recent research seeks to develop more comprehensive learner models for adaptive learning software. For example, models of reading comprehension built using data from students' use of adaptive instructional software for mathematics have recently been developed. These models aim to deliver experiences that consider factors related to learning beyond…
Descriptors: Middle School Students, Middle School Mathematics, Reading Comprehension, Intelligent Tutoring Systems
Husni Almoubayyed; Stephen E. Fancsali; Steve Ritter – Grantee Submission, 2023
Adaptive educational software is likely to better support broader and more diverse sets of learners by considering more comprehensive views (or models) of such learners. For example, recent work proposed making inferences about "non-math" factors like reading comprehension while students used adaptive software for mathematics to better…
Descriptors: Reading Ability, Computer Software, Mathematics Education, Intelligent Tutoring Systems
Husni Almoubayyed; Stephen E. Fancsali; Steve Ritter – International Educational Data Mining Society, 2023
Recent research seeks to develop more comprehensive learner models for adaptive learning software. For example, models of reading comprehension built using data from students' use of adaptive instructional software for mathematics have recently been developed. These models aim to deliver experiences that consider factors related to learning beyond…
Descriptors: Prediction, Models, Reading Ability, Computer Software