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Peer reviewedConrad Borchers; Jeroen Ooge; Cindy Peng; Vincent Aleven – Grantee Submission, 2025
Personalized problem selection enhances student practice in tutoring systems. Prior research has focused on transparent problem selection that supports learner control but rarely engages learners in selecting practice materials. We explored how different levels of control (i.e., full AI control, shared control, and full learner control), combined…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Learner Controlled Instruction, Learning Analytics
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Direct linkGuerrero, Tricia Ann; Griffin, Thomas D.; Wiley, Jennifer – Grantee Submission, 2020
Past work has shown that generating explanations can improve both comprehension and metacomprehension outcomes. Although practice testing may sometimes improve comprehension, it is unclear if it affects metacomprehension (the ability to monitor one's understanding). The current study tested whether online homework activities involving practice…
Descriptors: College Students, Comprehension, Metacognition, Testing
Joshua M. Langberg; Melissa R. Dvorsky; Stephen J. Molitor; Elizaveta Bourchtein; Laura D. Eddy; Zoe R. Smith; Lauren E. Oddo; Hana-May Eadeh – Grantee Submission, 2017
Objective: To evaluate the effectiveness of 2 brief school-based interventions targeting the homework problems of adolescents with attention-deficit/hyperactivity disorder (ADHD)--the Homework, Organization, and Planning Skills (HOPS) intervention and the Completing Homework by Improving Efficiency and Focus (CHIEF) intervention, as implemented by…
Descriptors: Randomized Controlled Trials, Theory Practice Relationship, Intervention, Homework
