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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
Peer reviewedDevika Venugopalan; Ziwen Yan; Conrad Borchers; Jionghao Lin; Vincent Aleven – Grantee Submission, 2025
Caregivers (i.e., parents and members of a child's caring community) are underappreciated stakeholders in learning analytics. Although caregiver involvement can enhance student academic outcomes, many obstacles hinder involvement, most notably knowledge gaps with respect to modern school curricula. An emerging topic of interest in learning…
Descriptors: Homework, Computational Linguistics, Teaching Methods, Learning Analytics
Direct linkS. Andrew Garbacz; Caleb Flack; Qi Huang; Anne Bowen; Elizabeth A. Stormshak; Laura Lee McIntyre – Grantee Submission, 2025
The purpose of this study was to examine the psychometric properties of the parent-report Short Form Positive Family Support Strengths and Needs Assessment (PFS-SaNA). The PFS-SaNA is designed to reduce the time and burden of collaborative mental health screening. Parents of 245 students in the Northwest completed the screener at third, fourth,…
Descriptors: Family Programs, Mental Health, Parents, Elementary School Students
