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Conrad 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
Rashmi Khazanchi; Daniele Di Mitri; Hendrik Drachsler – Journal of Computer Assisted Learning, 2025
Background: Despite educational advances, poor mathematics achievement persists among K-12 students, particularly in rural areas with limited resources and skilled teachers. Artificial Intelligence (AI) based systems have increasingly been adopted to support the diverse learning needs of students and have been shown to enhance mathematics…
Descriptors: Mathematics Achievement, Rural Areas, Artificial Intelligence, Individualized Instruction

Devika 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