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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
Direct linkNatalie Brezack; Wynnie Chan; Mingyu Feng – Grantee Submission, 2024
This paper explores how learning analytics data provided by a math problem-solving educational technology platform informed 5th and 6th grade teachers' instructional decisions around socioemotional learning (SEL). MathSpring is an educational technology tool that provides teachers with data on students' effort, progress, and emotions while…
Descriptors: Social Emotional Learning, Mathematics Instruction, Teacher Attitudes, Comparative Analysis
Arslanbay, Goshnag; Ersanli, Ceylan Yangin – Journal on English Language Teaching, 2023
Data-Driven Learning (DDL) is a method for learning languages that involves analyzing language usage trends and finding patterns in language data, utilizing technology and statistics. One of the key benefits of DDL is that it allows students to focus on the most relevant and useful language data for their needs. Data-driven learning is an…
Descriptors: English (Second Language), English for Academic Purposes, Second Language Learning, Second Language Instruction
