Modeling exploration strategies to predict student performance within a learning environment and beyond
Author:
Affiliation:
1. Stanford University
2. Temple University
Publisher
ACM
Reference42 articles.
1. Contextual Slip and Prediction of Student Performance after Use of an Intelligent Tutor
2. Detecting Student Misuse of Intelligent Tutoring Systems
3. Developing a generalizable detector of when students game the system
4. Does Help Help? Introducing the Bayesian Evaluation and Assessment Methodology
5. Using learning analytics to assess students' behavior in open-ended programming tasks
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3. Protected Attributes Tell Us Who, Behavior Tells Us How: A Comparison of Demographic and Behavioral Oversampling for Fair Student Success Modeling;LAK23: 13th International Learning Analytics and Knowledge Conference;2023-03-13
4. A systematic review of empirical studies using log data from open‐ended learning environments to measure science and engineering practices;British Journal of Educational Technology;2022-11-28
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