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Bridging Learnersourcing and AI: Exploring the Dynamics of Student-AI Collaborative Feedback Generation.

, , , , , and . CoRR, (2023)

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Exploring homophily in demographics and academic performance using spatial-temporal student networks., , , and . EDM, International Educational Data Mining Society, (2020)Logs or Self-Reports? Misalignment Between Behavioral Trace Data and Surveys When Modeling Learner Achievement Goal Orientation., , , , and . LAK, page 11-21. ACM, (2023)Influence on Judgements of Learning Given Perceived AI Annotations., and . L@S, page 221-231. ACM, (2024)What\textquotesingles In It for the Learners? Evidence from a Randomized Field Experiment on Learnersourcing Questions in a MOOC, , , and . Proceedings of the Eighth ACM Conference on Learning @ Scale, page 221-233. ACM, (June 2021)What's In It for the Learners? Evidence from a Randomized Field Experiment on Learnersourcing Questions in a MOOC., , , and . L@S, page 221-233. ACM, (2021)Bridging Learnersourcing and AI: Exploring the Dynamics of Student-AI Collaborative Feedback Generation., , , , , and . LAK, page 742-748. ACM, (2024)The Impact of Student Opt-Out on Educational Predictive Models., , and . LAK, page 411-420. ACM, (2019)Bridging Learnersourcing and AI: Exploring the Dynamics of Student-AI Collaborative Feedback Generation., , , , , and . CoRR, (2023)Building efficient incremental LL parser by augmenting LL table and threading parse tree.. ACM Southeast Regional Conference, page 269-270. ACM, (1995)A Simple and Efficient Incremental LL(1) parsing.. SOFSEM, volume 1012 of Lecture Notes in Computer Science, page 399-404. Springer, (1995)