EDM
AI Evaluation in Math Learning
Fri Jul 3, 10:45 AM–12:00 PM · North 202
★ Notable speakers
Justin Reich
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— Executive Director of MIT Teaching Systems Lab; author of 'Failure to Disrupt'; large-scale MOOC research (HarvardX/MITx); learning analytics; teacher preparation and tech policy
Ryan S. Baker
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— Educational data mining; BROMP observational protocol; student disengagement detection
Giora Alexandron
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— Learning analytics for MOOCs, fake-learner/cheating detection, AI in science education
Conrad Borchers
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— AI-supported self-regulated learning; intelligent tutoring systems; educational data mining; ordered network analysis
Kirk Vanacore
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— Learning analytics; educational data mining; causal inference in tutoring; AI annotation of learning discourse at scale
Danielle R. Thomas
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— Human-AI hybrid tutoring; educational equity; AI-augmented tutoring for students with disabilities
Jaclyn Ocumpaugh
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— Automated detection of student affect and engagement; co-developer of the BROMP field-observation protocol
Caitlin Mills
★
— Mind-wandering and attention during learning; eye-tracking; adaptive learning; educational data mining
EDM #17 | Long/Short Paper Session
4 talks in this session
A Causal Framework for Estimating Local Effects of On-Demand Tutoring
Kirk Vanacore, Danielle R Thomas, Digory Smith, Bibi Groot, Justin Reich
Identifying Items on Which Humans and Chatbots Diverge Using Differential Item Functioning
Licol Zeinfeld, Alona Strugatski, Ziva Bar-Dov, Ron Blonder, Shelley Rap
Multimodal LLM-based approach for detecting Disen-gagement from Task Goal (DTG) in Math problem solving
Nidhi Nasiar, Ryan S. Baker, Jaclyn Ocumpaugh, Zeyneb S. Sarioglan, Caitlin Mills
Simulating Learners' Task-Selection Strategies and System Constraints in Mastery Learning
Haley Noh, Aarna Chowdhary, Jeroen Ooge, Vincent Aleven, Conrad Borchers