AIED
LLM-Driven Personalized Feedback and Knowledge Tracing in Programming Education
Fri Jul 3, 10:45 AM–12:00 PM · R2 (Auditorium Meeting 2)
Generative AI & Large Language Models Automated Feedback Knowledge Tracing Programming & CS Education
★ Notable speakers
Yong Yu
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— Web search, data mining, and ML; director of SJTU APEX Lab; SeqGAN and low-rank representation; ACM-ICPC championship coach
Peter Bühlmann
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— High-dimensional statistics, causal inference, statistical machine learning; lasso-based variable selection and stability selection
Andrew Lan
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— Machine learning and NLP for personalized learning, knowledge tracing, automated assessment
Weinan Zhang
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— Reinforcement learning, recommendation systems, computational advertising, generative models (SeqGAN, Mean Field MARL)
Frank Hopfgartner
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— Information retrieval, recommender systems, gamification, human-centered data science
Mariana Silva
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— Computer-based assessments; LLMs for automated grading; computing education technology at scale
AIED75 (TS) | Technical | Short-paper session
5 talks in this session
A Generalizable Approach for Real-Time Personalized Feedback in Open-Ended Learning Environments
Ethan Prihar, Hugues Saltini, Peter Bühlmann, Tanja Käser
DebugTA: An LLM-Based Agent for Simplifying Debugging and Teaching in Programming Education
Lingyue Fu, Datong Chen, Haowei Yuan, Qingyao Li, Weiwen Liu
Using LLMs for Knowledge Component-level Correctness Labeling in Open-ended Coding Problems
Zhangqi Duan, Arnav Kankaria, Dhruv Kartik, Andrew Lan
Scaffolding-First Constraint Design for LLM Tutors in Data-Science Problem Solving
Stefania Zourlidou, Shokooh Ebri, Tai Le Quy, Frank Hopfgartner
On Generating and Validating Erroneous Examples in CS1 using LLMs
Yuxuan Chen, Chenyan Zhao, Jacob Levine, Kangyu Feng, Max Fowler