AIED
Evaluating LLM-Based Feedback for Learning and Assessment
Wed Jul 1, 3:45 PM–5:00 PM · North 210
★ Notable speakers
Tom Mitchell
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— Machine learning; AI in education; knowledge components; large-scale online learning
Sidney D'Mello
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— Affective computing; affect and engagement detection in intelligent learning environments; mind-wandering during learning
Xiaoming Zhai
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— AI and machine learning for science education assessment; automated scoring; GenAI in STEM
Jionghao Lin
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— Dialogue-based intelligent tutoring, NLP for educational feedback, AI-driven tutor training
Andy Nguyen
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— AI in education; collaborative learning; multimodal data analytics; hybrid intelligence
Michail Giannakos
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— Multimodal learning analytics; technology-enhanced learning; interaction design for learning systems
AIED54 (HS) | Human-centered | Short-paper session
5 talks in this session
Chat-Based Support Alone May Not Be Enough: Comparing Conversational and Embedded LLM Feedback for Mathematical Proof Learning
Eason Chen, Sophia Judicke, Kayla Beigh, Xinyi Tang, Isabel Wang
Can LLMs Support Formative Assessment? Comparing LLM-Based and Teaching Assistant–Based Assessment in Programming Education
Eleni A. Dimitriadou, Sondre Aune Stokke, Sebastian Hegreberg, Andy Nguyen, Michail Giannakos
Using Learning Progressions to Guide AI Feedback for Science Learning
Xin Xia, Nejla Yuruk, Yun Wang, Xiaoming Zhai
Who Benefits from LLM-Generated Learning Support Messages? Causal Evidence on Treatment Effect Heterogeneity
Aylin Ozturk, Gati Aher, Tom Mitchell, Mustafa Kemal Birgin, Hüseyin Kayhan
A Matter of Perspective: Contrasting User and Subject-Matter Experts’ Sensemaking of LLM Feedback on Instructional Discourse
Chelsea Brown, Chelsea Chandler, Sandra Sawaya, Sidney Dmello