4 citations · 18 across the 13 of their papers we have counts for
6 papers · 1 filter
Uncovering Students' Inquiry Patterns in GenAI-Supported Clinical Practice: An Integration of Epistemic Network Analysis and Sequential Pattern Mining
Jiameng Wei, Dinh Dang, Kaixun Yang +9
Assessment of medication history-taking has traditionally relied on human observation, limiting scalability and detailed performance data. While Generative AI (GenAI) platforms ena…
Beyond Self-Regulated Learning Processes: Unveiling Hidden Tactics in Generative AI-Assisted Writing
Kaixun Yang, Yizhou Fan, Luzhen Tang +4
The integration of Generative AI (GenAI) into education is reshaping how students learn, making self-regulated learning (SRL) - the ability to plan, monitor, and adapt one's learni…
SCALEFeedback: A Large-Scale Dataset of Synthetic Computer Science Assignments for LLM-generated Educational Feedback Research
Keyang Qian, Kaixun Yang, Wei Dai +8
Using Large Language Models (LLMs) to give educational feedback to students for their assignments has attracted much attention in the AI in Education (AIED) field. Yet, there is cu…
Dean of LLM Tutors: A Framework for Automated Quality Review of AI-generated Feedback
Keyang Qian, Yixin Cheng, Rui Guan +8
Large language model (LLM) tutors are increasingly used to generate educational feedback, but existing research has focused mainly on feedback generation rather than feedback evalu…
The Agency Gap in AI-Supported Writing: How Reactive and Proactive Agent Designs Shape Multimodal Reasoning
Yueqiao Jin, Kaixun Yang, Roberto Martinez-Maldonado +2
Generative AI is becoming part of academic writing, but its educational value depends on how control is shared between learner and system. This study examined an agency gap: perfor…
Does the Prompt-based Large Language Model Recognize Students' Demographics and Introduce Bias in Essay Scoring?
Kaixun Yang, Mladen Raković, Dragan Gašević +1
Large Language Models (LLMs) are widely used in Automated Essay Scoring (AES) due to their ability to capture semantic meaning. Traditional fine-tuning approaches required technica…