4 papers
THiNK: Can Large Language Models Think-aloud?
Yongan Yu, Mengqian Wu, Yiran Lin +1
Assessing higher-order thinking skills in large language models (LLMs) remains a fundamental challenge, especially in tasks that go beyond surface-level accuracy. In this work, we…
From Recall to Reasoning: Automated Question Generation for Deeper Math Learning through Large Language Models
Yongan Yu, Alexandre Krantz, Nikki G. Lobczowski
Educators have started to turn to Generative AI (GenAI) to help create new course content, but little is known about how they should do so. In this project, we investigated the fir…
Impact of Experiencing Misrecognition by Teachable Agents on Learning and Rapport
Yuya Asano, Diane Litman, Mingzhi Yu +4
While speech-enabled teachable agents have some advantages over typing-based ones, they are vulnerable to errors stemming from misrecognition by automatic speech recognition (ASR).…
Comparison of Lexical Alignment with a Teachable Robot in Human-Robot and Human-Human-Robot Interactions
Yuya Asano, Diane Litman, Mingzhi Yu +4
Speakers build rapport in the process of aligning conversational behaviors with each other. Rapport engendered with a teachable agent while instructing domain material has been sho…