33 citations · 64 across the 28 of their papers we have counts for
8 papers · 1 filter
Towards Breaking the Learning System Wall Using Multimodal Tutoring Transcriptions
Danielle R. Thomas, Marie Cynthia Abijuru Kamikazi, Ashish Gurung +5
Past research using log data has faced the "learning system wall," whereby few methods exist for generalizing models of student learning across platforms. Increasingly, online lear…
Improving Hybrid Human-AI Tutoring by Differentiating Human Tutor Roles Based on Student Needs
Ashish Gurung, Ge Gao, Jordan Gutterman +6
Hybrid human-AI tutoring, where technology and humans jointly facilitate student learning, can be more beneficial than AI-only tutoring. However, preliminary evidence suggests that…
Coasting Through Class: Learning Opportunity Loss from Practice Avoidance During Individual Seatwork
Ashish Gurung, Jordan Gutterman, Danielle R. Thomas +3
Measures of disengagement provide insights into unproductive use of learning opportunities. Although measures of active disengagement, such as gaming the system and mind-wandering,…
Does the TalkMoves Codebook Generalize to One-on-One Tutoring and Multimodal Interaction?
Corina Luca Focsan, Marie Cynthia Abijuru Kamikazi, Tamisha Thompson +5
Accountable Talk theory has been widely adopted to analyze classroom discourse and is increasingly used to annotate tutoring interactions. In particular, the TalkMoves codebook, gr…
Modernizing Ground Truth: Four Shifts Toward Improving Reliability and Validity in AI in Education
Danielle R. Thomas, Conrad Borchers, Kirk P. Vanacore +2
Generative Artificial Intelligence (GenAI) is now widespread in education, yet the efficacy of GenAI systems remains constrained by the quality and interpretation of the labeled da…
Evaluating a Data-Driven Redesign Process for Intelligent Tutoring Systems
Qianru Lyu, Conrad Borchers, Meng Xia +4
Past research has defined a general process for the data-driven redesign of educational technologies and has shown that in carefully-selected instances, this process can help make…
LLM-based Multimodal Feedback Produces Equivalent Learning and Better Student Perceptions than Educator Feedback
Chloe Qianhui Zhao, Jie Cao, Jionghao Lin +1
Providing timely, targeted, and multimodal feedback helps students quickly correct errors, build deep understanding and stay motivated, yet making it at scale remains a challenge.…
Brief but Impactful: How Human Tutoring Interactions Shape Engagement in Online Learning
Conrad Borchers, Ashish Gurung, Qinyi Liu +3
Learning analytics can guide human tutors to efficiently address motivational barriers to learning that AI systems struggle to support. Students become more engaged when they recei…