16 citations · 20 across the 5 of their papers we have counts for
5 papers
Learning to Optimize Feedback for One Million Students: Insights from Multi-Armed and Contextual Bandits in Large-Scale Online Tutoring
Robin Schmucker, Nimish Pachapurkar, Shanmuga Bala +2
We present an online tutoring system that learns to provide effective feedback to students after they answer questions incorrectly. Using data from one million students, the system…
AI Mentors for Student Projects: Spotting Early Issues in Computer Science Proposals
Gati Aher, Robin Schmucker, Tom Mitchell +1
When executed well, project-based learning (PBL) engages students' intrinsic motivation, encourages students to learn far beyond a course's limited curriculum, and prepares student…
Automated Generation and Tagging of Knowledge Components from Multiple-Choice Questions
Steven Moore, Robin Schmucker, Tom Mitchell +1
Knowledge Components (KCs) linked to assessments enhance the measurement of student learning, enrich analytics, and facilitate adaptivity. However, generating and linking KCs to as…
Ruffle&Riley: Insights from Designing and Evaluating a Large Language Model-Based Conversational Tutoring System
Robin Schmucker, Meng Xia, Amos Azaria +1
Conversational tutoring systems (CTSs) offer learning experiences through interactions based on natural language. They are recognized for promoting cognitive engagement and improvi…
Ruffle&Riley: Towards the Automated Induction of Conversational Tutoring Systems
Robin Schmucker, Meng Xia, Amos Azaria +1
Conversational tutoring systems (CTSs) offer learning experiences driven by natural language interaction. They are known to promote high levels of cognitive engagement and benefit…