16 citations · 21 across the 7 of their papers we have counts for
8 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…
Optimizing Mastery Learning by Fast-Forwarding Over-Practice Steps
Meng Xia, Robin Schmucker, Conrad Borchers +1
Mastery learning improves learning proficiency and efficiency. However, the overpractice of skills--students spending time on skills they have already mastered--remains a fundament…
The Impact of Item-Writing Flaws on Difficulty and Discrimination in Item Response Theory
Robin Schmucker, Steven Moore
High-quality test items are essential for educational assessments, particularly within Item Response Theory (IRT). Traditional validation methods rely on resource-intensive pilot t…
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…
TutorUp: What If Your Students Were Simulated? Training Tutors to Address Engagement Challenges in Online Learning
Sitong Pan, Robin Schmucker, Bernardo Garcia Bulle Bueno +5
With the rise of online learning, many novice tutors lack experience engaging students remotely. We introduce TutorUp, a Large Language Model (LLM)-based system that enables novice…
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…