2 citations · 4 across the 15 of their papers we have counts for
17 papers
Analyzing the Difficulty of Programming Assignments with Interpretable Knowledge Component Metrics
Tsvetomila Mihaylova, Jing Fan, Bita Akram +4
This research paper examines how Knowledge Components (KCs) - fine-grained concepts or skills required to solve programming tasks - can be used as interpretable signals for underst…
Automated Recommendation of Programming Learning Content Using Pattern-based Knowledge Components
Muntasir Hoq, Griffin Pitts, Zhangqi Duan +5
Introductory programming instruction relies on hands-on practice and short learning activities to support mastery of foundational concepts. Although many such learning resources ex…
The Effects of Structured LLM-Generated Feedback on Programming Assignment Performance
Tsvetomila Mihaylova, Evanfiya Logacheva, Arto Hellas +6
When programming students encounter errors in their code, compiler messages or static analysis output often provide limited guidance, particularly for novice programmers. Personali…
Retrieval-Augmented Tutoring for Algorithm Tracing and Problem-Solving in AI Education
Mragisha Jain, Tirth Bhatt, Griffin Pitts +6
Students learning algorithms often need support as they interpret traces, debug reasoning errors, and apply procedures across unfamiliar problem instances. In this paper, we presen…
An Explainable AI Assistant for Introductory Programming Education: Improving Feedback Reliability with Instructor-AI Collaboration
Muntasir Hoq, Griffin Pitts, Bradford Mott +6
Active learning is widely recognized as an effective approach for improving learning outcomes in introductory programming courses. However, insufficient instructional support often…
The Missing Evaluation Axis: What 10,000 Student Submissions Reveal About AI Tutor Effectiveness
Rose Niousha, Samantha Boatright Smith, Bita Akram +5
Current Artificial Intelligence (AI)-based tutoring systems (AI tutors) are primarily evaluated based on the pedagogical quality of their feedback messages. While important, pedago…
Personalized Worked Example Generation from Student Code Submissions Using Pattern-based Knowledge Components
Griffin Pitts, Muntasir Hoq, Peter Brusilovsky +4
Adaptive programming practice often relies on fixed libraries of worked examples and practice problems, which require substantial authoring effort and may not correspond well to th…
Spatiotemporal Link Formation Prediction in Social Learning Networks Using Graph Neural Networks
Ali Mohammadiasl, Bita Akram, Seyyedali Hosseinalipour +1
Social learning networks (SLNs) are graphical representations that capture student interactions within educational settings (e.g., a classroom), with nodes representing students an…
Democratizing Foundations of Problem-Solving with AI: A Breadth-First Search Curriculum for Middle School Students
Griffin Pitts, Kimia Fazeli, Tirth Bhatt +5
As AI becomes more common in students' everyday experiences, a major challenge for K-12 AI education is designing learning experiences that can be meaningfully integrated into exis…
Automated Program Repair of Uncompilable Student Code
Griffin Pitts, Aum Pandya, Darsh Rank +3
A significant portion of student programming submissions in CS1 learning environments are uncompilable, limiting their use in student modeling and downstream knowledge tracing. Tra…
Bringing Multi-Modal Multi-Task Federated Foundation Models to Education Domain: Prospects and Challenges
Kasra Borazjani, Naji Khosravan, Rajeev Sahay +2
Multi-modal multi-task (M3T) foundation models (FMs) have recently shown transformative potential in artificial intelligence, with emerging applications in education. However, thei…
Pattern-based Knowledge Component Extraction from Student Code Using Representation Learning
Muntasir Hoq, Griffin Pitts, Tirth Bhatt +4
Personalized instruction aims to provide learners with support that adapts to their individual knowledge and progress toward learning objectives. Discovering and tracing Knowledge…
Automated Identification of Logical Errors in Programs: Advancing Scalable Analysis of Student Misconceptions
Muntasir Hoq, Ananya Rao, Reisha Jaishankar +7
In Computer Science (CS) education, understanding factors contributing to students' programming difficulties is crucial for effective learning support. By identifying specific issu…
Facilitating Instructors-LLM Collaboration for Problem Design in Introductory Programming Classrooms
Muntasir Hoq, Jessica Vandenberg, Shuyin Jiao +5
Advancements in Large Language Models (LLMs), such as ChatGPT, offer significant opportunities to enhance instructional support in introductory programming courses. While extensive…
Privacy-Preserving Distributed Link Predictions Among Peers in Online Classrooms Using Federated Learning
Anurata Prabha Hridi, Muntasir Hoq, Zhikai Gao +4
Social interactions among classroom peers, represented as social learning networks (SLNs), play a crucial role in enhancing learning outcomes. While SLN analysis has recently garne…
Automated Knowledge Component Generation for Interpretable Knowledge Tracing in Coding Problems
Zhangqi Duan, Nigel Fernandez, Arun Balajiee Lekshmi Narayanan +5
Knowledge components (KCs) mapped to problems help model student learning, tracking their mastery levels on fine-grained skills thereby facilitating personalized learning and feedb…
The Transition from Centralized Machine Learning to Federated Learning for Mental Health in Education: A Survey of Current Methods and Future Directions
Maryam Ebrahimi, Rajeev Sahay, Seyyedali Hosseinalipour +1
Research has increasingly explored the application of artificial intelligence (AI) and machine learning (ML) within the mental health domain to enhance both patient care and health…