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cs.CY2026

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…

cs.CY2026

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…

cs.CY2026

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…

cs.CY2026

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…

cs.CY2026

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…

cs.CY2025

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…