13 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…
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…
AI-Generated Slides: Are They Good? Can Students Tell?
Juho Leinonen, Lisa Zhang, Arto Hellas
As generative AI (GenAI) tools become easily accessible, there is promise in using such tools to support instructors. To that end, this paper examines using GenAI to help generate…
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…
Teaching Language Models How to Code Like Learners: Conversational Serialization for Student Simulation
Charles Koutcheme, Juho Leinonen, Arto Hellas
Artificial students -- models that simulate how learners act and respond within educational systems -- are a promising tool for evaluating tutoring strategies and feedback mechanis…
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…