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20212026
most citedAutomatic Generation of Programming Exercises and Code Explanations using Large Language Models

473 citations · 1.2k across the 39 of their papers we have counts for

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9 papers · 1 filter

cs.HC2026

Pulla: A Parsons Problem Tool for Fine-Grained Behavioral Tracing and Instructor-Facing Problem-Solving Analysis

Daniel Prol, Juho Leinonen, Arto Hellas +2

Existing Parsons problem tools primarily focus on correctness, indicating whether a student solved a problem, but providing limited visibility into the underlying problem-solving p…

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.HC2026

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…

cs.AI2026

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…

cs.AI2026

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…

cs.AI2026

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…

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.HC2026

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…

cs.CL2026

When Looks Do Not Lie: Discourse Structure Guided In-Context Learning for Faithful Diagram Generation

Evanfiya Logacheva, Arto Hellas, Tsvetomila Mihaylova +3

GenAI is widespread in educational applications; however, it is known to generate content with intrinsic and extrinsic hallucination. We introduce a novel method for ICL diagram ge…