10 papers
Decomposing the Doer Effect in Programming Practice: Code Writing Stands Out Among Active Practice
Arun Balajiee Lekshmi Narayanan, Gillian Gold, Jordan Barria-Pineda +3
The "doer effect" suggests that actively doing practice activities is more strongly associated with learning outcomes than passively viewing content. In the doer effect literature,…
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…
Exploring the Effectiveness of Using LLMs for Automated Assessment of Student Self Explanations in Programming Education
Arun-Balajiee Lekshmi-Narayanan, Mohammad Hassany, Peter Brusilovsky
Worked examples are step-by-step solutions to problems in a specific domain, offered to students to acquire domain-specific problem-solving skills. The effectiveness of worked exam…
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…
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…
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 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…