7 papers
Understanding Student Perceptions, Mistakes, and Debugging Approaches when Solving Natural Language Programming Tasks
Victor-Alexandru PÄdurean, Kaitlin Riegel, Gweneth Barbre +7
Learning to communicate with code-generating AI models is an emerging skill for novice programmers. One recent pedagogical approach, Prompt Problems, has students solve computation…
Exploring the Value of Diverse LLM Explanations in Introductory Programming
Seth Bernstein, Paul Denny, Juho Leinonen +4
Large Language Models (LLMs) have shown the potential to generate code explanations that surpass those of peers in quality, offering promising opportunities for computer science ed…
From Prompts to Propositions: A Logic-Based Lens on Student-LLM Interactions
Ali Alfageeh, Sadegh AlMahdi Kazemi Zarkouei, Daye Nam +9
Background and Context. The increasing integration of large language models (LLMs) in computing education presents an emerging challenge in understanding how students use LLMs and…
Probing the Unknown: Exploring Student Interactions with Probeable Problems at Scale in Introductory Programming
Paul Denny, Viraj Kumar, Stephen MacNeil +2
Introductory programming courses often rely on small code-writing exercises that have clearly specified problem statements. This limits opportunities for students to practice how t…
Breaking the Programming Language Barrier: Multilingual Prompting to Empower Non-Native English Learners
James Prather, Brent N. Reeves, Paul Denny +11
Non-native English speakers (NNES) face multiple barriers to learning programming. These barriers can be obvious, such as the fact that programming language syntax and instruction…
From Automation to Cognition: Redefining the Roles of Educators and Generative AI in Computing Education
Tony Haoran Feng, Andrew Luxton-Reilly, Burkhard C. Wünsche +1
Generative Artificial Intelligence (GenAI) offers numerous opportunities to revolutionise teaching and learning in Computing Education (CE). However, educators have expressed conce…