369 citations · 906 across the 16 of their papers we have counts for
10 papers · 1 filter
Digital Reading Materials and Religious Practice: Usage in Personal Study and Religious Education Courses
Teancum Price, Musa Blake, James Prather +1
Religion is an important part of many people's lives, with reading from religious texts being among the most common and important regular practices. Modern technology has changed t…
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…
Evaluating Contextually Personalized Programming Exercises Created with Generative AI
Evanfiya Logacheva, Arto Hellas, James Prather +2
Programming skills are typically developed through completing various hands-on exercises. Such programming problems can be contextualized to students' interests and cultural backgr…
Explaining Code with a Purpose: An Integrated Approach for Developing Code Comprehension and Prompting Skills
Paul Denny, David H. Smith, Max Fowler +3
Reading, understanding and explaining code have traditionally been important skills for novices learning programming. As large language models (LLMs) become prevalent, these founda…
Interactions with Prompt Problems: A New Way to Teach Programming with Large Language Models
James Prather, Paul Denny, Juho Leinonen +7
Large Language Models (LLMs) have upended decades of pedagogy in computing education. Students previously learned to code through \textit{writing} many small problems with less emp…
Prompt Problems: A New Programming Exercise for the Generative AI Era
Paul Denny, Juho Leinonen, James Prather +4
Large Language Models (LLMs) are revolutionizing the field of computing education with their powerful code-generating capabilities. Traditional pedagogical practices have focused o…
Promptly: Using Prompt Problems to Teach Learners How to Effectively Utilize AI Code Generators
Paul Denny, Juho Leinonen, James Prather +4
With their remarkable ability to generate code, large language models (LLMs) are a transformative technology for computing education practice. They have created an urgent need for…
"It's Weird That it Knows What I Want": Usability and Interactions with Copilot for Novice Programmers
James Prather, Brent N. Reeves, Paul Denny +6
Recent developments in deep learning have resulted in code-generation models that produce source code from natural language and code-based prompts with high accuracy. This is likel…
Programming Is Hard -- Or at Least It Used to Be: Educational Opportunities And Challenges of AI Code Generation
Brett A. Becker, Paul Denny, James Finnie-Ansley +3
The introductory programming sequence has been the focus of much research in computing education. The recent advent of several viable and freely-available AI-driven code generation…
Using Large Language Models to Enhance Programming Error Messages
Juho Leinonen, Arto Hellas, Sami Sarsa +4
A key part of learning to program is learning to understand programming error messages. They can be hard to interpret and identifying the cause of errors can be time-consuming. One…