15 citations · 40 across the 7 of their papers we have counts for
7 papers
Beyond the Hype: A Comprehensive Review of Current Trends in Generative AI Research, Teaching Practices, and Tools
James Prather, Juho Leinonen, Natalie Kiesler +12
Generative AI (GenAI) is advancing rapidly, and the literature in computing education is expanding almost as quickly. Initial responses to GenAI tools were mixed between panic and…
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…
Prompts First, Finally
Brent N. Reeves, James Prather, Paul Denny +4
Generative AI (GenAI) and large language models in particular, are disrupting Computer Science Education. They are proving increasingly capable at more and more challenges. Some ed…
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…