228 citations · 528 across the 7 of their papers we have counts for
8 papers
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…
Computing Education in the Era of Generative AI
Paul Denny, James Prather, Brett A. Becker +7
The computing education community has a rich history of pedagogical innovation designed to support students in introductory courses, and to support teachers in facilitating student…
"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…
Assessing the Influencing Factors on the Accuracy of Underage Facial Age Estimation
Felix Anda, Brett A. Becker, David Lillis +2
Swift response to the detection of endangered minors is an ongoing concern for law enforcement. Many child-focused investigations hinge on digital evidence discovery and analysis.…