369 citations · 820 across the 17 of their papers we have counts for
19 papers
Testing Our Foundations: Citation Trends, Errors, and Emerging Hallucinations in the Computing Education Literature
Paul Denny, Gweneth Barbre, Musa Blake +5
Accurate references are foundational to scholarly work, enabling verification, attribution, and systematic review. However, the rapid adoption of large language models has introduc…
Playsemble: Learning Low-Level Programming Through Interactive Games
Elliott Wen, Paul Denny, Andrew Luxton-Reilly +5
Teaching assembly programming is a fundamental component of undergraduate computer science education, yet many students struggle with its abstract and low-level concepts. Existing…
Interleaving Natural Language Prompting with Code Editing for Solving Programming Tasks with Generative AI Models
Victor-Alexandru Pădurean, Alkis Gotovos, Ahana Ghosh +5
Modern computing students often rely on both natural-language prompting and manual code editing to solve programming tasks. Yet we still lack a clear understanding of how these two…
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…
An Eye for an AI: Evaluating GPT-4o's Visual Perception Skills and Geometric Reasoning Skills Using Computer Graphics Questions
Tony Haoran Feng, Paul Denny, Burkhard C. Wünsche +2
CG (Computer Graphics) is a popular field of CS (Computer Science), but many students find this topic difficult due to it requiring a large number of skills, such as mathematics, p…
Anti-patterns in Students' Conditional Statements
Etienne Naude, Paul Denny, Andrew Luxton-Reilly
Producing high-quality code is essential as it makes a codebase more maintainable, reducing the cost and effort associated with a project. However, students learning to program are…
Integrating Natural Language Prompting Tasks in Introductory Programming Courses
Chris Kerslake, Paul Denny, David H Smith +4
Introductory programming courses often emphasize mastering syntax and basic constructs before progressing to more complex and interesting programs. This bottom-up approach can be f…
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…
Desirable Characteristics for AI Teaching Assistants in Programming Education
Paul Denny, Stephen MacNeil, Jaromir Savelka +2
Providing timely and personalized feedback to large numbers of students is a long-standing challenge in programming courses. Relying on human teaching assistants (TAs) has been ext…
Automating Personalized Parsons Problems with Customized Contexts and Concepts
Andre del Carpio Gutierrez, Paul Denny, Andrew Luxton-Reilly
Parsons problems provide useful scaffolding for introductory programming students learning to write code. However, generating large numbers of high-quality Parsons problems that ap…
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…
The Robots are Here: Navigating the Generative AI Revolution in Computing Education
James Prather, Paul Denny, Juho Leinonen +12
Recent advancements in artificial intelligence (AI) are fundamentally reshaping computing, with large language models (LLMs) now effectively being able to generate and interpret so…
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…
Many bioinformatics programming tasks can be automated with ChatGPT
Stephen R. Piccolo, Paul Denny, Andrew Luxton-Reilly +2
Computer programming is a fundamental tool for life scientists, allowing them to carry out many essential research tasks. However, despite a variety of educational efforts, learnin…
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…