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Large Language Models (LLMs) are revolutionizing the field of computing education with their powerful code-generating capabilities.
CodeWrite: Supporting Student-Driven Practice of Java. In Proceedings of the 42nd ACM Technical Symposium on Computer Science Education (Dallas, TX, USA) (SIGCSE ’11) . Association for Computing Machinery, NY, USA, 471–476
Paul Denny, Andrew Luxton-Reilly, Ewan Tempero, and Jacob Hendrickx. 2011 · 2011
Earlier work this paper cites.
Coderunner: A Tool for Assessing Computer Programming Skills
Richard Lobb and Jenny Harlow. 2016 · 2016
Earlier work this paper cites.
Many Small Programs in CS1: Usage Analysis from Multiple Universities. In 2019 ASEE Annual Conference & Exposition " . ASEE Conferences, Tampa, Florida, 1–13
Joe Michael Allen, Kelly Downey, Kris Miller, Alex Daniel Edgcomb, and Frank Vahid. 2019 · 2019
Earlier work this paper cites.
Compiler Error Messages Considered Unhelpful: The Landscape of Text-Based Programming Error Message Research. In Proceedings of the Working Group Reports on Innovation and Technology in Computer Science Education (Aberdeen, Scotland Uk) (ITiCSE-WGR ’19) . ACM, NY, NY, USA, 177–210
Brett A. Becker, Paul Denny, Raymond Pettit, Durell Bouchard, Dennis J. Bouvier, Brian Harrington, Amir Kamil, Amey Karkare, Chris McDonald, Peter-Michael Osera, Janice L. Pearce, and James Prather. 2019 · 2019
Earlier work this paper cites.
A Review of Research on Parsons Problems. In Proceedings of the Twenty-Second Australasian Computing Education Conference (Melbourne, VIC, Australia) (ACE’20) . Association for Computing Machinery, NY, USA, 195–202
Yuemeng Du, Andrew Luxton-Reilly, and Paul Denny. 2020 · 2020
Earlier work this paper cites.
Parsons Problems and Beyond: Systematic Literature Review and Empirical Study Designs. In Proceedings of the 2022 Working Group Reports on Innovation and Technology in Computer Science Education (Dublin, Ireland) (ITiCSE-WGR ’22) . Association for Computing Machinery, NY, USA, 191–234
Barbara J. Ericson, Paul Denny, James Prather, Rodrigo Duran, Arto Hellas, Juho Leinonen, Craig S. Miller, Briana B. Morrison, Janice L. Pearce, and Susan H. Rodger. 2022 · 2022
Earlier work this paper cites.
The Robots Are Coming: Exploring the Implications of OpenAI Codex on Introductory Programming. In Proceedings of the 24th Australasian Computing Education Conference (Virtual Event, Australia) (ACE ’22) . Association for Computing Machinery, NY, USA, 10–19
James Finnie-Ansley, Paul Denny, Brett A. Becker, Andrew Luxton-Reilly, and James Prather. 2022 · 2022
Earlier work this paper cites.
Automatic Generation of Programming Exercises and Code Explanations Using Large Language Models. In Proceedings of the 2022 ACM Conference on International Computing Education Research - Volume 1 (Lugano and Virtual Event, Switzerland) (ICER ’22) . Association for Computing Machinery, NY, USA, 27–43
Sami Sarsa, Paul Denny, Arto Hellas, and Juho Leinonen. 2022 · 2022
Earlier work this paper cites.
Solving Probability And Statistics Problems By Probabilistic Program Synthesis At Human Level And Predicting Solvability. In Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium: 23rd International Conference, AIED 2022, Durham, UK, July 27–31, 2022, Proceedings, Part II (Durham, United Kingdom). Springer-Verlag, Berlin, Heidelberg, 612–615
Leonard Tang, Elizabeth Ke, Nikhil Singh, Bo Feng, Derek Austin, Nakul Verma, and Iddo Drori. 2022 · 2022
Earlier work this paper cites.
StudentEval: A Benchmark of Student-Written Prompts for Large Language Models of Code
Hannah McLean Babe, Sydney Nguyen, Yangtian Zi, Arjun Guha, Molly Q Feldman, and Carolyn Jane Anderson. 2023 · 2023
Earlier work this paper cites.
Programming Is Hard - Or at Least It Used to Be: Educational Opportunities and Challenges of AI Code Generation. In Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1 (Toronto ON, Canada) (SIGCSE 2023) . Association for Computing Machinery, NY, USA, 500–506
Brett A. Becker, Paul Denny, James Finnie-Ansley, Andrew Luxton-Reilly, James Prather, and Eddie Antonio Santos. 2023 · 2023
Cited alongside, same era.
GPT-3 vs Object Oriented Programming Assignments: An Experience Report. In Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 1 (Turku, Finland) (ITiCSE 2023) . Association for Computing Machinery, NY, USA, 61–67
Bruno Pereira Cipriano and Pedro Alves. 2023 · 2023
Cited alongside, same era.
Chat Overflow: Artificially Intelligent Models for Computing Education - RenAIssance or ApocAIypse?. In Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 1 (Turku, Finland) (ITiCSE 2023) . Association for Computing Machinery, NY, USA, 3–4
Paul Denny, Brett A. Becker, Juho Leinonen, and James Prather. 2023a · 2023
Cited alongside, same era.
The Implications of Large Language Models for CS Teachers and Students. In Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 2 (Toronto ON, Canada) (SIGCSE 2023) . Association for Computing Machinery, NY, USA, 1255
Stephen MacNeil, Joanne Kim, Juho Leinonen, Paul Denny, Seth Bernstein, Brett A. Becker, Michel Wermelinger, Arto Hellas, Andrew Tran, Sami Sarsa, James Prather, and Viraj Kumar. 2023a · 2023
Closest in time.
Experiences from Using Code Explanations Generated by Large Language Models in a Web Software Development E-Book. In Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1 (Toronto ON, Canada) (SIGCSE 2023) . Association for Computing Machinery, NY, USA, 931–937
Stephen MacNeil, Andrew Tran, Arto Hellas, Joanne Kim, Sami Sarsa, Paul Denny, Seth Bernstein, and Juho Leinonen. 2023b · 2023
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On the Educational Impact of ChatGPT: Is Artificial Intelligence Ready to Obtain a University Degree?. In Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 1 (Turku, Finland) (ITiCSE 2023) . Association for Computing Machinery, NY, USA, 47–53
Kamil Malinka, Martin Peresíni, Anton Firc, Ondrej Hujnák, and Filip Janus. 2023 · 2023
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Conversing with Copilot: Exploring Prompt Engineering for Solving CS1 Problems Using Natural Language. In Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1 (Toronto ON, Canada) (SIGCSE 2023) . Association for Computing Machinery, NY, USA, 1136–1142
Paul Denny, Viraj Kumar, and Nasser Giacaman. 2023b · 2023
Cited alongside, same era.
My AI Wants to Know If This Will Be on the Exam: Testing OpenAI’s Codex on CS2 Programming Exercises. In Proceedings of the 25th Australasian Computing Education Conference (Melbourne, VIC, Australia) (ACE ’23) . Association for Computing Machinery, NY, USA, 97–104
James Finnie-Ansley, Paul Denny, Andrew Luxton-Reilly, Eddie Antonio Santos, James Prather, and Brett A. Becker. 2023 · 2023
Cited alongside, same era.
Studying the Effect of AI Code Generators on Supporting Novice Learners in Introductory Programming. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (Hamburg, Germany) (CHI ’23) . Association for Computing Machinery, NY, USA, Article 455, 23 pages
Majeed Kazemitabaar, Justin Chow, Carl Ka To Ma, Barbara J. Ericson, David Weintrop, and Tovi Grossman. 2023 · 2023
Cited alongside, same era.
From “Ban It Till We Understand It” to “Resistance is Futile”’: How University Programming Instructors Plan to Adapt as More Students Use AI Code Generation and Explanation Tools such as ChatGPT and GitHub Copilot. ACM ICER 2023 to appear
Sam Lau and Philip J Guo. 2023 · 2023
Cited alongside, same era.
Using Large Language Models to Enhance Programming Error Messages. In Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1 (Toronto ON, Canada) (SIGCSE 2023) . Association for Computing Machinery, NY, USA, 563–569
Juho Leinonen, Arto Hellas, Sami Sarsa, Brent Reeves, Paul Denny, James Prather, and Brett A. Becker. 2023b · 2023
Cited alongside, same era.
CodeHelp: Using Large Language Models with Guardrails for Scalable Support in Programming Classes
Mark Liffiton, Brad Sheese, Jaromir Savelka, and Paul Denny. 2023 · 2023
Cited alongside, same era.
Computing Education in the Era of Generative AI
Paul Denny, James Prather, Brett A. Becker, James Finnie-Ansley, Arto Hellas, Juho Leinonen, Andrew Luxton-Reilly, Brent N. Reeves, Eddie Antonio Santos, and Sami Sarsa. 2023c
Cited in the paper.
Comparing Code Explanations Created by Students and Large Language Models
Juho Leinonen, Paul Denny, Stephen MacNeil, Sami Sarsa, Seth Bernstein, Joanne Kim, Andrew Tran, and Arto Hellas. 2023a
Cited in the paper.
Learn AI-Assisted Python Programming: With Github Copilot and ChatGPT
Leo Porter and Daniel Zingaro. 2023 · 2023
Closest in time.
The Robots are Here: Navigating the Generative AI Revolution in Computing Education. In Proceedings of the 2023 Working Group Reports on Innovation and Technology in Computer Science Education (Turku, Finland) (ITiCSE-WGR ’23) . ACM, NY, USA
James Prather, Paul Denny, Juho Leinonen, Brett Becker, et al · 2023
Closest in time.
“It’s Weird That It Knows What I Want”: Usability and Interactions with Copilot for Novice Programmers
James Prather, Brent N. Reeves, Paul Denny, Brett A. Becker, Juho Leinonen, Andrew Luxton-Reilly, Garrett Powell, James Finnie-Ansley, and Eddie Antonio Santos. 2023b · 2023
Closest in time.
Evaluating the Performance of Code Generation Models for Solving Parsons Problems With Small Prompt Variations. In Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 1 (Turku, Finland) (ITiCSE 2023) . Association for Computing Machinery, NY, USA, 299–305
Brent Reeves, Sami Sarsa, James Prather, Paul Denny, Brett A. Becker, Arto Hellas, Bailey Kimmel, Garrett Powell, and Juho Leinonen. 2023 · 2023
Closest in time.
K-12 Computing Education for the AI Era: From Data Literacy to Data Agency. In Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 1 (Turku, Finland) (ITiCSE 2023) . Association for Computing Machinery, NY, USA, 1–2
Matti Tedre and Henriikka Vartiainen. 2023 · 2023
Closest in time.
A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT
Jules White, Quchen Fu, Sam Hays, Michael Sandborn, Carlos Olea, Henry Gilbert, Ashraf Elnashar, Jesse Spencer-Smith, and Douglas C. Schmidt. 2023 · 2023
Closest in time.