BibTeX:

@inproceedings{prather2023transformed,
author = {Prather, James and Denny, Paul and Leinonen, Juho and Becker, Brett A. and Albluwi, Ibrahim and Caspersen, Michael E. and Craig, Michelle and Keuning, Hieke and Kiesler, Natalie and Kohn, Tobias and Luxton-Reilly, Andrew and MacNeil, Stephen and Petersen, Andrew and Pettit, Raymond and Reeves, Brent N. and Savelka, Jaromir},
title = {Transformed by Transformers: Navigating the AI Coding Revolution for Computing Education: An ITiCSE Working Group Conducted by Humans},
year = {2023},
isbn = {9798400701399},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3587103.3594206},
doi = {10.1145/3587103.3594206},
abstract = {The recent advent of highly accurate and scalable large language models (LLMs) has taken the world by storm. From art to essays to computer code, LLMs are producing novel content that until recently was thought only humans could produce. Recent work in computing education has sought to understand the capabilities of LLMs for solving tasks such as writing code, explaining code, creating novel coding assignments, interpreting programming error messages, and more. However, these technologies continue to evolve at an astonishing rate leaving educators little time to adapt. This working group seeks to document the state-of-the-art for code generation LLMs, detail current opportunities and challenges related to their use, and present actionable approaches to integrating them into computing curricula.},
booktitle = {Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 2},
pages = {561–562},
numpages = {2},
keywords = {computer programming, code generation, LLM, copilot, GPT, codex, artificial intelligence, GitHub, AI, CS1, openAI, pedagogical practices, large language models, novice programming},
location = {Turku, Finland},
series = {ITiCSE 2023}
}

EndNote:

%0 Conference Paper
%T Transformed by Transformers: Navigating the AI Coding Revolution for Computing Education: An ITiCSE Working Group Conducted by Humans
%@ 9798400701399
%U https://doi.org/10.1145/3587103.3594206
%R 10.1145/3587103.3594206
%B Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 2
%I Association for Computing Machinery
%A James Prather
%A Paul Denny
%A Juho Leinonen
%A Brett A. Becker
%A Ibrahim Albluwi
%A Michael E. Caspersen
%A Michelle Craig
%A Hieke Keuning
%A Natalie Kiesler
%A Tobias Kohn
%A Andrew Luxton-Reilly
%A Stephen MacNeil
%A Andrew Petersen
%A Raymond Pettit
%A Brent N. Reeves
%A Jaromir Savelka
%D 2023
%P 561–562
%K LLM, codex, code generation, large language models, openAI, computer programming, copilot, CS1, GitHub, novice programming, pedagogical practices, AI, GPT, artificial intelligence
%C Turku, Finland

ACM:

James Prather, Paul Denny, Juho Leinonen, Brett A. Becker, Ibrahim Albluwi, Michael E. Caspersen, Michelle Craig, Hieke Keuning, Natalie Kiesler, Tobias Kohn, Andrew Luxton-Reilly, Stephen MacNeil, Andrew Petersen, Raymond Pettit, Brent N. Reeves, and Jaromir Savelka. 2023. Transformed by Transformers: Navigating the AI Coding Revolution for Computing Education: An ITiCSE Working Group Conducted by Humans. In Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 2 (ITiCSE 2023). Association for Computing Machinery, New York, NY, USA, 561–562. https://doi.org/10.1145/3587103.3594206