Computing Education in the Era of Generative AI

Обучение информатике в эпоху генеративного искусственного интеллекта
James Finnie-Ansley, Paul Denny, Brett A. Becker, Andrew Luxton-Reilly, James Prather, Juho Leinonen, Brent N. Reeves, Sami Sarsa, Arto Hellas, Eddie Antonio Santos
2024-01-18
SCID:  54.1/r5n77a5e Discuss with AI
computing educationgenerative AIlarge language modelsnatural-language problem descriptionssource code generation
Abstract (AI)
Challenges and opportunities faced by computing educators and students adapting to LLMs capable of generating accurate source code from natural-language problem descriptions.
Key Findings
1
Generative AI and large language models create new challenges for computing educators and students.
2
LLMs can generate accurate source code from natural-language problem descriptions, affecting conventional approaches to computing education.
3
The integration of generative AI into computing education presents both pedagogical opportunities and adaptation challenges.
Research Object

computing educators and students adapting to LLMs

Research Subject

challenges and opportunities of adapting to LLMs capable of generating accurate source code from natural-language problem descriptions

Publication Details
Publication Date
2024-01-18
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294
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Authors
James Finnie-Ansley
Paul Denny
Brett A. Becker
Andrew Luxton-Reilly
James Prather
Juho Leinonen
Brent N. Reeves
Sami Sarsa
Arto Hellas
Eddie Antonio Santos
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