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Seth Bernstein
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Generating diverse code explanations using the gpt-3 large language model
S MacNeil, A Tran, D Mogil, S Bernstein, E Ross, Z Huang
Proceedings of the 2022 ACM Conference on International Computing Education …, 2022
1802022
Experiences from using code explanations generated by large language models in a web software development e-book
S MacNeil, A Tran, A Hellas, J Kim, S Sarsa, P Denny, S Bernstein, ...
Proceedings of the 54th ACM Technical Symposium on Computer Science …, 2023
1372023
Comparing code explanations created by students and large language models
J Leinonen, P Denny, S MacNeil, S Sarsa, S Bernstein, J Kim, A Tran, ...
Proceedings of the 2023 Conference on Innovation and Technology in Computer …, 2023
1222023
Automatically generating cs learning materials with large language models
S MacNeil, A Tran, J Leinonen, P Denny, J Kim, A Hellas, S Bernstein, ...
arXiv preprint arXiv:2212.05113, 2022
412022
The Implications of Large Language Models for CS Teachers and Students.
S MacNeil, J Kim, J Leinonen, P Denny, S Bernstein, BA Becker, ...
SIGCSE (2), 1255, 2023
252023
Decoding logic errors: a comparative study on bug detection by students and large language models
S MacNeil, P Denny, A Tran, J Leinonen, S Bernstein, A Hellas, S Sarsa, ...
Proceedings of the 26th Australasian Computing Education Conference, 11-18, 2024
122024
Prompt middleware: Mapping prompts for large language models to UI affordances
S MacNeil, A Tran, J Kim, Z Huang, S Bernstein, D Mogil
arXiv preprint arXiv:2307.01142, 2023
92023
Analyzing Students' Preferences for LLM-Generated Analogies
S Bernstein, P Denny, J Leinonen, M Littlefield, A Hellas, S MacNeil
Proceedings of the 2024 on Innovation and Technology in Computer Science …, 2024
2024
"Like a Nesting Doll": Analyzing Recursion Analogies Generated by CS Students using Large Language Models
S Bernstein, P Denny, J Leinonen, L Kan, A Hellas, MLS Sarsa, ...
Proceedings of the 2024 on Innovation and Technology in Computer Science …, 2024
2024
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