Comparing Code Explanations Created by Students and Large Language Models

Author:

Leinonen Juho1ORCID,Denny Paul1ORCID,MacNeil Stephen2ORCID,Sarsa Sami3ORCID,Bernstein Seth2ORCID,Kim Joanne2ORCID,Tran Andrew2ORCID,Hellas Arto3ORCID

Affiliation:

1. University of Auckland, Auckland, New Zealand

2. Temple University, Philadelphia, PA, USA

3. Aalto University, Espoo, Finland

Funder

Ulla Tuominen Foundation

Publisher

ACM

Reference48 articles.

1. Evaluating the Quality of Learning Resources: A Learnersourcing Approach

2. Learning programming via worked-examples: Relation of learning styles to cognitive load

3. Programming Is Hard - Or at Least It Used to Be

4. Tom Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared D Kaplan Prafulla Dhariwal Arvind Neelakantan Pranav Shyam Girish Sastry Amanda Askell etal 2020. Language models are few-shot learners. Advances in neural information processing systems Vol. 33 (2020) 1877--1901. Tom Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared D Kaplan Prafulla Dhariwal Arvind Neelakantan Pranav Shyam Girish Sastry Amanda Askell et al. 2020. Language models are few-shot learners. Advances in neural information processing systems Vol. 33 (2020) 1877--1901.

5. Mark Chen , Jerry Tworek , Heewoo Jun , Qiming Yuan , Henrique Ponde de Oliveira Pinto , Jared Kaplan, Harri Edwards, Yuri Burda, et al. 2021 . Evaluating large language models trained on code. arXiv preprint arXiv:2107.03374 (2021). Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, et al. 2021. Evaluating large language models trained on code. arXiv preprint arXiv:2107.03374 (2021).

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