A Fast and Accurate Machine Learning Autograder for the Breakout Assignment-Reference-Cited by-同舟云学术

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A Fast and Accurate Machine Learning Autograder for the Breakout Assignment

Published:2024-03-07 Issue: Volume:9 Page:736-742
ISSN:
Container-title:Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1
language:
Short-container-title:

Author:

Liu Evan Zheran¹^ORCID,Yuan David²^ORCID,Ahmed Ahmed²^ORCID,Cornwall Elyse²^ORCID,Woodrow Juliette²^ORCID,Burns Kaylee²^ORCID,Nie Allen²^ORCID,Brunskill Emma²^ORCID,Piech Chris²^ORCID,Finn Chelsea²^ORCID

Affiliation:

1. Stanford University & Imbue, Stanford, CA, USA

2. Stanford University, Stanford, CA, USA

Funder

National Science Foundation

Stanford University

Intel Foundation

CIFAR Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3626252.3630759

Reference34 articles.

1. Games for teaching computing in higher education--a systematic review;Battistella Paulo;IEEE Technology and Engineering Education,2016

2. Sahil Bhatia and Rishabh Singh. 2016. Automated correction for syntax errors in programming assignments using recurrent neural networks. arXiv preprint arXiv:1603.06129 (2016).

3. Girls, computer science, and games

4. Code.org. 2022. Code.org. https://code.org/about.

5. Five Major Shifts in 100 Years of Engineering Education

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