{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T02:36:29Z","timestamp":1784342189268,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":17,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T00:00:00Z","timestamp":1709769600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,3,7]]},"DOI":"10.1145\/3626252.3630789","type":"proceedings-article","created":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T18:17:20Z","timestamp":1709835440000},"page":"743-749","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":48,"title":["Beyond Traditional Teaching: Large Language Models as Simulated Teaching Assistants in Computer Science"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-4661-8470","authenticated-orcid":false,"given":"Mengqi","family":"Liu","sequence":"first","affiliation":[{"name":"Department of Computer Science, McGill University, Montreal, QC, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6243-7521","authenticated-orcid":false,"given":"Faten","family":"M'Hiri","sequence":"additional","affiliation":[{"name":"Department of Computer Science, McGill University, Montreal, QC, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,3,7]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Borisov V. Se\u00dfler K. Leemann T. Pawelczyk M. & Kasneci G.. 2022. Language models are realistic tabular data generators. arXiv:2210.06280. Retrieved from https:\/\/arxiv.org\/abs\/2210.06280"},{"key":"e_1_3_2_1_2_1","first-page":"1877","article-title":"Language models are few-shot learners","volume":"33","author":"Brown T.","year":"2020","unstructured":"Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al.. 2020. Language models are few-shot learners. Advances in Neural Information Processing Systems 33 (2020), 1877--1901.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_3_1","unstructured":"Chase H.. 2022. LangChain (Version 1.2.0) [%Computer software$]. Retrieved from https:\/\/github.com\/hwchase17\/langchain"},{"key":"e_1_3_2_1_4_1","volume-title":"Proceedings of Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT)","author":"Jacob Devlin","year":"2019","unstructured":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. Bert: Pre-training of deep bidirectional transformers for language understanding. In Proceedings of Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT) (2019), 4171--4186."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11023-020-09548-1"},{"key":"e_1_3_2_1_6_1","unstructured":"Chuqin Geng Yihan Zhang Brigitte Pientka and Xujie Si. 2023. Can ChatGPT Pass An Introductory Level Functional Language Programming Course? arXiv:2305.02230. Retrieved from https:\/\/arxiv.org\/abs\/2305.02230"},{"key":"e_1_3_2_1_7_1","unstructured":"Hamid R. D. & Schisgall E. J.. 2023. CS50 will integrate artificial intelligence into course instruction: News: The Harvard Crimson. Retrieved from https:\/\/www.thecrimson.com\/article\/2023\/6\/21\/cs50-artificial-intelligence"},{"key":"e_1_3_2_1_8_1","unstructured":"Haque M. U. Dharmadasa I. Sworna Z. T. Rajapakse R. N. & Ahmad H.. 2022. \"I think this is the most disruptive technology\": Exploring sentiments of ChatGPT early adopters using Twitter data. arXiv:2212.05856. Retrieved from https:\/\/arxiv.org\/abs\/2212.05856"},{"key":"e_1_3_2_1_9_1","unstructured":"Ho N. Schmid L. & Yun S. Y.. 2022. Large language models are reasoning teachers. arXiv:2212.10071. Retrieved from https:\/\/arxiv.org\/abs\/2212.10071"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.lindif.2023.102274"},{"key":"e_1_3_2_1_11_1","volume-title":"Recent advances in natural language processing via large pre-trained language models: A survey. ACM Computing Surveys","author":"Min B.","year":"2021","unstructured":"Min, B., Ross, H., Sulem, E., Veyseh, A. P. B., Nguyen, T. H., Sainz, O., & Roth, D.. 2021. Recent advances in natural language processing via large pre-trained language models: A survey. ACM Computing Surveys (2021)."},{"key":"e_1_3_2_1_12_1","unstructured":"Mogavi R. H. Deng C. Kim J. J. Zhou P. Kwon Y. D. Metwally A. H. S. & Hui P.. 2023. Exploring user perspectives on ChatGPT: Applications perceptions and implications for AI-integrated education. arXiv:2305.13114. Retrieved from https:\/\/arxiv.org\/abs\/2305.13114"},{"key":"e_1_3_2_1_13_1","unstructured":"OpenAI. 2023. Gpt-4 technical report. Retrieved from https:\/\/cdn.openai.com\/papers\/gpt-4.pdf"},{"key":"e_1_3_2_1_14_1","unstructured":"Qureshi B.. 2023. Exploring the use of ChatGPT as a tool for learning and assessment in undergraduate computer science curriculum: Opportunities and challenges. arXiv:2304.11214. Retrieved from https:\/\/arxiv.org\/abs\/2304.11214"},{"key":"e_1_3_2_1_15_1","volume-title":"What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart Learning Environments 10(1)","author":"Tlili A.","year":"2023","unstructured":"Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B.. 2023. What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart Learning Environments 10(1) (2023), 15."},{"key":"e_1_3_2_1_16_1","volume-title":"Llama: Open and efficient foundation language models. arXiv:2302.13971.","author":"Touvron H.","year":"2023","unstructured":"Touvron, H., Lavril, T., Izacard, G., Martinet, X., Lachaux, M. A., Lacroix, T., & Lample, G.. 2023. Llama: Open and efficient foundation language models. arXiv:2302.13971. Retrieved from https:\/\/arxiv.org\/abs\/2302.13971"},{"key":"e_1_3_2_1_17_1","volume-title":"Attention is all you need. Advances in neural information processing systems","author":"Vaswani A.","year":"2017","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., & Polosukhin, I.. 2017. Attention is all you need. Advances in neural information processing systems (2017)."}],"event":{"name":"SIGCSE 2024: The 55th ACM Technical Symposium on Computer Science Education","location":"Portland OR USA","acronym":"SIGCSE 2024","sponsor":["SIGCSE ACM Special Interest Group on Computer Science Education"]},"container-title":["Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3626252.3630789","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3626252.3630789","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,21]],"date-time":"2025-08-21T04:34:45Z","timestamp":1755750885000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3626252.3630789"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,7]]},"references-count":17,"alternative-id":["10.1145\/3626252.3630789","10.1145\/3626252"],"URL":"https:\/\/doi.org\/10.1145\/3626252.3630789","relation":{},"subject":[],"published":{"date-parts":[[2024,3,7]]},"assertion":[{"value":"2024-03-07","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}