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Towards Integrating Emerging AI Applications in SE Education (2405.18062v2)

Published 28 May 2024 in cs.SE

Abstract: AI approaches have been incorporated into modern learning environments and software engineering (SE) courses and curricula for several years. However, with the significant rise in popularity of LLMs in general, and OpenAI's LLM-powered chatbot ChatGPT in particular in the last year, educators are faced with rapidly changing classroom environments and disrupted teaching principles. Examples range from programming assignment solutions that are fully generated via ChatGPT, to various forms of cheating during exams. However, despite these negative aspects and emerging challenges, AI tools in general, and LLM applications in particular, can also provide significant opportunities in a wide variety of SE courses, supporting both students and educators in meaningful ways. In this early research paper, we present preliminary results of a systematic analysis of current trends in the area of AI, and how they can be integrated into university-level SE curricula, guidelines, and approaches to support both instructors and learners. We collected both teaching and research papers and analyzed their potential usage in SE education, using the ACM Computer Science Curriculum Guidelines CS2023. As an initial outcome, we discuss a series of opportunities for AI applications and further research areas.

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References (36)
  1. Investigating the potential of GPT-3 in providing feedback for programming assessments. In Proc. of the 2023 Conf. on Innovation and Technology in Computer Science Education, page 292–298. ACM, 2023.
  2. Engaging minds - how gamified chatbots can support and motivate learners in digital education. In T. X. Bui, editor, Proc. of the 57th Hawaii Int’l Conf. on System Sciences, pages 54–63. ScholarSpace, 2024.
  3. Challenges to academic integrity from new tools-a survey of students’ perceptions and behaviors of employing chatgpt. 2024.
  4. I. Bouzenia and M. Pradel. When to say what: Learning to find condition-message inconsistencies. In Proc. of the 45th Int’l Conf. on Software Engineering, pages 868–880. IEEE, 2023.
  5. B. P. Cipriano and P. Alves. Gpt-3 vs object oriented programming assignments: An experience report. In 2023 Conf. on Innovation and Technology in Computer Science Education V.1, pages 61–67, 2023.
  6. M. Daun and J. Brings. How chatgpt will change software engineering education. In Proc. of the 2023 Conf. on Innovation and Technology in Computer Science Education V.1, pages 110–116, 2023.
  7. Revisiting learning-based commit message generation. In Proc. of the 45th Int’l Conference on Software Engineering, ICSE ’23, page 794–805. IEEE Press, 2023.
  8. AI-based question answering assistance for analyzing natural-language requirements. arXiv preprint arXiv:2302.04793, 2023.
  9. Baldur: Whole-proof generation and repair with large language models. In Proc. of the 31st ACM Joint European Software Engineering Conf. and Symposium on the Foundations of Software Engineering, pages 1229–1241, 2023.
  10. NLP/AI based techniques for programming exercises generation. In Proc. of the 4th Int’l Computer Programming Education Conf. Schloss Dagstuhl-Leibniz-Zentrum für Informatik, 2023.
  11. Artificial intelligence for student assessment: A systematic review. Applied Sciences, 11(12):5467, 2021.
  12. On the applicability of language models to block-based programs. In Proc. of the 45th Int’l Conf. on Software Engineering, pages 2374–2386, 2023.
  13. The earlybird catches the bug: On exploiting early layers of encoder models for more efficient code classification. arXiv preprint arXiv:2305.04940, 2023.
  14. IEEE Computer Society. SWEBOK Guide Version 4.0 beta. https://sebokwiki.org/wiki/SWEBOK_Guide_Version_4.0, Last accessed 01-06-2024.
  15. M. Johnson. Generative AI and CS education. Communications of the ACM, 67(4):23–24, Mar. 2024.
  16. D. Kalles. Artificial intelligence meets software engineering in computing education. In Proc. of the 9th Hellenic Conf. on Artificial Intelligence, USA, 2016. ACM.
  17. Large language models are few-shot testers: Exploring LLM-based general bug reproduction. In Proc. of the 45th Int’l Conf. on Software Engineering, pages 2312–2323. IEEE, 2023.
  18. A review of ai-supported tutoring approaches for learning programming. Advanced computational methods for knowledge engineering, pages 267–279, 2013.
  19. Comparing code explanations created by students and large language models. In 2023 Conf. on Innovation and Technology in Computer Science Education V. 1. ACM, 2023.
  20. Competition-level code generation with alphacode. Science, 378(6624):1092–1097, 2022.
  21. On the robustness of code generation techniques: An empirical study on github copilot. In Proc. of the 45th Int’l Conf. on Software Engineering, pages 2149–2160, 2023.
  22. GitHub copilot AI pair programmer: Asset or liability? Journal of Systems and Software, 203, 2023.
  23. Improving API knowledge discovery with ML: A case study of comparable API methods. In 45th Int’l Conf. on Software Engineering, pages 1890–1906, 2023.
  24. Learning deep semantics for test completion. preprint - arXiv:2302.10166, 2023.
  25. C. W. Okonkwo and A. Ade-Ibijola. Chatbots applications in education: A systematic review. Computers and Education: Artificial Intelligence, 2:100033, 2021.
  26. M. C. Pluff and V. Weiss. Competency-based education: The future of higher education. New Models of Higher Education: Unbundled, Rebundled, Customized, and DIY, pages 200–218, 2022.
  27. M. M. Rahman and Y. Watanobe. ChatGPT for education and research: Opportunities, threats, and strategies. Applied Sciences, 13(9):5783, 2023.
  28. Toward computer science curricular guidelines 2023 (cs2023). Inroads, 13(4):22–25, 2022.
  29. Evaluating the performance of code generation models for solving parsons problems with small prompt variations. In Proc. of the 2023 Conf. on Innovation and Technology in Computer Science Education V.1, page 299–305. ACM, 2023.
  30. Artificial intelligence and learning analytics in teacher education: A systematic review. Education Sciences, 12(8):569, 2022.
  31. An empirical evaluation of using large language models for automated unit test generation. IEEE Transactions on Software Engineering, 2023.
  32. PSAbot: A chatbot system for the analysis of posts on stack overflow. In Proc. of the 35th Int’l Conf. on Software Engineering Education and Training, pages 137–141. IEEE, 2023.
  33. CoCoSoDa: Effective contrastive learning for code search. In Proc. of the 45th Int’l Conf. on Software Engineering, pages 2198–2210, 2023.
  34. Investigating the use of ai-generated exercises for beginner and intermediate programming courses: A ChatGPT case study. In Proc. of the 35th Int’l Conf. on Software Engineering Education and Training, pages 142–146. IEEE, 2023.
  35. Automated program repair in the era of large pre-trained language models. In Proc. of the 45th Int’l Conf. on Software Engineering, pages 1482–1494, 2023.
  36. Multilingual code co-evolution using large language models. In Proc. of the 31st ACM Joint European Software Engineering Conf. and Symposium on the Foundations of Software Engineering, pages 695–707, 2023.
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Authors (4)
  1. Michael Vierhauser (16 papers)
  2. Iris Groher (3 papers)
  3. Tobias Antensteiner (2 papers)
  4. Clemens Sauerwein (10 papers)
Citations (1)
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