ChatGPT for Education and Research: Opportunities, Threats, and Strategies
Source abstract
Abstract
In recent years, the rise of advanced artificial intelligence technologies has had a profound impact on many fields, including education and research. One such technology is ChatGPT, a powerful large language model developed by OpenAI. This technology offers exciting opportunities for students and educators, including personalized feedback, increased accessibility, interactive conversations, lesson preparation, evaluation, and new ways to teach complex concepts. However, ChatGPT poses different threats to the traditional education and research system, including the possibility of cheating on online exams, human-like text generation, diminished critical thinking skills, and difficulties in evaluating information generated by ChatGPT. This study explores the potential opportunities and threats that ChatGPT poses to overall education from the perspective of students and educators. Furthermore, for programming learning, we explore how ChatGPT helps students improve their programming skills. To demonstrate this, we conducted different coding-related experiments with ChatGPT, including code generation from problem descriptions, pseudocode generation of algorithms from texts, and code correction. The generated codes are validated with an online judge system to evaluate their accuracy. In addition, we conducted several surveys with students and teachers to find out how ChatGPT supports programming learning and teaching. Finally, we present the survey results and analysis.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Artificial Intelligence in Healthcare and Education · Explainable Artificial Intelligence (XAI) · Topic Modeling
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Dhaka University of Engineering & Technology, Gazipur, Gazipur 1707, Bangladesh
Department of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu 965-8580, Japan
Funding
Japan Society for the Promotion of Science (JSPS) KAKENHI
References (63)
Show source-provided references
1. A neural network based intelligent support model for program code completion
2. Rahman, M.M., Watanobe, Y., and Nakamura, K. (2021). A bidirectional LSTM language model for code evaluation and repair. Symmetry, 13.10.3390/sym13020247 ↗
3. Rahman, M.M. (2022). Data Analysis and Code Assessment Using Machine Learning Techniques for Programming Activities. [Ph.D. Thesis, The University of Aizu].
4. Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, Ł., and Polosukhin, I. (2017). Attention is all you need. Adv. Neural Inf. Process. Syst., 30, Available online: https://proceedings.neurips.cc/paper_files/paper/2017/file/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf.
5. Language models are few-shot learners
6. GPT-3: Its nature, scope, limits, and consequences10.1007/s11023-020-09548-1 ↗
7. OpenAI-Team (2023, March 11). ChatGPT: Optimizing Language Models for Dialogue. Available online: https://openai.com/blog/chatgpt/.
8. Ouyang, L., Wu, J., Jiang, X., Almeida, D., Wainwright, C.L., Mishkin, P., Zhang, C., Agarwal, S., Slama, K., and Ray, A. (2022). Training language models to follow instructions with human feedback. arXiv.
9. ChatGPT for good? On opportunities and challenges of large language models for education10.1016/j.lindif.2023.102274 ↗
10. Qadir, J. (2022). Engineering Education in the Era of ChatGPT: Promise and Pitfalls of Generative AI for Education. TechRxiv Prepr.10.36227/techrxiv.21789434.v1 ↗
11. Thunstrom, A.O. (Scientific American, 2022). We asked GPT-3 to write an academic paper about itself: Then we tried to get it published, Scientific American.
12. Stokel-Walker, C. (Nature, 2022). AI bot ChatGPT writes smart essays-should academics worry?, Nature.10.1038/d41586-022-04397-7 ↗
13. The End of Programming10.1145/3570220 ↗
14. Susnjak, T. (2022). ChatGPT: The End of Online Exam Integrity?. arXiv.
15. Commentary: How the internet is changing the way we think, read and remember10.1002/bmb.20514 ↗
16. Pappano, L. (New York Times, 2012). The Year of the MOOC, New York Times.
17. Are we there yet?—A systematic literature review on chatbots in education10.3389/frai.2021.654924 ↗
18. Rahman, M.M., Watanobe, Y., Rage, U.K., and Nakamura, K. (2021, January 26–29). A novel rule-based online judge recommender system to promote computer programming education. Proceedings of the Advances and Trends in Artificial Intelligence. From Theory to Practice: 34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2021, Kuala Lumpur, Malaysia.10.1007/978-3-030-79463-7_2 ↗
19. Rahman, M.M., Watanobe, Y., and Nakamura, K. (2020). Source code assessment and classification based on estimated error probability using attentive LSTM language model and its application in programming education. Appl. Sci., 10.10.3390/app10082973 ↗
20. Rahman, M.M., Watanobe, Y., Kiran, R.U., and Kabir, R. (2021, January 13–17). A stacked bidirectional lstm model for classifying source codes built in mpls. Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases: International Workshops of ECML PKDD 2021, Virtual Event.10.1007/978-3-030-93733-1_5 ↗
21. Litman, D. (2016, January 12–17). Natural language processing for enhancing teaching and learning. Proceedings of the AAAI Conference on Artificial Intelligence, Phoenix, AZ, USA.10.1609/aaai.v30i1.9879 ↗
22. Alshater, M.M. (2022). Exploring the role of artificial intelligence in enhancing academic performance: A case study of ChatGPT. SSRN.10.2139/ssrn.4312358 ↗
23. Dowling, M., and Lucey, B. (2023). ChatGPT for (finance) research: The Bananarama conjecture. Financ. Res. Lett., 103662.10.1016/j.frl.2023.103662 ↗
24. Rudolph, J., Tan, S., and Tan, S. (2023). ChatGPT: Bullshit spewer or the end of traditional assessments in higher education?. J. Appl. Learn. Teach., 6.10.37074/jalt.2023.6.1.9 ↗
25. Frieder, S., Pinchetti, L., Griffiths, R.R., Salvatori, T., Lukasiewicz, T., Petersen, P.C., Chevalier, A., and Berner, J. (2023). Mathematical capabilities of chatgpt. arXiv.
26. Kung, T.H., Cheatham, M., Medenilla, A., Sillos, C., De Leon, L., Elepaño, C., Madriaga, M., Aggabao, R., Diaz-Candido, G., and Maningo, J. (2023). Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models. PLoS Digit. Health, 2.10.1371/journal.pdig.0000198 ↗
27. Gilson, A., Safranek, C., Huang, T., Socrates, V., Chi, L., Taylor, R.A., and Chartash, D. (2022). How Well Does ChatGPT Do When Taking the Medical Licensing Exams? The Implications of Large Language Models for Medical Education and Knowledge Assessment. medRxiv.10.1101/2022.12.23.22283901 ↗
28. Aydın, Ö., and Karaarslan, E. (2022). OpenAI ChatGPT generated literature review: Digital twin in healthcare. SSRN.10.2139/ssrn.4308687 ↗
29. Watanobe, Y., Rahman, M.M., Amin, M.F.I., and Kabir, R. (2022). Identifying algorithm in program code based on structural features using CNN classification model. Appl. Intell., 1–27.10.1007/s10489-022-04078-y ↗
30. Competition-level code generation with alphacode10.1126/science.abq1158 ↗
31. Castelvecchi, D. (Nature, 2022). Are ChatGPT and AlphaCode going to replace programmers?, Nature.10.1038/d41586-022-04383-z ↗
32. Sobania, D., Briesch, M., Hanna, C., and Petke, J. (2023). An analysis of the automatic bug fixing performance of chatgpt. arXiv.10.1109/APR59189.2023.00012 ↗
33. Jalil, S., Rafi, S., LaToza, T.D., Moran, K., and Lam, W. (2023). ChatGPT and Software Testing Education: Promises & Perils. arXiv.10.1109/ICSTW58534.2023.00078 ↗
34. Malinka, K., Perešíni, M., Firc, A., Hujňák, O., and Januš, F. (2023). On the educational impact of ChatGPT: Is Artificial Intelligence ready to obtain a university degree?. arXiv.10.1145/3587102.3588827 ↗
35. Kashefi, A., and Mukerji, T. (2023). Chatgpt for programming numerical methods. arXiv.10.1615/JMachLearnModelComput.2023048492 ↗
36. White, J., Hays, S., Fu, Q., Spencer-Smith, J., and Schmidt, D.C. (2023). Chatgpt prompt patterns for improving code quality, refactoring, requirements elicitation, and software design. arXiv.
37. Lee, H. (2023). The rise of ChatGPT: Exploring its potential in medical education. Anat. Sci. Educ.10.1002/ase.2270 ↗
38. Dai, H., Liu, Z., Liao, W., Huang, X., Wu, Z., Zhao, L., Liu, W., Liu, N., Li, S., and Zhu, D. (2023). Chataug: Leveraging chatgpt for text data augmentation. arXiv.
39. Chat with chatgpt on industry 5.0: Learning and decision-making for intelligent industries10.1109/JAS.2023.123552 ↗
40. Using ChatGPT to produce code for a typical college-level assignment
41. Chat with chatgpt on intelligent vehicles: An ieee tiv perspective10.1109/TIV.2023.3253281 ↗
42. Shen, Y., Song, K., Tan, X., Li, D., Lu, W., and Zhuang, Y. (2023). Hugginggpt: Solving ai tasks with chatgpt and its friends in huggingface. arXiv.
43. Avila-Chauvet, L., Mejía, D., and Acosta Quiroz, C.O. (2023). Chatgpt as a Support Tool for Online Behavioral Task Programming. SSRN, Available online: https://ssrn.com/abstract=4329020.
44. Antaki, F., Touma, S., Milad, D., El-Khoury, J., and Duval, R. (2023). Evaluating the performance of chatgpt in ophthalmology: An analysis of its successes and shortcomings. medRxiv.10.1101/2023.01.22.23284882 ↗
45. Rao, A.S., Kim, J., Kamineni, M., Pang, M., Lie, W., and Succi, M. (2023). Evaluating ChatGPT as an adjunct for radiologic decision-making. medRxiv.10.1101/2023.02.02.23285399 ↗
46. Wenzlaff, K., and Spaeth, S. (2022). Smarter than Humans? Validating how OpenAI’s ChatGPT model explains Crowdfunding, Alternative Finance and Community Finance. SSRN.10.2139/ssrn.4302443 ↗
47. Zaremba, A., and Demir, E. (2023). ChatGPT: Unlocking the Future of NLP in Finance. SSRN.10.2139/ssrn.4323643 ↗
48. Choi, J.H., Hickman, K.E., Monahan, A., and Schwarcz, D. (2023). Chatgpt goes to law school. SSRN.10.2139/ssrn.4335905 ↗
49. Jiao, W., Wang, W., Huang, J.t., Wang, X., and Tu, Z. (2023). Is ChatGPT a good translator? A preliminary study. arXiv.
50. Beth, M. (2023, March 12). AI and the Future of Undergraduate Writing. Available online: https://www.chronicle.com/article/ai-and-the-future-of-undergraduate-writing.
51. Automated essay writing: An AIED opinion10.1007/s40593-022-00300-7 ↗
52. Impact of practical skills on academic performance: A data-driven analysis10.1109/ACCESS.2021.3119145 ↗
53. Zhang, Q., Fang, C., Ma, Y., Sun, W., and Chen, Z. (2023). A Survey of Learning-based Automated Program Repair. arXiv.10.1145/3631974 ↗
54. Rahman, M.M., Watanobe, Y., and Nakamura, K. (2020, January 21–23). Evaluation of source codes using bidirectional lstm neural network. Proceedings of the 2020 3rd IEEE International Conference on Knowledge Innovation and Invention (ICKII), Kaohsiung, Taiwan.10.1109/ICKII50300.2020.9318916 ↗
55. Sobania, D., Briesch, M., and Rothlauf, F. (2022, January 9–13). Choose your programming copilot: A comparison of the program synthesis performance of github copilot and genetic programming. Proceedings of the Genetic and Evolutionary Computation Conference, New York, NY, USA.10.1145/3512290.3528700 ↗
56. Online judge system: Requirements, architecture, and experiences10.1142/S0218194022500346 ↗
57. Cotton, D.R., Cotton, P.A., and Shipway, J.R. (2023). Chatting and Cheating. Ensuring academic integrity in the era of ChatGPT. Innov. Educ. Teach. Int., 1–12.10.1080/14703297.2023.2190148 ↗
58. ChatGPT listed as author on research papers: Many scientists disapprove10.1038/d41586-023-00107-z ↗
59. Collaborating with ChatGPT: Considering the Implications of Generative Artificial Intelligence for Journalism and Media Education
60. Can GPT-3 pass a Writer’s turing test?
61. Gao, C.A., Howard, F.M., Markov, N.S., Dyer, E.C., Ramesh, S., Luo, Y., and Pearson, A.T. (2022). Comparing scientific abstracts generated by ChatGPT to original abstracts using an artificial intelligence output detector, plagiarism detector, and blinded human reviewers. bioRxiv.10.1101/2022.12.23.521610 ↗
62. Plagiarism in the age of massive Generative Pre-trained Transformers (GPT-3)10.3354/esep00195 ↗
63. Kalhan, R. (2023, March 12). ChatGPT Banned from New York City Public Schools’ Devices and Networks. Available online: https://www.nbcnews.com/tech/tech-news/new-york-city-public-schools-ban-chatgpt-devices-networks-rcna64446.