Utilization of ChatGPT in CDIO projects to enhance the literacy of international students

ChatGPT is based on generative pre-trained transformer architecture which can generate new contents in real time. By utilizing a text-to-text generative AI capability while trained on a large dataset, it can offer customized learning experiences to students with a summary of information, feedback, market research, preparing reports and explanations.

To embed graduate employability skills, CDIO projects have been incorporated into most of the engineering courses at our university. Each year, thousands of international students come to study post-graduate courses at UK universities, especially from South Asian countries where the traditional learning process has been embedded with exam-based summative assessments. However, international students have found it difficult to prepare project reports due to their limited experience. Evidently, a large number of international students plagiarized their reports and faced academic misconduct panels. After chairing a few academic misconduct panels, we have realized that we need to improve their literacy in preparing project reports. ChatGPT can be a useful tool for improving their literacy in completing CDIO projects, especially when their native language is not English. It may also support disabled students with dyslexia and learning disability to overcome language barriers in preparing the report with sentence structuring, avoiding grammatical errors etc.

Despite showing several benefits, ChatGPT has some limitations and risks. It may generate biased information or even misinformation, raising legitimacy and authenticity of academic work, and ethical concerns relevant to the inappropriate use of it by students. Hence, the significance of academic transparency and ethical standards should be maintained while using it. While understanding the limitations and negative impacts of ChatGPT, it is important to adapt it in engineering education so that future engineers can use it as an effective tool for CDIO projects in engineering education.

Austin, J., Odena, A., Nye, M., Bosma, M., Michalewski, H., Dohan, D., . . . Le, Q. (2021). Program synthesis with large language models. arXiv Preprint arXiv:2108.07732.
Barbetta, P. M. (2023). Remedial and compensatory writing technologies for middle school students with learning disabilities and their classmates in inclusive classrooms. Preventing School Failure: Alternative Education for Children and Youth, 1-12.
Bolton, P., Lewis, J., & Gower, M. (2023). International students in UK higher education. House of Commons. Retrieved from https://commonslibrary.parliament.uk/research-briefings/cbp-7976/.
Cai, Z. G., Haslett, D. A., Duan, X., Wang, S., & Pickering, M. J. (2023). Does ChatGPT resemble humans in language use? arXiv Preprint arXiv:2303.08014.
Coello, C. E. A., Alimam, M. N., & Kouatly, R. (2024). Effectiveness of ChatGPT in coding: A comparative analysis of popular large language models. Digital, 4(1), 114-125.
Crawley, E. F., Malmqvist, J., Östlund, S., Brodeur, D. R., & Edström, K. (2014). The CDIO approach. Rethinking engineering education (pp. 11-45) Springer.
Dai, W., Lin, J., Jin, H., Li, T., Tsai, Y., Gašević, D., & Chen, G. (2023). Can large language models provide feedback to students? A case study on ChatGPT.In 2023 IEEE International Conference on Advanced Learning Technologies (ICALT) (pp. 323-325). IEEE.
Kennedy, D., Halim, E., Condrobimo, A. R., Syamsuar, D., & Ferdianto, F. (2023). Overcoming language barriers in MOOCs with artificial intelligence: An AI-based approach for multilingual education.In Eighth International Conference on Informatics and Computing (ICIC), (pp. 1 -6). IEEE.
Kumar, A. H. (2023). Analysis of ChatGPT tool to assess the potential of its utility for academic writing in biomedical domain. Biology, Engineering, Medicine and Science Reports, 9(1), 24-30.
Manna, S., Joyce, N., & Nortcliffe, A. (2023). Integration of graduate employability skills through industry outsourced CDIO project.In 19th International CDIO Conference (pp. 425-435). NTNU SEED.
Nawani, D., & Goswami, R. (2020). Assessment of student learning in south asia: Concerns and challenges. Handbook of Education Systems in South Asia, 1-33.
OpenAI. (2024). ChatGPT [Large language model]. https://chat.openai.com.
Qadir, J. (2023). Engineering education in the era of ChatGPT: Promise and pitfalls of generative AI for education. In IEEE Global Engineering Education Conference (EDUCON) (pp. 1-9). IEEE.
Qadir, J., Taha, A. M., Yau, K. A., Ponciano, J., Hussain, S., Al-Fuqaha, A., & Imran, M. A. (2020). Leveraging the force of formative assessment & feedback for effective engineering education. Retrieved from https://eprints.gla.ac.uk/202106/.
Sakib, F. A., Khan, S. H., & Karim, A. (2023). Extending the frontier of chatgpt: Code generation and debugging. arXiv Preprint arXiv:2307.08260.
Sina, A. (2023). Open AI and its Impact on Fraud Detection in Financial Industry. Journal of Knowledge Learning and Science Technology, 2(3), 263-281.
Singh, A., Dwivedi, T., Bulchandani, S., Dwivedi, B., Sharma, R., & Kaur, A. (2023). Pros and cons of using ChatGPT in medical research and Publishing–A comprehensive review. American Journal of Medical Case Reports, 11(10), 161-163.
Sohail, S. S. (2023). A promising start and not a panacea: ChatGPT's early impact and potential in medical science and biomedical engineering research. Annals of Biomedical Engineering,1-5.
Surameery, N. M. S., & Shakor, M. Y. (2023). Use chat gpt to solve programming bugs. International Journal of Information Technology & Computer Engineering, 3(1), 17-22.
Tamariz, M. (2019). Replication and emergence in cultural transmission. Physics of Life Reviews, 30, 47-71.
Watters, C., & Lemanski, M. K. (2023). Universal skepticism of ChatGPT: A review of early literature on chat generative pre-trained transformer. Frontiers in Big Data, 6.