ChatGPT as a tool to support learning in higher education: a teaching experience
DOI:
https://doi.org/10.51302/tce.2024.19083Keywords:
ChatGPT, teaching experience, higher education, technology acceptance model (TAM), unreliability, efficacy, ethical useAbstract
Access to ChatGPT represents an advance in the development of different and complex tasks, but its potential is not free of risks for different fields, including education. With this study we present a teaching experience of ChatGPT integration in the degree in Computer Engineering with the aim of showing its effective and ethical use as a teaching resource for teachers and students (men and women). Specifically, we analyze the use and the degree of acceptance of this technology by students and teachers. The results show that the majority of students (92.50 %) consider ChatGPT to be a useful and easy-to-use tool for academic performance, while the teaching staff (80 %) support this argument to a lesser extent. In addition, the students point out as disadvantages the difficulty of checking the veracity of the result and that it is very generic if the questions are not fine-tuned. The majority of students claim to be quite experienced in using ChatGPT to search for information and, although they do not consider it suitable for generating complete works, they find it beneficial for their learning process if it is used in a complementary and balanced way.
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References
Ajzen, I. y Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behavior. Prentice Hall.
Atlas, S. (2023). ChatGPT for Higher Education and Professional Development: a Guide to Conversational AI. University of Rhode Island. https://digitalcommons.uri.edu/cba_facpubs/548/
Baidoo-Anu, D. y Owusu Ansah, L. (2023). Education in the era of generative artificial intelligence (AI): understanding the potential benefits of ChatGPT in promoting teaching and learning. SSRN, 1-11. http://dx.doi.org/10.2139/ssrn.4337484
Baker, T. y Smith, L. (2019). Educ-AI-tion Rebooted? Exploring the Future of Artificial Intelligence in Schools and Colleges. Nesta Foundation. https://media.nesta.org.uk/documents/Future_of_AI_and_education_v5_WEB.pdf
Bedregal-Alpaca, N., Cornejo-Aparicio, V., Tupacyupanqui-Jaén, D. y Flores-Silva, S. (2019). Evaluación de la percepción estudiantil en relación al uso de la plataforma Moodle desde la perspectiva del TAM. Revista Chilena de Ingeniería, 27(4), 707-718.
Bishop, C. M. (2011). Pattern Recognition and Machine Learning. Springer.
Brookfield, S. D., Rudolph, J. y Yeo, E. (2019). The power of critical thinking in learning and teaching. An interview with Professor Stephen D. Brookfield. Journal of Applied Learning and Teaching, 2(2), 76-90.
Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G. Henighan, T., Child, R., Ramesh, A., Ziegler, D., Wu, J., Winter, C., … y Amodei, D. (2020). Language models are few-shot learners. En H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan y H. Lin (Eds.), Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020 (NeurIPS 2020) (pp. 1.877-1.901).
Cabero Almenara, J., Barroso Osuna, J. y Llorente Cejudo, M.ª D. (2016). Technology acceptance model & realidad aumentada: estudio en desarrollo. Revista Lasallista de Investigación, 13(2), 18-26.
Celik, I., Dindar, M., Muukkonen, H. y Järvelä, S. (2022). The promises and challenges of artificial intelligence for teachers: a systematic review of research. TechTrends, 66, 616-630.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
Eaton, S. E., Mindzak, M. y Morrison, R. (2021). The Impact of Text-Generating Technologies on Academic Integrity: AI & AI. Canadian Association for the Study of Educational Administration (CASEA), University of Alberta.
García Villarroel, J. J. (2021). Implicancia de la inteligencia artificial en las aulas virtuales para la educación superior. Revista Orbis Tertius-UPAL, 5(10), 31-52.
Goodfellow, I., Bengio, Y. y Courville, A. (2016). Deep Learning. MIT Press.
Haleem, A., Javaid, M. y Singh, R. P. (2022). An era of ChatGPT as a significant futuristic support tool: a study on features, abilities, and challenges. BenchCouncil Transactions on Benchmarks, Standards and Evaluations, 2(4), 1-8. https://doi.org/10.1016/j.tbench.2023.100089
Islam, I. e Islam, M. N. (2023). Opportunities and Challenges of ChatGPT in academia: a conceptual analysis. Authorea, 1-9.
Lim, W. M., Gunasekara, A., Pallant, J. L., Pallant, J. I. y Pechenkina, E. (2023). Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators. The International Journal of Management Education, 21(2). https://doi.org/10.1016/j.ijme.2023.100790
Lim, W. M., Kumar, S., Verma, S. y Chaturvedi, R. (2022). Alexa, what do we know about conversational commerce? Insights from a systematic literature review. Psychology and Marketing, 39(6), 1.129-1.155.
Lucy, L. y Bamman, D. (2021). Gender and representation bias in GPT-3 generated stories. Proceedings of the Third Workshop on Narrative Understanding (pp. 48-55).
McMurtrie, B. (2022). AI and the future of undergraduate writing. The Chronicle of Higher Education. https://www.chronicle.com/article/ai-and-the-future-of-undergraduate-writing
Morales-Chan, M. A. (2023). Explorando el potencial de Chat GPT: una clasificación de prompts efectivos para la enseñanza. Galileo Universidad. Tesario Virtual.
Ng, D. T. K., Luo, W., Chan, H. M. Y. y Chu, S. K. W. (2022). Using digital story writing as a pedagogy to develop AI literacy among primary students. Computers and Education: Artificial Intelligence, 3, 1-14. https://doi.org/10.1016/j.caeai.2022.100054
OpenAI. (s. f.). https://help.openai.com/en/
Peng, H., Ma, S. y Spector, J. M. (2019). Personalized adaptive learning: an emerging pedagogical approach enabled by a smart learning environment. Smart Learning Environments, 6(1), 1-14. https://doi.org/10.1186/s40561-019-0089-y
Qadir, J. (2022). Engineering Education in the Era of ChatGPT: Promise and Pitfalls of Generative AI for Education. TechRxiv. https://doi.org/10.36227/techrxiv.21789434.v1
Ray, P. P. (2023). ChatGPT: a comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope. Internet of Things and Cyber-Physical Systems, 3, 121-154.
Ríos Medina, J. de los. (2021). El valor pedagógico de Telegram como complemento del mobile learning en la formación en finanzas: aplicación práctica a un caso de estudio. Tecnología, Ciencia y Educación, 18, 7-42. https://doi.org/10.51302/tce.2021.567
Rudolph, J., Tan, S. y Tan, S. (2023). ChatGPT: bullshit spewer or the end of traditional assessments in higher education? Journal of Applied Learning and Teaching, 6(1), 342-363.
Russell, S. y Norvig, P. (2021). Artificial Intelligence: A Modern Approach (4.ª ed.). Pearson Education.
Salas-Pilco, S. Z. y Yang, Y. (2022). Artificial intelligence applications in Latin American higher education: a systematic review. International Journal of Educational Technology in Higher Education, 19(1), 1-20.
Sánchez Prieto, J. C., Olmos Migueláñez, S. y García-Peñalvo, F. J. (2017). ¿Utilizarán los futuros docentes las tecnologías móviles? Validación de una propuesta de modelo TAM extendido. Revista de Educación a Distancia (RED), 52, 1-31.
Sharples, M. (2022). Automated essay writing: an AIED opinion. International Journal of Artificial Intelligence in Education, 32(4), 1.119-1.126.
Sison, A. J. G., Daza, M. T., Gozalo-Brizuela, R. y Garrido-Merchán, E. C. (2023). ChatGPT: More than a Weapon of Mass Deception, Ethical Challenges and Responses from the Human-Centered Artificial Intelligence (HCAI) Perspective. arXiv. https://arxiv.org/abs/2304.11215
Susnjak, T. (2022). ChatGPT: The End of Online Exam Integrity? arXiv. https://arxiv.org/abs/2212.09292
Tapalova, O. y Zhiyenbayeva, N. (2022). Artificial intelligence in education: AIEd for personalised learning pathways. Electronic Journal of e-Learning, 20(5), 639-653.
Tate, T., Doroudi, S., Ritchie, D. y Xu, Y. (2023). Educational Research and AI-Generated Writing: Confronting the Coming Tsunami. EdArXiv. https://osf.io/preprints/edarxiv/4mec3
Turing, A. M. (1950). Computing machinery and intelligence. Mind, LIX(236), 433-460.
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Copyright (c) 2024 Mercedes Segarra Ciprés, Reyes Grangel Seguer, Óscar Belmonte Fernández
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