ChatGPT has gained popularity on social media and proves to be a valuable resource in higher education, assisting students in understanding and evaluating topics by offering topic-specific information, suggesting undiscovered aspects, and introducing new research topics. However, there are currently limited studies on ChatGPT generating text and creating scientific teaching resources in the context of science education. Moreover, there is no research on how university students or teachers apply it to influence teachers’ teaching or students’ learning ability. The study aimed to explore how a university instructor used the ChatGPT flipped model to impact university students’ perceptions of the instructor’s TPACK and students’ self-regulated learning (SRL) ability in a general education course. The results show that while the total mean values of TPACK pre- and post-tests did not reach significant differences, the self-regulated learning (SRL) outcomes of university students obtain significant differences. The research indicates that ChatGPT can assist the university instructor in sourcing text materials, facilitating class discussions, and providing individualized guidance. Additionally, ChatGPT helps the instructor find various topics and offers rich and diverse cross-domain content suggestions. ChatGPT facilitates quick access to required information and reducing search time. It also assists students in finding various topics, offering suggestions, explanations, and aiding in task organization. While it offers different types of subject information and aids in task completion, students should self-evaluate the text information provided by ChatGPT to ensure correctness and suitability. Despite functioning as an artificial intelligence environment, it lacks the ability to empathize with users. The research implications of this study are presented along with relevant suggestions.
References
[1]
Atlas, S. (2023). ChatGPT for Higher Education and Professional Development: A Guide to Conversational AI. https://digitalcommons.uri.edu/cba_facpubs/548
[2]
Barnard, L., Lan, W. Y., To, Y. M., Paton, V. O., & Lai, S. (2009). Measuring Self-Regulation in Online and Blended Learning Environments. The Internet and Higher Education, 12, 1-6. https://doi.org/10.1016/j.iheduc.2008.10.005
[3]
Bogdan, R. C., & Biklen, S. K. (1998). Qualitative Research for Education: An Introduction to Theory and Methods (3rd ed.). Allyn and Bacon.
[4]
Chang, Y., Jang, S., & Chen, Y. (2015). Assessing University Students’ Perceptions of Their physics Instructors’ TPACK Development in Two Contexts. British Journal of Educational Technology, 46, 1236-1249. https://doi.org/10.1111/bjet.12192
[5]
Chatterjee, J., & Dethlefs, N. (2023). This New Conversational AI Model Can Be Your Friend, Philosopher, and Guide ... and Even Your Worst Enemy. Patterns, 4, Article ID: 100676. https://doi.org/10.1016/j.patter.2022.100676
[6]
Chen, Y., Wang, Y., Kinshuk, & Chen, N. (2014). Is FLIP Enough? Or Should We Use the FLIPPED Model Instead? Computers & Education, 79, 16-27.
https://doi.org/10.1016/j.compedu.2014.07.004
[7]
Cooper, G. (2023). Examining Science Education in ChatGPT: An Exploratory Study of Generative Artificial Intelligence. Journal of Science Education and Technology, 32, 444-452. https://doi.org/10.1007/s10956-023-10039-y
[8]
Creswell, J. W., & Clark, V. L. P. (2011). Designing and Conducting Mixed Methods Research. SAGE Publications, Inc.
[9]
Dowling, M., & Lucey, B. (2023). ChatGPT for (Finance) Research: The Bananarama Conjecture. Finance Research Letters, 53, Article ID: 103662.
https://doi.org/10.1016/j.frl.2023.103662
[10]
García-Peñalvo, F. J. (2023). La percepción de la Inteligencia Artificial en contextos educativos tras el lanzamiento de ChatGPT: Disrupción o pánico. Education in the Knowledge Society (EKS), 24, e31279. https://doi.org/10.14201/eks.31279
[11]
Gleason, N. (2022). ChatGPT and the Rise of AI Writers: How Should Higher Education Respond? Times Higher Education.
https://www.timeshighereducation.com/campus/chatgpt-and-rise-aiwriters-how-should-higher-education-respo
[12]
Halaweh, M. (2023). ChatGPT in Education: Strategies for Responsible Implementation. Contemporary Educational Technology, 15, ep421.
https://doi.org/10.30935/cedtech/13036
[13]
Hrastinski, S. (2008). Asynchronous and Synchronous E-Learning. Educause Quarterly, 31, 51-55.
[14]
Jang, S. J. (2017). The Effects of Two Flipped Classrooms on University Students’ Self-Regulated Learning. In R. V. Nata (Ed.), Progress in Education 48 (pp. 103-124). Nova Science Publishers.
[15]
Jang, S. J., & Chen, K. C. (2013). Development of an Instrument to Assess University Students’ Perceptions of Their Science Instructors’ TPACK. Journal of Modern Education Review, 3, 771-783.
[16]
Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., Kasneci, G. et L. (2023). ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education. https://doi.org/10.35542/osf.io/5er8f
[17]
Khalil, M., & Er, E. (2023). Will ChatGPT Get You Caught? Rethinking of Plagiarism Detection. arXiv: 2302.04335. https://doi.org/10.35542/osf.io/fnh48
[18]
Kung, T. H., Cheatham, M., Medenilla, A., Sillos, C., De Leon, L., Elepaño, C. et al. (2023). Performance of ChatGPT on USMLE: Potential for AI-Assisted Medical Education Using Large Language Models. PLOS Digital Health, 2, e0000198.
https://doi.org/10.1371/journal.pdig.0000198
[19]
Lo, C. K., & Hew, K. F. (2019). The Impact of Flipped Classrooms on Student Achievement in Engineering Education: A Meta-Analysis of 10 Years of Research. Journal of Engineering Education, 108, 523-546. https://doi.org/10.1002/jee.20293
[20]
Lo, C. K., Hew, K. F., & Chen, G. (2017). Toward a Set of Design Principles for Mathematics Flipped Classrooms: A Synthesis of Research in Mathematics Education. Educational Research Review, 22, 50-73. https://doi.org/10.1016/j.edurev.2017.08.002
[21]
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
[22]
Mhlanga, D. (2023). Open AI in Education, the Responsible and Ethical Use of ChatGPT Towards Lifelong Learning. SSRN Electronic Journal.
https://doi.org/10.2139/ssrn.4354422
[23]
Mishra, P., & Koehler, M. J. (2006). Technological Pedagogical Content Knowledge: A Framework for Teacher Knowledge. Teachers College Record: The Voice of Scholarship in Education, 108, 1017-1054. https://doi.org/10.1111/j.1467-9620.2006.00684.x
[24]
OpenAI (2023). Educator Considerations for ChatGPT.
https://platform.openai.com/docs/chatgpt-education
[25]
Paris, S. G., & Paris, A. H. (2001). Classroom Applications of Research on Self-Regulated Learning. Educational Psychologist, 36, 89-101.
https://doi.org/10.1207/s15326985ep3602_4
[26]
Pintrich, P. R. (2000). The Role of Goal Orientation in Self-Regulated Learning. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of Self-Regulation (pp. 451-502). Elsevier. https://doi.org/10.1016/b978-012109890-2/50043-3
[27]
Ropek, L. (2023). New York City Schools ban ChatGPT to Head Off a Cheating Epidemic.
https://gizmodo.com/new-york-city-schools-chatgpt-ban-cheating-essay-openai-1849949384
[28]
Susnjak, T. (2022). ChatGPT: The End of Online Exam Integrity? arXiv: 2212.09292.
https://doi.org/10.48550/arXiv.2212.09292
[29]
Zimmerman, B. J. (2000). Self-Efficacy: An Essential Motive to Learn. Contemporary Educational Psychology, 25, 82-91. https://doi.org/10.1006/ceps.1999.1016
[30]
Zimmerman, B. J. (2008). Goal Setting: A Key Proactive Source of Academic Self-Regulation. In D. H. Schunk, & B. J. Zimmerman (Eds.), Motivation and Self-Regulated Learning: Theory, Research, and Applications (pp. 267-295). Lawrence Erlbaum Associates.
