A Study on the Application of Artificial Intelligence in Supporting University Lecturers' Lecture Preparation

Le Tien Duy; Le Thi Lien

doi:10.56201/wjimt.v10.no10.2026.pg223.232

📄 Download Paper

A Study on the Application of Artificial Intelligence in Supporting University Lecturers' Lecture Preparation

Le Tien Duy, Le Thi Lien

Abstract

In the context of accelerating digital transformation across higher education institutions worldwide, generative artificial intelligence tools are increasingly adopted by university lecturers in lecture preparation, creating an urgent need for an integrative theoretical framework to explain this process of application. This study aims to clarify the functional categories through which artificial intelligence is applied in lecture preparation, to identify the factors governing the extent to which this technology is accepted and effectively used, and to assess the accompanying opportunities and challenges. To achieve these objectives, the study adopts a desk research method, collecting and comparatively analyzing academic works published from 2015 onward, drawing on the Technology Acceptance Model, the Unified Theory of Acceptance and Use of Technology, and the Technological Pedagogical Content Knowledge framework as its theoretical foundation. The findings show that artificial intelligence is applied through five principal functional categories, among which content and outline generation is the most prevalent; the degree of technology acceptance is jointly shaped by technological perception, institutional conditions, and pedagogical competence; and opportunities for efficiency and personalization consistently coexist with challenges relating to content quality and academic integrity. On this basis, the study proposes an integrative conceptual framework combining the three theories above, contributing a theoretical foundation for subsequent empirical research and offering governance implications for lecturers, higher education institutions, and education management authorities.

Keywords

Generative artificial intelligence; University lecture preparation; Technology acceptance model; Technological pedagogical content knowledge.

References

Black, E., & Betts, K. (2025). Unlocking the future: How are EdD faculty using generative AI in doctoral research? Impacting Education: Journal on Transforming Professional Practice, 10(1), 49–56. https://doi.org/10.5195/ie.2025.475 Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008 Digital Education Council. (2024). What students want: Key results from DEC Global AI Student Survey 2024. https://www.digitaleducationcouncil.com/post/what-students-want-key- results-from-dec-global-ai-student-survey-2024 Digital Education Council. (2025). Global AI Faculty Survey 2025. https://www.digitaleducationcouncil.com/post/digital-education-council-global-ai- faculty-survey Koehler, M. J., & Mishra, P. (2009). What is technological pedagogical content knowledge? Contemporary Issues in Technology and Teacher Education, 9(1), 60–70. https://citejournal.org/volume-9/issue-1-09/general/what-is-technological- pedagogicalcontent-knowledge Liang, D., & Suwanragsa, I. (2025). Determinants of generative AI adoption in higher education: A social science perspective on Thai faculty behavioral intentions. European Journal of Social Science Education and Research, 12(4), 132–147. https://doi.org/10.26417/bamx9m98 Michel-Villarreal, R., Vilalta-Perdomo, E., Salinas-Navarro, D. E., Thierry-Aguilera, R., & Gerardou, F. S. (2023). Challenges and opportunities of generative AI for higher education as explained by ChatGPT. Education Sciences, 13(9), Article 856. https://doi.org/10.3390/educsci13090856 Mishra, P., Warr, M., & Islam, R. (2023). TPACK in the age of ChatGPT and generative AI. Journal of Digital Learning in Teacher Education, 39(4), 235–251. https://doi.org/10.1080/21532974.2023.2247480 Moundridou, M., Matzakos, N., & Doukakis, S. (2024). Generative AI tools as educators' assistants: Designing and implementing inquiry-based lesson plans. Computers and Education: Artificial Intelligence, 7, Article 100277. https://doi.org/10.1016/j.caeai.2024.100277 Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., ... Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, Article n71. https://doi.org/10.1136/bmj.n71 Samala, A. D., Rawas, S., Wang, T., Reed, J. M., Kim, J., Howard, N.-J., & Ertz, M. (2025). Unveiling the landscape of generative artificial intelligence in education: A comprehensive taxonomy of applications, challenges, and future prospects. Education and Information Technologies, 30(3), 3239–3278. https://doi.org/10.1007/s10639-024-12936-0 Sevilla-Bernardo, J., Cervera, L., & Martin-Robles, J. (2025). Impact and opportunities of generative artificial intelligence in education: A study of academic perceptions. International Journal of Emerging Technologies in Learning , 20(3), 55–71. https://doi.org/10.3991/ijet.v20i03.55809 Shata, A., & Hartley, K. (2025). Artificial intelligence and communication technologies in academia: Faculty perceptions and the adoption of generative AI. International Journal of Educational Technology in Higher Education, 22, Article 14. https://doi.org/10.1186/s41239-025-00511-7 Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–339. https://doi.org/10.1016/j.jbusres.2019.07.039 Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540

A Study on the Application of Artificial Intelligence in Supporting University Lecturers' Lecture Preparation

Abstract

Keywords

References

More Articles from WORLD JOURNAL OF INNOVATION AND MODERN TECHNOLOGY