Using Artificial Intelligence Technology to Develop Office Technology Skills of Pre-Service Teachers: A Classroom Action Research
Keywords:
Artificial Intelligence, Office Technology, Document Management, Presentation, Pre-service TeachersAbstract
This classroom action research aimed to investigate the effects of integrating Artificial Intelligence (AI) into teaching and learning on the development of office technology skills among undergraduate students, focusing on document preparation and presentation tasks. The study also examined students’ satisfaction and reflective thinking toward the use of AI. The study involved the entire population of twelve second-year undergraduate students majoring in Digital Technology for Education, Faculty of Education, Kasetsart University. The intervention was conducted over a four-week period, during which the students were assigned four tasks, comprising two document-based assignments and two presentation projects, to evaluate their office technology skills supported by AI. Research instruments included performance assessment rubrics, a satisfaction questionnaire, and reflective journals. Data were analyzed using mean, percentage, and standard deviation. The findings revealed that students’ skills in document preparation and presentation were at an excellent level (μ = 64.83, 81.04%). Student satisfaction was rated at a high to very high level across all dimensions, particularly in the development of document and presentation skills (μ = 4.92, σ = 0.29). Reflective results indicated that students recognized both the benefits and limitations of using AI, emphasizing the importance of effective prompting and ethical use of technology. In conclusion, the study confirms that integrating AI into teaching and learning enhances students’ office technology skills in documentation and presentation, increases work efficiency, and fosters high satisfaction and positive reflection. These insights are valuable for improving instructional practices and promoting the responsible use of technology to strengthen students’ learning performance in the future.
References
McAfee, A. and E. Brynjolfsson, E. (2017). Machine, Platform, Crowd: Harnessing Our Digital Future, W. W. Norton & Company, New York.
Holmes, W., Bialik, M. and Fadel, C. (2019). Artificial Intelligence in Education: Promises and Implications for Teaching and Learning, Center for Curriculum Redesign: Boston, MA, USA.
West, D.M. and Allen, J.R. (2020). Turning Point: Policymaking in the Era of Artificial Intelligence, Brookings Institution Press, Washington, DC, USA.
Microsoft (2023). 2023 Work Trend Index: Will AI Fix Work?, Microsoft Corporation, URL: https://www.microsoft.com/en-us/worklab/work-trend-index/will-ai-fix-work, accessed on 26/11/2025.
UNESCO (2017). A Guide for Ensuring Inclusion and Equity in Education, UNESCO Publishing, Paris, URL: https://unesdoc.unesco.org/ark:/48223/pf0000248254, accessed on 26/11/2025.
Anderson, J. and Rainie, L. (2022). The Role of AI in Education and the Workforce, Pew Research Center, Washington, DC, USA.
OECD (2019). OECD Skills Outlook 2019: Thriving in a Digital World, OECD Publishing, Paris, URL: https://www.oecd.org/content/dam/oecd/en/publications/reports/2019/05/oecd-skills-outlook-2019_c8896fe0/df80bc12-en.pdf, accessed on 26/11/2025.
สมชาย สุวรรณวงศ์ (2564). การพัฒนาหลักสูตรเพื่อเสริมสร้างทักษะดิจิทัลในศตวรรษที่ 21,วารสารศึกษาศาสตร์, 45, หน้า 101–120.
ศิริลักษณ์ จันทร์ดี (2562). การใช้เทคโนโลยีปัญญาประดิษฐ์เพื่อพัฒนาความมั่นใจในการจัดการเอกสารของนิสิตครู,วารสารครุศาสตร์อุตสาหกรรม, 18, หน้า 55–70.
Microsoft & LinkedIn (2024). 2024 Work Trend Index Annual Report: AI at Work Is Here. Now Comes the Hard Part, Microsoft Corporation, URL: https://www.microsoft.com/en-us/worklab/work-trend-index/ai-at-work-is-here-now-comes-the-hard-part, accessed on 26/11/2025.
Wolff, A., Gooch, R. and Cavero, M. (2021). AI in education: Opportunities and challenges for teachers, Computers and Education Open, vol. 2, pp. 1–10, 2021.
Crompton, H. and Burke, D. (2023). Artificial intelligence in higher education: the state of the field, International Journal of Educational Technology in Higher Education, vol. 20(1), pp. 1-22.
Holmes, W. and Miao, F. (2023). Guidance for Generative AI in Education and Research, Unesco Publishing, Paris.
OECD (2025). What Should Teachers Teach and Students Learn in a Future of Powerful AI?, OECD Education Spotlights, No. 20, OECD Publishing, Paris.
Wan, T. and Chen, Z. (2024). Exploring generative AI assisted feedback writing for students’ written responses to a physics conceptual question with prompt engineering and few-shot learning, Physical Review Physics Education Research, vol. 20(1), Article 010152.
Al Ghamdi, R. (2024). Exploring the impact of ChatGPT-generated feedback on technical writing skills of computing students: A blinded study, Education and Information Technologies, vol. 29, Article 18901.
Zhang, K. (2025). Enhancing critical writing through AI feedback: A randomized control study, Behavioral Sciences, vol. 15(5), Article 600.
Microsoft WorkLab (2024). 11 unexpected AI-at-work insights from 2024, URL: https://www.microsoft.com/en-us/worklab/11-unexpected-ai-at-work-insights-from-2024?utm_source=chatgpt.com, accessed on 24/11/2025.
Kinder, A., Briese, F. J., Jacobs, M., Dern, N., Glodny, N., Jacobs, S., and Leßmann, S. (2025). Effects of adaptive feedback generated by a large language model: A case study in teacher education, Computers and Education: Artificial Intelligence, vol. 8, Article 100349.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Journal of Learning Innovation and Technology

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Publishing Ethics
- The editorial team reserves the right to consider articles that meet the full format and specifications only. If the article does not meet the editorial requirements, the editors have the right to refuse to publish.
- To request a letter of acceptance for publication, the editorial office is issued only if the article is ready to be published unconditionally.
- The peer review of the Journal of Learning Innovation and Technology is final. The article may not be published in the specified volumes until the article has been reviewed and is ready to be published.
- Research related to the ethics of human and animal research must be reviewed by the Institutional Review Board (IRB)
- The submitted articles must not have been published in any other publication before and must not be under consideration by other journals. Published articles are copyright of the JLIT.