A Systematic Review of Generative AI in Education: Implications for Non-Designer Educators in Microlearning Videos Production

Authors

  • Gladys Tagie Faculty of Art, Sustainability & Creative Industry, Universiti Pendidikan Sultan Idris, 35900, Tanjong Malim, Perak, Malaysia
  • Ahmad Zamzuri Mohamad Ali Faculty of Art and Design, Universiti Teknologi MARA Perak Branch, Seri Iskandar Campus, 32610, Seri Iskandar, Perak, Malaysia
  • Suraya Md Nasir Faculty of Art and Design, Universiti Teknologi MARA Perak Branch, Seri Iskandar Campus, 32610, Seri Iskandar, Perak, Malaysia

DOI:

https://doi.org/10.24191/idealogy.v11i2.954

Keywords:

Educator empowerment, Generative Artificial Intelligence (GenAI), Microlearning videos, Pedagogical design, Student engagement, Educator empowerment, Generative Artificial Intelligence (GenAi), Microlearning video, Pedagogical design, Student engagement

Abstract

Generative Artificial Intelligence (GenAI) is swiftly revolutionising educational approaches, offering innovative prospects for educators to generate and tailor digital learning resources. Yet, the present literature is scattered in its exploration of how GenAI can facilitate non-designer educators in the production of microlearning videos, especially in relation to pedagogical, design, and technical aspects. Hence the objective of this systematic  literature review is to synthesise current research on GenAI in education and evaluate its significance for supporting non-designer educators in the development of microlearning videos . Complying with the PRISMA framework, an extensive search of Web of Science and Scopus discovered 31 foundational papers published throughout the years 2023 to 2025. The selected studies were analysed through an integrative synthesis, with recurring findings organised into three themes: (1) GenAI as a pedagogical catalyst for microlearning video production; (2) Opportunities and challenges for non-designer educators in creating microlearning videos, and (3) The need for a conceptual framework to support non-designer educators in GenAI-supported microlearning video production. The findings indicate that GenAI can enhance educators’ efficiency and creative capacity by supporting content creation, personalisation, and the development of engaging learning resources. However, challenges remain in relation to design expertise, technical competency, ethical considerations, and institutional support. Overall, the review identifies a need for systematic guidance to support non-designer educators in applying GenAI effectively within microlearning video production. 

Author Biographies

Ahmad Zamzuri Mohamad Ali, Faculty of Art and Design, Universiti Teknologi MARA Perak Branch, Seri Iskandar Campus, 32610, Seri Iskandar, Perak, Malaysia

Prof. Ahmad Zamzuri Mohamad Ali Ais Professor of Multimedia in the Faculty of Art, Sustainability and Creative Industry, Universiti Pendidikan Sultan Idris, Malaysia. He has a PhD in Multimedia Design from Universiti Sains Malaysia (USM), a Master in Education and Bachelor Degree in Electrical Engineering from Universiti Teknologi Malaysia (UTM). Has taught both face-to-face and online classes in higher education for over 25 years. His research and publication interests are in the field of Instructional Technology. Specifically, in multimedia design and teaching and learning coding/programming.

Suraya Md Nasir, Faculty of Art and Design, Universiti Teknologi MARA Perak Branch, Seri Iskandar Campus, 32610, Seri Iskandar, Perak, Malaysia

Dr Suraya Md Nasir is a lecturer and visual storyteller specializing in multimedia creative design, with a focus on comics, animation, and participatory visual narratives. She holds a PhD in Art (Manga) from Kyoto Seika University. Currently serving at Universiti Pendidikan Sultan Idris (UPSI)], she is actively involved in teaching and research related to visual storytelling, participatory animation, and the intersection of culture, identity, and digital media. Her research interests include participatory visual methodologies, comics-based research, animation for cultural preservation, and narrative approaches to youth empowerment. She has contributed to several academic publications and creative projects, particularly in the areas of multimedia design, cultural storytelling, and community-based creative practices.

References

AIAli, R., Wardat, Y., Al-Saud, K., & Alhayek, K. A. (2024). Generative AI in Education: Best Practices for Successful Implementation. International Journal of Religion, 5(9), 1016–1025. https://doi.org/10.61707/pkwb8402

Abramenka-Lachheb, V., Lachheb, A., & Ozogul, G. (2025). Value-sensitive design in the praxis of instructional design: A view of designers in situ. British Journal of Educational Technology, 56, 1311-1349.https://doi.org/10.1111/bjet.13574

Alias, N. F., & Abdul Razak, R. (2023). Exploring the pedagogical aspects of microlearning in educational settings: A systematic literature review. Malaysian Journal of Learning and Instruction, 20(2), 267–294. https://doi.org/10.32890/mjli2023.20.2.3

Balasundaram, S., Mathew, J., & Nair, S. (2024). Microlearning and learning performance in higher education: A post-test control group study. Journal of Learning for Development, 11(1), 1–14. https://doi.org/10.56059/jl4d.v11i1.752

Bahroun, Z., Anane, C., Ahmed, V., & Zacca, A. (2023). Transforming Education: A Comprehensive Review of Generative Artificial Intelligence in Educational Settings through Bibliometric and Content Analysis. Sustainability, 15(17), 12983. https://doi.org/10.3390/su151712983

Cacho, R. M. (2024). Integrating generative AI in university teaching and learning: A model for balanced guidelines. Online Learning Journal, 28(3), 4508. https://doi.org/10.24059/olj.v28i3.4508

Chan, C. K. Y. (2024). Holistic competencies and AI in education: A synergistic pathway. Australasian Journal of Educational Technology, 40(1), 14742. https://doi.org/10.14742/ajet.10191

Chen, S.-Y. (2023). Generative AI, learning and new literacies. Journal of Educational Technology Development and Exchange, 16(2), 1–19. https://doi.org/10.18785/jetde.1602.01

Chiu, T. K. F. (2023). The impact of Generative AI (GenAI) on practices, policies and research direction in education: a case of ChatGPT and Midjourney. Interactive Learning Environments, 32(10), 6187–6203. https://doi.org/10.1080/10494820.2023.2253861

Cordero, J., Torres-Zambrano, J., & Cordero-Castillo, A. (2025). Integration of Generative Artificial Intelligence in Higher Education: Best Practices. Education Sciences, 15(1), 32. https://doi.org/10.3390/educsci15010032

Creely, E., & Blannin, J. (2025). Creative partnerships with generative AI: Possibilities for education and beyond. Thinking Skills and Creativity, 47, 101727. https://doi.org/10.1016/j.tsc.2024.101727

Cukurova, M. (2025). The interplay of learning, analytics and artificial intelligence in education: A vision for hybrid intelligence. British Journal of Educational Technology, 56(2), 469–488. https://doi.org/10.1111/bjet.13514

Delello, J. A., Watters, J. B., & Garcia-Lopez, A. (2024). Artificial intelligence in education: Transforming learning and teaching. In J. A. Delello & R. R. McWhorter (Eds.), Disruptive technologies in education and workforce development (pp. 1–26). IGI Global. https://doi.org/10.4018/979-8-3693-3003-6.ch001

Elsaiary, R. (2025). Transforming Best Practices and Empowering Educators. In A. ElSayary (Ed.), Prompt Engineering and Generative AI Applications for Teaching and Learning (pp. 161-172). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-7332-3.ch010

Farrelly, T., & Baker, N. (2023). Generative Artificial Intelligence: Implications and Considerations for Higher Education Practice. Education Sciences, 13(11), 1109. https://doi.org/10.3390/educsci13111109

Francis, N. J., Jones, S., & Smith, D. P. (2025). Generative AI in higher education: Balancing innovation and integrity. British Journal of Biomedical Science, 81, 14048. https://doi.org/10.3389/bjbs.2024.14048

Gutierrez-Gonzalez, R., Zamarron, A., & Royuela, A. (2024). Video-based lecture engagement in a flipped classroom environment. BMC Medical Education, 24, 1218. https://doi.org/10.1186/s12909-024-06228-x

Giurgiu, L. (2017). Microlearning: An evolving eLearning trend. Scientific Bulletin, 22(1), 18–23. https://doi.org/10.1515/bsaft-2017-0003

Haroud, S., & Saqri, N. (2025). Generative AI in higher education: Teachers’ and students’ perspectives on support, replacement, and digital literacy. Education Sciences, 15(4), 396. https://doi.org/10.3390/educsci15040396

Hassan, K., Denny, P., Moore, S., & Stamper, J. (2023). Learnersourcing in the age of AI: Student, educator and machine partnerships for content creation. Computers and Education: Artificial Intelligence, 5, 100151. https://doi.org/10.1016/j.caeai.2023.100151

Hazzan-Bishara, A., Kol, O., & Levy, S. (2025). The factors affecting teachers’ adoption of AI technologies: A unified model of external and internal determinants. Education and Information Technologies,30,15043-15049. https://doi.org/10.1007/s10639-025-13393-z

Hwang, Y., & Wu, Y. (2025). Graphic design education in the era of text-to-image generation: Transitioning to contents creator. Journal of Art & Design Education, 44(1) 239-253. https://doi.org/10.1111/jade.12558

Jayaweera, I. G. U. D. (2025). Revolutionizing education: Generative AI as a catalyst for personalized learning and innovative teaching practices. In 2025 5th International Conference on Advanced Research in Computing (ICARC) (pp. 1–6). Belihuloya, Sri Lanka. IEEE. https://doi.org/10.1109/ICARC64760.2025.10962979

Kanbach, D. K., Heiduk, L., Blueher, G., Schreiter, M., & Lahmann, A. (2024). The GenAI is out of the bottle: Generative artificial intelligence from a business model innovation perspective. Review of Managerial Science, 18(4), 1189–1220. https://doi.org/10.1007/s11846-023-00696-z

Karataş, F., Eriçok, B., & Tanrikulu, L. (2025). Reshaping curriculum adaptation in the age of artificial intelligence: Mapping teachers’ AI-driven curriculum adaptation patterns. British Educational Research Journal, 51(1), 154–180. https://doi.org/10.1002/berj.4068

Kong, S.-C., & Yang, Y. (2024). A human-centered learning and teaching framework using generative artificial intelligence for self-regulated learning development through domain knowledge learning in K–12 settings. IEEE Transactions on Learning Technologies, 17, 1562–1573. https://doi.org/10.1109/TLT.2024.3392830

Kurtz, G., Amzalag, M., Shaked, N., Zaguri, Y., Kohen-Vacs, D., Gal, E., Zailer, G., & Barak-Medina, E. (2024). Strategies for integrating generative AI into higher education: Navigating challenges and leveraging opportunities. Education Sciences, 14(5), 503. https://doi.org/10.3390/educsci14050503

Lee, Y.-L., & Lui, N. P. (2024). Re-embracing orality in digital education: The pedagogical affordances of podcasting in the era of generative AI. Frontiers in Education, 9, 1447015. https://doi.org/10.3389/feduc.2024.1447015

Liang, Y., & Lu, J. (2025). How school support influences the content creation of pre-service teachers’ instructional design. Behavioral Sciences, 15(5), 568. https://doi.org/10.3390/bs15050568

Magri, R., Gaglieri, C., Alarcon, R. T., de Souza, A. R., & Bannach, G. (2022). Microlearning as a tool for scientific dissemination: Thermal analysis of the Portuguese good luck rooster. Química Nova, 45(2), 245–248. https://doi.org/10.21577/0100-4042.20170836

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), 856. https://doi.org/10.3390/educsci13090856

Mulyani, H., Istiaq, M. A., Shauki, E. R., Kurniati, F., & Arlinda, H. (2025). Transforming education: exploring the influence of generative AI on teaching performance. Cogent Education, 12(1). https://doi.org/10.1080/2331186X.2024.2448066

Nartey, E. K. (2024). Guiding principles of generative AI for employability and learning in UK universities. Cogent Education, 11(1). https://doi.org/10.1080/2331186X.2024.2357898

Nonthamand, N. (2024). Designing the video-based learning environments using workflow and scaffolding to enhance self-instructional video production ability of pre-service teacher. Contemporary Educational Technology, 16(1), ep492. https://doi.org/10.30935/cedtech/14102

Noroozi, O., Soleimani, S., Farrokhnia, M., & Banihashem, S. K. (2024). Generative AI in education: Pedagogical, theoretical, and methodological perspectives. International Journal of Technology in Education, 7(2), 845. https://doi.org/10.46328/ijte.845

Ochoa, X., Huang, X., & Shao, Y. (2025). Exploring the Potential of Generative AI to Support Non-experts in Learning Analytics Practice. Journal of Learning Analytics, 12(1), 65-90. https://doi.org/10.18608/jla.2025.8615

Peláez-Sánchez, I. C., Velarde-Camaqui, D., & Glasserman-Morales, L. D. (2024). The impact of large language models on higher education: Exploring the connection between AI and Education 4.0. Frontiers in Education, 9, 1392091. https://doi.org/10.3389/feduc.2024.1392091

Ruiz-Rojas, L. I., Salvador-Ullauri, L., & Acosta-Vargas, P. (2024). Collaborative Working and Critical Thinking: Adoption of Generative Artificial Intelligence Tools in Higher Education. Sustainability, 16(13), 5367. https://doi.org/10.3390/su16135367

Ruiz-Rojas, L. I., Acosta-Vargas, P., De-Moreta-Llovet, J., & Gonzalez-Rodriguez, M. (2023). Empowering education with generative artificial intelligence tools: Approach with an instructional design matrix. Sustainability, 15(15), 11524. https://doi.org/10.3390/su151511524

Sagin, F. G., Özkaya, A. B., Tengiz, F., Geyik, Ö. G., & Geyik, C. (2023). Current evaluation and recommendations for the use of artificial intelligence tools in education. Turkish Journal of Biochemistry, 48(6), 617–626. https://doi.org/10.1515/tjb-2023-0254

Saúde, S., Barros, J. P., & Almeida, I. (2024). Impacts of generative artificial intelligence in higher education: Research trends and students’ perceptions. Social Sciences, 13(8), 410. https://doi.org/10.3390/socsci13080410

Şimşek, A. S., Cengiz, G. Ş. T., & Bal, M. (2025). Extending the TAM framework: Exploring learning motivation and agility in educational adoption of generative AI. Education and Information Technologies, 30, 20913–20942. https://doi.org/10.1007/s10639-025-13591-9

Stefaniak, J. E., & Moore, S. L. (2025). The use of generative AI to support inclusivity and design deliberation for online instruction. Online Learning Journal, 28(3), Article 4458. https://doi.org/10.24059/olj.v28i3.4458

Sumalinog, G. G. (2022). Barriers of online education in the new normal: Teachers’ perspectives. International Journal of Learning, Teaching and Educational Research, 21(1), 33–50. https://doi.org/10.26803/ijlter.21.1.3

Suresh Babu, C. V., William, M. P., & Kowsika, S. (2025). Generative AI tools and education: Enabling collaborative intelligence through ChatGPT, Canva, InVideo AI, and InShot. In Handbook of generative AI in education (pp. 300–325). IGI Global. https://doi.org/10.4018/979-8-3693-8332-2.ch019

Theodorio, A. O. (2024). Examining the support required by educators for successful technology integration in teacher professional development programs. Cogent Education, 11(1) https://doi.org/10.1080/2331186X.2023.2298607

Van Den Berg, G. (2024). Generative AI and educators: Partnering in using open digital content for transforming education. Open Praxis, 16(2), 640. https://doi.org/10.55982/openpraxis.16.2.640

Vartiainen, H., Liukkonen, P., & Tedre, M. (2025). Emerging human-technology relationships in a co-design process with generative AI. Thinking Skills and Creativity, 47, 101742. https://doi.org/10.1016/j.tsc.2024.101742

Walczak, K., & Cellary, W. (2023). Challenges for higher education in the era of widespread access to generative AI. Economics and Business Review, 9(2), Article 743. https://doi.org/10.18559/ebr.2023.2.743

Downloads

Published

2026-09-01

Most read articles by the same author(s)