MENTORING TEACHERS IN LEARNING INNOVATION MANAGEMENT USING ARTIFICIAL INTELLIGENCE LEARNING MANAGEMENT SYSTEMS AND VIRTUAL REALITY FOR SCHOOL DIGITAL TRANSFORMATION
DOI:
https://doi.org/10.37478/mahajana.v7i3.8693Abstract
School digital transformation requires teachers to manage pedagogical innovation rather than merely adopt devices. This community service program aimed to strengthen teachers' capacity at SMA Negeri 12 Ambon through integrated mentoring in artificial intelligence (AI), learning management systems (LMS), and virtual reality (VR). The program used a learning innovation management mentoring model comprising coordination, needs analysis, resource design, technical-pedagogical training, guided implementation, and evaluation. The intensive on-site phase was conducted on 1-4 September 2026, while program evidence was documented through attendance records, LMS credential lists, training materials, asset handover records, and institutional cooperation documents. Documented outputs include participation records with 50 numbered entries, the preparation of 44 teacher LMS accounts, the distribution of 50 copies of the training book Mengajar Lebih Cerdas [Teaching Smarter], and the transfer of four Shinecon 6.0 VR Box units with headphones. The activity was also institutionalized through cooperation and implementation agreements between Universitas Pattimura and SMA Negeri 12 Ambon. These outputs indicate that the program established access, learning resources, and institutional support needed for continued digital innovation. Follow-up should verify competency gains through prospective pre-test and post-test measures in the next mentoring cycle, LMS analytics, digital portfolios, and monitoring of reusable AI-LMS-VR learning products.
Downloads
Keywords:
artificial intelligence, learning management system, school digital transformation, virtual realityReferences
Ali, O., Murray, P. A., Momin, M., Dwivedi, Y. K., & Malik, T. (2024). The effects of artificial intelligence applications in educational settings: Challenges and strategies. Technological Forecasting and Social Change, 199, 123076. https://doi.org/10.1016/j.techfore.2023.123076
Bond, M., Bedenlier, S., Marín, V. I., & Händel, M. (2021). Emergency remote teaching in higher education: Mapping the first global online semester. International Journal of Educational Technology in Higher Education, 18(1), 50. https://doi.org/10.1186/s41239-021-00282-x
Celik, I. (2023). Towards Intelligent-TPACK: An empirical study on teachers’ professional knowledge to ethically integrate artificial intelligence (AI)-based tools into education. Computers in Human Behavior, 138, 107468. https://doi.org/10.1016/j.chb.2022.107468
Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: The state of the field. International Journal of Educational Technology in Higher Education, 20(1), 22. https://doi.org/10.1186/s41239-023-00392-8
Desimone, L. M. (2009). Improving impact studies of teachers’ professional development: Toward better conceptualizations and measures. Educational Researcher, 38(3), 181-199. https://doi.org/10.3102/0013189X08331140
Ertmer, P. A., & Ottenbreit-Leftwich, A. T. (2010). Teacher technology change: How knowledge, confidence, beliefs, and culture intersect. Journal of Research on Technology in Education, 42(3), 255-284. https://doi.org/10.1080/15391523.2010.10782551
Ertmer, P. A., Ottenbreit-Leftwich, A. T., Sadik, O., Sendurur, E., & Sendurur, P. (2012). Teacher beliefs and technology integration practices: A critical relationship. Computers & Education, 59(2), 423-435. https://doi.org/10.1016/j.compedu.2012.02.001
Falloon, G. (2020). From digital literacy to digital competence: the teacher digital competency (TDC) framework. Educational Technology Research and Development, 68(5), 2449-2472. https://doi.org/10.1007/s11423-020-09767-4
Hamilton, D., McKechnie, J., Edgerton, E., & Wilson, C. (2021). Immersive virtual reality as a pedagogical tool in education: A systematic literature review of quantitative learning outcomes and experimental design. Journal of Computers in Education, 8(1), 1-32. https://doi.org/10.1007/s40692-020-00169-2
Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Buckingham Shum, S., Santos, O. C., Rodrigo, M. T., Cukurova, M., Bittencourt, I. I., & Koedinger, K. R. (2022). Ethics of AI in education: Towards a community-wide framework. International Journal of Artificial Intelligence in Education, 32(3), 504-526. https://doi.org/10.1007/s40593-021-00239-1
Hrastinski, S. (2019). What do we mean by blended learning? TechTrends, 63(5), 564-569. https://doi.org/10.1007/s11528-019-00375-5
Instefjord, E. J., & Munthe, E. (2017). Educating digitally competent teachers: A study of integration of professional digital competence in teacher education. Teaching and Teacher Education, 67, 37-45. https://doi.org/10.1016/j.tate.2017.05.016
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. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
Lindfors, M., Pettersson, F., & Olofsson, A. D. (2021). Conditions for professional digital competence: The teacher educators’ view. Education Inquiry, 12(4), 390-409. https://doi.org/10.1080/20004508.2021.1890936
Makransky, G., & Petersen, G. B. (2021). The Cognitive Affective Model of Immersive Learning (CAMIL): A theoretical research-based model of learning in immersive virtual reality. Educational Psychology Review, 33(3), 937-958. https://doi.org/10.1007/s10648-020-09586-2
Makransky, G., Terkildsen, T. S., & Mayer, R. E. (2019). Adding immersive virtual reality to a science lab simulation causes more presence but less learning. Learning and Instruction, 60, 225-236. https://doi.org/10.1016/j.learninstruc.2017.12.007
Miao, F., & Cukurova, M. (2024). AI competency framework for teachers. UNESCO. https://doi.org/10.54675/ZJTE2084
Miao, F., & Holmes, W. (2023). Guidance for generative AI in education and research. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000386693
Miao, F., Holmes, W., Huang, R., & Zhang, H. (2021). AI and education: Guidance for policy-makers. UNESCO. https://doi.org/10.54675/PCSP7350
Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017-1054. https://doi.org/10.1111/j.1467-9620.2006.00684.x
OECD. (2023). OECD Digital Education Outlook 2023: Towards an effective digital education ecosystem. OECD Publishing. https://doi.org/10.1787/b12e15ef-en
Parong, J., & Mayer, R. E. (2018). Learning science in immersive virtual reality. Journal of Educational Psychology, 110(6), 785-797. https://doi.org/10.1037/edu0000241
Pellas, N., Dengel, A., & Christopoulos, A. (2020). A scoping review of immersive virtual reality in STEM education. IEEE Transactions on Learning Technologies, 13(4), 748-761. https://doi.org/10.1109/TLT.2020.3019405
Philipsen, B., Tondeur, J., Pareja Roblin, N., Vanslambrouck, S., & Zhu, C. (2019). Improving teacher professional development for online and blended learning: A systematic meta-aggregative review. Educational Technology Research and Development, 67(5), 1145-1174. https://doi.org/10.1007/s11423-019-09645-8
Radianti, J., Majchrzak, T. A., Fromm, J., & Wohlgenannt, I. (2020). A systematic review of immersive virtual reality applications for higher education: Design elements, lessons learned, and research agenda. Computers & Education, 147, 103778. https://doi.org/10.1016/j.compedu.2019.103778
Rasheed, R. A., Kamsin, A., & Abdullah, N. A. (2020). Challenges in the online component of blended learning: A systematic review. Computers & Education, 144, 103701. https://doi.org/10.1016/j.compedu.2019.103701
Redecker, C. (2017). European framework for the digital competence of educators: DigCompEdu. Publications Office of the European Union. https://doi.org/10.2760/159770
Scherer, R., Siddiq, F., & Tondeur, J. (2019). The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education. Computers & Education, 128, 13-35. https://doi.org/10.1016/j.compedu.2018.09.009
Tene, T., Marcatoma Tixi, J. A., Palacios Robalino, M. L., Mendoza Salazar, M. J., Vacacela Gomez, C., & Bellucci, S. (2024). Integrating immersive technologies with STEM education: A systematic review. Frontiers in Education, 9, 1410163. https://doi.org/10.3389/feduc.2024.1410163
Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023). What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart Learning Environments, 10(1), 15. https://doi.org/10.1186/s40561-023-00237-x
Tondeur, J., van Braak, J., Ertmer, P. A., & Ottenbreit-Leftwich, A. (2017). Understanding the relationship between teachers’ pedagogical beliefs and technology use in education: A systematic review of qualitative evidence. Educational Technology Research and Development, 65(3), 555-575. https://doi.org/10.1007/s11423-016-9481-2
Tondeur, J., van Braak, J., Sang, G., Voogt, J., Fisser, P., & Ottenbreit-Leftwich, A. (2012). Preparing pre-service teachers to integrate technology in education: A synthesis of qualitative evidence. Computers & Education, 59(1), 134-144. https://doi.org/10.1016/j.compedu.2011.10.009
Trust, T., Krutka, D. G., & Carpenter, J. P. (2016). “Together we are better”: Professional learning networks for teachers. Computers & Education, 102, 15-34. https://doi.org/10.1016/j.compedu.2016.06.007
Vescio, V., Ross, D., & Adams, A. (2008). A review of research on the impact of professional learning communities on teaching practice and student learning. Teaching and Teacher Education, 24(1), 80-91. https://doi.org/10.1016/j.tate.2007.01.004
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 39. https://doi.org/10.1186/s41239-019-0171-0
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Paul Arjanto, Desembra Sohilait, Nandalita Nunuela, Estin Indria Maahury, Izak Jakobis Makulua, Muhammad Yusril Musiin, Lifia Meiliza Wiyono

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
The authors and other parties are bound to the Attribution-ShareAlike 4.0 International license (CC BY-SA 4.0 DEED) for the published articles. This permits users to:
Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
Adapt — remix, transform, and build upon the material for any purpose, even commercially.
The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.



