Strengthening Vocational Teachers' AI Literacy through NotebookLM Training: A Community-Based Initiative for Sustainable AI Integration in Vocational Education
DOI:
https://doi.org/10.33394/jpu.v7i3.21947Keywords:
Artificial Intelligence (AI) Literacy, NotebookLM, Teacher Professional Development, Vocational Education, Digital CompetenceAbstract
This community service program aims to enhance vocational high school (SMK) teachers' AI literacy through NotebookLM training and to formulate practical strategies for the sustainable integration of artificial intelligence into vocational education. The program involved 35 SMK teachers and was implemented through a series of workshops, hands-on practice sessions, mentoring, and reflective discussions. Program effectiveness was evaluated using a one-group pretest-posttest design. Data were collected through validated pre-test and post-test instruments and analyzed using the Wilcoxon Signed-Rank Test and Normalized Gain (N-Gain) analysis. The results showed a statistically significant improvement in participants' understanding of NotebookLM, with mean post-test scores exceeding pre-test scores and an overall moderate N-Gain. The greatest learning gains were observed in participants' understanding and use of the Audio Overviews, Source Grounding, and Data Security features. Participants also reported increased confidence in integrating AI into instructional planning and classroom learning activities. Despite these positive outcomes, challenges related to digital infrastructure, varying levels of AI literacy, and teachers' readiness remained important considerations for wider implementation. These findings suggest that NotebookLM-based professional development can effectively enhance teachers' AI literacy while supporting the pedagogically meaningful integration of AI into vocational education. Continuous professional development, institutional support, equitable access to digital infrastructure, and collaboration with industry partners are essential to sustain AI adoption in vocational schools.
References
Alam, R. G., & Hidayah, A. K. (2025). Critical Success Factors of ICT Implementation in Vocational High Schools. Jurnal Teknologi Informasi Dan Pendidikan, 18(2), 1051–1062. https://doi.org/10.24036/jtip.v18i2.958
Anwar, C., Sofyan, H., Ratnaningsih, N., & Muh. Asriadi, A. M. (2024). Digital technology practices for vocational teachers in the industrial revolution 4.0: Mediating technology self-efficacy. Journal of Pedagogical Research, 8(1), 172–190. https://doi.org/10.33902/JPR.202424585
Aryadoust, V., Ng, L. Y., & Sayama, H. (2021). A comprehensive review of Rasch measurement in language assessment: Recommendations and guidelines for research. Language Testing, 38(1), 6–40. https://doi.org/10.1177/0265532220927487
Astuti, M., Sudira, P., Mutohhari, F., & Nurtanto, M. (2021). Competency of Digital Technology: The Maturity Levels of Teachers and Students in Vocational Education in Indonesia. Journal of Education Technology, 5(2), 254–262. https://ejournal.undiksha.ac.id/index.php/JET
Bond, T. G., Yan, Z., & Heene, M. (2021). Applying the Rasch Model: Fundamental Measurement in the Human Sciences (4th ed). Routledge. https://doi.org/10.4324/9780429030499
Çelik, H., & Dost, M. T. (2025). The Effect of Psychological Flexibility, Meaning in Life, and Work Engagement on Teacher Burnout. International Journal of Psychology and Educational Studies, 12(3), 214–227. https://doi.org/10.52380/ijpes.2025.12.3.1405
Chiu, T. K. F., Ahmad, Z., & Çoban, M. (2025). Development and validation of teacher artificial intelligence (AI) competence self-efficacy (TAICS) scale. Education and Information Technologies, 30(5), 6667–6685. https://doi.org/10.1007/s10639-024-13094-z
Creswell, J. W., & Creswell, J. D. (2023). Research Design: Qualitative, Quantitative and Mixed Methods Approaches. Sage Publications. https://www.scirp.org/reference/referencespapers?referenceid=3784840
Daengs, G. S. A., Ginantra, N. L. W. S. R., Afriliansyah, T., Wanto, A., & Okprana, H. (2024). Workshop Pemanfaatan AI untuk Meningkatkan Literasi Digital Guru-Guru SMK dalam Proses Pembelajaran di Sekolah. PaKMas: Jurnal Pengabdian Kepada Masyarakat, 4(1), 224–233. https://doi.org/10.54259/pakmas.v4i1.2838
Dihan, Q. A., Nihalani, B. R., Tooley, A. A., & Elhusseiny, A. M. (2025). Eyes on Google’s NotebookLM: using generative AI to create ophthalmology podcasts with a single click. In Eye (Basingstoke) (Vol. 39, Number 2, pp. 215–216). Springer Nature. https://doi.org/10.1038/s41433-024-03481-8
Field, A. P. (2024). Discovering statistics using SPSS. Sage publications limited. https://books.google.com/books?id=83L2EAAAQBAJ
Gaeta, L., & Brydges, C. R. (2020). An examination of effect sizes and statistical power in speech, language, and hearing research. Journal of Speech, Language, and Hearing Research, 63(5), 1572–1580. https://doi.org/10.1044/2020_JSLHR-19-00299
Gozali, A. A., & Ciftady, D. (2025). Peningkatan Kompetensi Guru SMK melalui Literasi dan Pemanfaatan Generative AI untuk Pengembangan Pembelajaran Inovatif. COSECANT: Community Service and Engagement, 5, 114–117. https://journals.telkomuniversity.ac.id/cosecant/article/view/10333
Habibi, A., Sofyan, S., & Mukminin, A. (2023). Factors affecting digital technology access in vocational education. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-32755-6
Hake, R. R. (1999). Analyzing change/gain scores. https://scispace.com/pdf/analyzing-change-gain-scores-2flqldd4zo.pdf
Jatmoko, D., Suyitno, S., Rasul, M. S., Nurtanto, M., Kholifah, N., Masek, A., & Nur, H. R. (2023). The Factors Influencing Digital Literacy Practice in Vocational Education: A Structural Equation Modeling Approach. European Journal of Educational Research, 12(2), 1109–1121. https://doi.org/10.12973/eu-jer.12.2.1109
Kamalov, F., Santandreu Calonge, D., & Gurrib, I. (2023). New Era of Artificial Intelligence in Education: Towards a Sustainable Multifaceted Revolution. Sustainability (Switzerland), 15(16). https://doi.org/10.3390/su151612451
Kemendikbudristekdikti. (2022). Kurikulum Merdeka: Panduan Pengembangan Kurikulum. https://kemdiktisaintek.go.id/library/book/panduan-penyusunan-kurikulum-pendidikan-tinggi-mendukung-merdeka-belajar-kampus-merdeka-menuju-indonesia-emas
Kharbach, M. (2026). Unexpected Ways to Use NotebookLM with Your Students. https://medkharbach.com/wp-content/uploads/2026/01/10-Unexpected-Ways-to-Use-NotebookLM-with-Your-Students.pdf
Li, M., & Wilson, J. (2025). AI-Integrated Scaffolding to Enhance Agency and Creativity in K-12 English Language Learners: A Systematic Review. In Information (Switzerland) (Vol. 16, Number 7). Multidisciplinary Digital Publishing Institute (MDPI). https://doi.org/10.3390/info16070519
Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054. https://rediie.cl/wp-content/uploads/Mishra-Koehler.pdf
Muslim, R., & Ariyanto, E. D. (2025). Digital literacy as a catalyst for future workforce: enhancing vocational high school graduates’ employability in the evolving digital economy Evidence from Indonesia. Literate: International Journal of Social Science and Humanities, 3(1), 44–57. https://doi.org/10.52005/literate.v3i1.29
Ning, Y., Zhang, C., Xu, B., Zhou, Y., & Wijaya, T. T. (2024). Teachers’ AI-TPACK: Exploring the Relationship between Knowledge Elements. Sustainability (Switzerland), 16(3). https://doi.org/10.3390/su16030978
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric Theory (3rd ed.). McGraw-Hill. https://doi.org/10.1177/014662169501900308
Rais, M., Putra, K. P., Syahid, M., Wahid, N., & Hidayat, M. A. (2025). PKM Pelatihan Partisipatif AI Prompting bagi Guru SMK dalam Meningkatkan Keterampilan Digital 1. Journal of Engineering Service and Innovation, 1(1), 44–54. https://journal.unm.ac.id/index.php/JESI/article/view/10307
Reuter, M., Philippone, M., Benton, B., & Dilley, L. (2025). Generative AI in clinical practice: novel qualitative evidence of risk and responsible use of Google’s NotebookLM. In Eye (Basingstoke) (Vol. 39, Number 8, pp. 1650–1652). Springer Nature. https://doi.org/10.1038/s41433-025-03817-y
Reyna, J. (2025). The Potential of Google NotebookLM for Teaching and Learning. https://www.academia.edu/download/123907198/NotebookLM_paper_FINAL_2.pdf
Rosyanto, R., Wahyudin, D., & Hernawan, A. H. (2025). ADDIE-based AI training using open-source LMS for vocational teachers. Curricula: Journal of Curriculum Development, 4(2), 979–992. https://doi.org/10.17509/curricula.v4i2.87744
Setiyawan, A., Soeharto, S., Wijaya, T. T., Korenova, L., & Lavicza, Z. (2025). Measuring Teachers’ competencies for AI integration: Development and validation of the AI-TPACK in vocational education. Computers and Education Open, 9. https://doi.org/10.1016/j.caeo.2025.100319
Sheskin, D. J. (2020). Handbook of Parametric and Nonparametric Statistical Procedures (Fifth Edition). Chapman and hall/CRC. https://taylorfrancis.com/books/mono/10.1201/9781420036268
Shulman, L. S. (2013). Those who understand: Knowledge growth in teaching. Journal of Education, 193(3), 1–11. https://doi.org/10.1177/002205741319300302
Taber, K. S. (2018). The Use of Cronbach’s Alpha When Developing and Reporting Research Instruments in Science Education. Research in Science Education, 48(6), 1273–1296. https://doi.org/10.1007/s11165-016-9602-2
Tufino, E. (2025). NotebookLM as a Socratic physics tutor: Design and preliminary observations of a RAG-based tool. http://arxiv.org/abs/2504.09720
Wahjusaputri, S., & Nastiti, T. I. (2022). Digital literacy competency indicator for Indonesian high vocational education needs. Journal of Education and Learning (EduLearn), 16(1), 85–91. https://doi.org/10.11591/edulearn.v16i1.20390
Wahjusaputri, S., Nastiti, T. I., Bunyamin, B., Sukmawati, W., & Johan, J. (2024). Development of Teaching Factory Model-Based Artificial Intelligence: Improving the Quality of Learning Vocational Schools in Indonesia. AL-ISHLAH: Jurnal Pendidikan, 16(4). https://doi.org/10.35445/alishlah.v16i4.5979
Wetria, W., & Supratman, S. (2025). Peran Artificial Intelligence dalam meningkatkan layanan pendidikan di SMK. Journal of Education, Cultural and Politics, 5(3), 626–637. https://jecco.ppj.unp.ac.id/index.php/jecco/article/view/873
World Bank. (2021). World Development Report 2021: Data for Better Lives. https://wdr2021.worldbank.org/
Wulff, P., Mientus, L., Nowak, A., & Borowski, A. (2025). AI in STEM Teacher Education: Inquiry into Capabilities of an Emerging Technology. International Journal of Technology in Education and Science, 9(4), 597–618. https://doi.org/10.46328/ijtes.5105
Yusro, M., Misin, R., & Mauludin, M. A. (2024). Vocational Education Development Strategy in the Use of Artificial Intelligence in the Digital Era. 5th Vocational Education International Conference, 734–741. https://doi.org/10.2991/978-2-38476-198-2_100
Downloads
Published
How to Cite
Issue
Section
Citation Check
License
Copyright (c) 2026 The Author(s)

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).



