The Effect of AI-Based Recommendation System for Material Personalization on Vocational Student Satisfaction
DOI:
https://doi.org/10.70609/g-tech.v9i4.8091Keywords:
Vocational student satisfaction, Personalization of learning materials , AI-based recommendation systemAbstract
This study analyzes the influence of artificial intelligence (AI) based recommendation systems on the satisfaction of vocational students, focusing on two main variables: feature mapping and technological readiness. The research background is driven by the need for more adaptive and personalized learning, considering that conventional methods tend to be generic and overlook individual differences. Involving 183 vocational students selected through purposive sampling, the study employs a quantitative approach with descriptive and associative methods. Data were collected using valid and reliable questionnaires with a 1–5 Likert scale and analyzed using multiple linear regression. The results indicate that both feature mapping and technological readiness have a positive and significant influence on student satisfaction. Simultaneously, these two variables explain 43% of the variation in student satisfaction. Partially, feature mapping has the most dominant influence compared to technological readiness, indicating the importance of adaptive feature design in AI-based recommendation systems. This study proves that technology-based learning material personalization if supported by adequate infrastructure can enhance the learning experience and satisfaction of vocational students. Therefore, the study recommends the development of AI-based adaptive learning models that prioritize aspects of feature design and technological readiness to improve the effectiveness and quality of vocational education.
References
Almansour, M., & Alfhaid, F. M. (2024). Generative artificial intelligence and the personalization of health professional education: a narrative review. Medicine, 103(31), e38955. DOI: https://doi.org/10.1097/MD.0000000000038955
Bernacki, M. L., Greene, M. J., & Lobczowski, N. G. (2021). A systematic review of research on personalized learning: Personalized by whom, to what, how, and for what purpose (s)? Educational Psychology Review, 33(4), 1675–1715. DOI: https://doi.org/10.1007/s10648-021-09615-8
Cui, Q., & Fwuyuan, W. (2024). Adaptive learning strategies in higher vocational education: utilizing concise cases for diverse learning styles. International Journal of Instructional Cases, 8(2), 18–37.
Daga, A. T., Nasril, N., Ramli, A., Anwar, C., & Ridani, A. (2024). Analisis Peran Kecerdasan Buatan (Artificial Intelligences) dalam Transformasi Sistem Manajemen Pendidikan yang Bermutu di Era Metaverse.
Ellikkal, A., & Rajamohan, S. (2025). AI-enabled personalized learning: empowering management students for improving engagement and academic performance. Vilakshan-XIMB Journal of Management, 22(1), 28–44. DOI: https://doi.org/10.1108/XJM-02-2024-0023
Gustiawan, W., Sari, M. P., & Septivani, M. D. (2025). Menggagas Paradigma Baru Kurikulum : Strategi, Inovasi, dan Implementasi dalam Transformasi Pendidikan Vokasi. PENERBIT KBM INDONESIA.
Jaya, H., Haryoko, S., Anwar, B., & Kasau, S. (2024). Integration of Artificial Intelligence in Learning at Vocational Schools: Building Sustainable Collaboration for Educational Innovation in the Industrial Era 4.0. International Conference on Sciences, Technology and Education (ICSTE 2024), 127–139. DOI: https://doi.org/10.2991/978-2-38476-335-1_12
Kumar, S., Lee, J., & Park, H. (2024). Technological readiness as a critical enabler for AI adoption in higher education institutions. Journal of Research on Technology in Education, 1–15. DOI: https://doi.org/10.1504/IJTLID.2024.140316
Liu, K., Chen, J., Wei, M., & Chen, X. (2023). Research on the Sharing Mechanism of Vocational Education Resources Supported by Artificial Intelligence. Advances in Vocational and Technical Education, 5(7). DOI: https://doi.org/10.23977/avte.2023.050710
Mastam, N. M., Mokhtar, K., & Zaharudin, R. (2024). Bridging The Digital Divide In Malaysia: Enhancing Digital Literacy For Inclusive Students In Educational Systems. Asia Pacific Journal of Youth Studies (APJYS), 15(2), 111–131. DOI: https://doi.org/10.56390/apjys2024.6.128.6.6
Novelti, N., Devi, P. A. P., Khusnah, W. D., Marjuki, M., & Stevani, M. (2024). Pelatihan Teknis Pemanfaatan Artificial Intelligences Chat Gpt Dan Canva Bagi Guru SMK Dalam Membuat Media Pembelajaran Berbasis Masa Kini. Journal Of Human And Education (JAHE), 4(6), 1332–1339. DOI: https://doi.org/10.31004/jh.v4i6.2084
Park, S., Kim, H. K., Park, J., & Lee, Y. (2023). Designing and evaluating user experience of an AI-based defense system. IEEE Access, 11, 122045–122056. DOI: https://doi.org/10.1109/ACCESS.2023.3329257
Rahyasih, Y., Wijaya, W. M., & Syarifah, L. S. (2023). Exploring Vocational Students’ Satisfaction with Online Learning. Journal of Education and E-Learning Research, 10(3), 352–357. DOI: https://doi.org/10.20448/jeelr.v10i3.4668
Sahudra, T. M., Ramadhani, D., Kenedi, A. K., Wardana, M. R., & Khalil, N. A. (2023). Gaya belajar siswa sekolah dasar dan tes diagnostik: Membangun pembelajaran berdiferensiasi yang efektif dan inklusif. Deepublish.
Sitompul, R. P. (n.d.). Analisis faktor yang mempengaruhi penerimaan pengguna platform generative artificial intelligence sebagai perangkat pendukung proses pembelajaran dengan pendekatan extended technology acceptance. Fakultas Sains dan Teknologi UIN Syarif HIdayatullah Jakarta.
Smith, P., & Jones, R. K. (n.d.). Beyond technology: Non-technical determinants of student satisfaction with AI tools in vocational training. He International Journal of Information and Learning Technology, 40(2), 123–138.
Strielkowski, W., Grebennikova, V., Lisovskiy, A., Rakhimova, G., & Vasileva, T. (2025). AI‐driven adaptive learning for sustainable educational transformation. Sustainable Development, 33(2), 1921–1947. DOI: https://doi.org/10.1002/sd.3221
Suparyati, A., Widiastuti, I., Saputro, I. N., & Pambudi, N. A. (2023). The role of artificial intelligence (AI) in vocational education. JIPTEK: Jurnal Ilmiah Pendidikan Teknik Dan Kejuruan, 17(1). DOI: https://doi.org/10.20961/jiptek.v17i1.75995
Supriyatmoko, S., Anam, K., & Kurniawan, W. (2025). Model Pembelajaran Adaptif Berbasis Kecerdasan Buatan: Peluang Dan Tantangan Dalam Mewujudkan Pendidikan Personalisasi. STRATEGY: Jurnal Inovasi Strategi Dan Model Pembelajaran, 5(1), 36–45. DOI: https://doi.org/10.51878/strategi.v5i1.4944
Surya, A. (2024). Personalized Learning in Vocational Education: A Case Study of AI-Driven Recommendation Systems. Journal of Vocational Education Studies, 7(1), 88–105.
Surya, R. A. (2024). Implementation of Artificial Intelligence in Personalized Learning Systems. Journal of Vocational Education and Educational Technology Innovations, 1(2), 41–48.
Thongchotchat, V., Kudo, Y., Okada, Y., & Sato, K. (2023). Educational recommendation system utilizing learning styles: a systematic literature review. IEEe Access, 11, 8988–8999. DOI: https://doi.org/10.1109/ACCESS.2023.3238417
Widayanthi, D. G. C. (2024). AI in vocational education: Balancing digital skills and humanism. Indonesian Journal of Educational Inquiry, 1(2), 1–10.
Zheng, L., Long, M., Zhong, L., & Gyasi, J. F. (2022). The effectiveness of technology-facilitated personalized learning on learning achievements and learning perceptions: A meta-analysis. Education and Information Technologies, 27(8), 11807–11830. DOI: https://doi.org/10.1007/s10639-022-11092-7
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Intan Wulan Sari, Hilma Erliana, Cut Meurah Nurul ‘Akla, Nabilla Yudisha
This work is licensed under a Creative Commons Attribution 4.0 International License.
