AI Readiness in 21st-Century Islamic Education: Teachers Behavioral Intentions and Perceived Control
DOI:
https://doi.org/10.22437/teknopedagogi.v15i2.42852Keywords:
Artificial Intelligence, Islamic Religious Education, Theory of Planned BehaviorAbstract
This study investigates the determinants of AI adoption among Islamic Religious Education teachers within the 21st-century learning paradigm. Grounded in the TPB, it examines how attitudes, subjective norms, and perceived behavioral control shape teachers’ intentions and actual behaviors regarding AI integration. A quantitative survey was conducted via online questionnaires distributed to 150 islamic religious education teachers in Tanjung Jabung Barat Regency, Jambi. Data were analyzed using SmartPLS 3 for PLS-SEM. Results indicate that perceived behavioral control was the most significant predictor, strongly influencing intention with coefficient = 0.586, p <0.001 and behavior with coefficient = 0.300, p = 0.021. Subjective norms also significantly affected intention with coefficient = 0.278, p = 0.001. Conversely, attitudes had no direct impact on intention (p = 0.681) but significantly predicted behavior with coefficient = 0.432, p <0.001. The model demonstrated strong explanatory power. Accounting for 65.8% of intention variance and 78.9% of behavior variance, affirming TPB’s efficacy in understanding technology adoption among Islamic religious education teachers. These findings underscore the critical role of teachers’ self-efficacy and social influence in AI adoption. Practical interventions, such as hands-on training and fostering supportive environments, are essential for successful integration. Future research could explore mediating variables or qualitative approaches to deepen understanding of barriers and facilitators.
Downloads
References
Abdillah, A., & Astutik, A. P. (2024). Pemanfaatan teknologi dalam pembelajaran pendidikan agama islam di SD. MODELING: Jurnal Program Studi PGMI, 11(1). https://jurnal.stitnualhikmah. ac.id/index.php/modeling/article/view/2497
Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes. The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2). https://doi.org/10.1016/0749-5978(91)90020-T
Ajzen, I. (2011). The theory of planned behaviour: Reactions and reflections. Psychology and Health, 26(9), 1113–1127. https://doi.org/10.1080/08870446.2011.613995
Bakti, I. K., Zulkarnain, Yarun, A., Rusdi, Syaifudin, M., & Syafaq, H. (2023). The role of Artificial Intelligence in education: A systematic literature review. Jurnal Iqra’ : Kajian Ilmu Pendidikan, 8(2), 182–197. https://doi.org/10.25217/ji.v8i2.3194
Bosnjak, M., Ajzen, I., & Schmidt, P. (2020). The theory of planned behavior: Selected recent advances and applications. In Europe’s Journal of Psychology, 16(3), 352–356. PsychOpen. https://doi.org/10.5964/ejop.v16i3.3107
Cirignano, S. M. (2023). New resources for nutrition educators. Journal of Nutrition Education and Behavior, 55(6), 464. https://doi.org/10.1016/j.jneb.2023.01.008
Connell, J., Carlton, J., Grundy, A., Taylor Buck, E., Keetharuth, A. D., Ricketts, T., Barkham, M., Robotham, D., Rose, D., & Brazier, J. (2018). The importance of content and face validity in instrument development: lessons learnt from service users when developing the Recovering Quality of Life measure (ReQoL). Quality of Life Research, 27(7), 1893–1902. https://doi.org/10.1007/s11136-018-1847-y
Diantama, S. (2023). Pemanfaatan Artificial Intelegent (AI) dalam dunia pendidikan. DEWANTECH Jurnal Teknologi Pendidikan, 1(1), 8–14. https://doi.org/10.61434/dewantech.v1i1.8
Erdfelder, E., Faul, F., Buchner, A., & Lang, A. G. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149–1160. https://doi.org/10.3758/BRM.41.4.1149
Habibi, A., Riady, Y., Samed Al-Adwan, A., & Awni Albelbisi, N. (2023). Beliefs and knowledge for pre-service teachers’ technology integration during teaching practice: An extended theory of planned behavior. Computers in the Schools, 40(2), 107–132. https://doi.org/10.1080/07380569.2022.2124752
Hair, J., & Alamer, A. (2022). Partial Least Squares Structural Equation Modeling (PLS-SEM) in second language and education research: Guidelines using an applied example. Research Methods in Applied Linguistics, 1(3). https://doi.org/10.1016/j.rmal.2022.100027
Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., & Thiele, K. O. (2017). Mirror, mirror on the wall: a comparative evaluation of composite-based structural equation modeling methods. Journal of the Academy of Marketing Science, 45(5), 616–632. https://doi.org/10.1007/s11747-017-0517-x
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
Hair, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial Least Squares Structural Equation Modeling (PLS-SEM): An emerging tool in business research. European Business Review, 26(2), 106–121. https://doi.org/10.1108/EBR-10-2013-0128
Hakim. A. R., Sulistiawati, Arifin. S. (2018). Hubungan antara kecerdasan emosional dan motivasi belajar dengan prestasi belajar matematika siswa SMP. Jurnal Teorema: Teori dan Riset Matematika, 3(2), 165-176.
Harnoko, A. D., & Herianingrum, S. (2020). Analisis teori perilaku yang direncanakan terhadap niat warga Surabaya untuk kredit pemilikan rumah syariah di De Rayyan Developer Property. Jurnal Ekonomi Syariah Teori Dan Terapan, 7(8), 1527. https://doi.org/10.20473/vol7iss20208pp1527-1537
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
Hirose, M., & Creswell, J. W. (2023). Applying core quality criteria of mixed methods research to an empirical study. Journal of Mixed Methods Research, 17(1), 12–28. https://doi.org/10.1177/15586898221086346
Johnston, K. M., Lakzadeh, P., Donato, B. M. K., & Szabo, S. M. (2019). Methods of sample size calculation in descriptive retrospective burden of illness studies. BMC Medical Research Methodology, 19(1). https://doi.org/10.1186/s12874-018-0657-9
Khafifatulfian, K. F., & Misbah, M. (2023). Studi analitis model pembelajaran pai abad 21 berbasis multiple intelligences. Al-Ikhtibar: Jurnal Ilmu Pendidikan, 10(1), 48–67. https://doi.org/10.32505/ikhtibar.v10i1.6188
Lung-Guang, N. (2019). Decision-making determinants of students participating in MOOCs: Merging the theory of planned behavior and self-regulated learning model. Computers and Education, 134, 50–62. https://doi.org/10.1016/j.compedu.2019.02.004
Luthfan, M. A., Wahab, W., & Kurniawan, S. (2024). Pengembangan desain pembelajaran PAI “Pendidikan Agama Islam Abad 21: Genealogi, Karakteristik dan Metode.” JIIP - Jurnal Ilmiah Ilmu Pendidikan, 7(3). https://doi.org/10.54371/jiip.v7i3.3552
Lynn M. R. (1986). Determination and quantification of content validity. Nursing Research, 35(6), 382–386. http://ijoh.tums.ac.ir/index.php/ijoh/article/view/26
Meliani, G. R., & Suryadi, A. (2018). Game artificial intelegent: Ram City Tower dengan algoritma A*. JURNAL PETIK, 3(2). https://doi.org/10.31980/jpetik.v3i2.148
Musyafak, M., & Subhi, M. R. (2023). Strategi pembelajaran pendidikan agama islam dalam menghadapi tantangan di Era Revolusi Industri 5.0. Asian Journal of Islamic Studies and Da’wah, 1(2), 373–398. https://doi.org/10.58578/ajisd.v1i2.2109
Putriana, D., Qurrotul Aini, A., Irsyad, A., & Mu’alimin, M. (2024). Revolusi digital dalam pendidikan islam meningkatkan kualitas pembelajaran melalui integrasi teknologi. Reflection: Islamic Education Journal, 1(4), 200–210. https://doi.org/10.61132/reflection.v1i4.263
Rahmanita, F., Pamulang, U., & Wirandana, E. (2021). Hubungan antara gaya kepemimpinan, motivasi dan dimensi komitmen organisasi karyawan. Scientia Sacra: Jurnal Sains, 1 (1). https://www.pijarpemikiran.com/index.php/Aufklarung/article/view/164
Rahmat, R. (2021). Pembelajaran pendidikan agama islam abad 21 prespektif kitab Al Arba’in An Nawawiyah. Andragogi : Jurnal Ilmiah Pendidikan Agama Islam, 3(2). https://doi.org/10.33474/ja.v3i2.13866
Rahmawati, I. (2022). Pengaruh penggunaan model pembelajaran abad 21 terhadap kemampuan kognitif peserta didik Sekolah Dasar. EDUSAINTEK: Jurnal Pendidikan, Sains dan Teknologi, 9(2), 404–418. https://doi.org/10.47668/edusaintek.v9i2.461
Sabella, B., Rhomadhona, H., & Rusadi Arrahimi, A. (2023). Pelatihan pembuatan game sederhana sebagai media pembelajaran untuk pengajar SMP berbasis artificial intelegent. Jurnal Widya Laksmi: Jurnal Pengabdian Kepada Masyarakat, 3(2), 69–76. https://doi.org/10.59458/jwl.v3i2.59
Saefudin, M., Widianti, L. W., & Hendrato, H. (2023). Penerapan platform analisis media sosial berbasis artificial intelegent sebagai model pemasaran produk secara digital. Seminar Nasional Teknologi Informasi Dan Komunikasi STI&K (SeNTIK), 7(1). https://ejournal.jak-stik.ac.id/index.php/sentik/article/view/3457
Salsabila, U. H., Fitrah, P. F., & Nursangadah, A. (2020). Eksistensi teknologi pendidikan dalam kemajuan pendidikan islam abad 21. JURNAL EDUSCIENCE, 7(2), 68–77. https://doi.org/10.36987/jes.v7i2.1913
Saputra, H. (2019). Analisa kepatuhan pajak dengan pendekatan Teori Perilaku Terencana (Theory of Planned Behavior) (terhadap wajib pajak orang pribadi di Provinsi DKI Jakarta). Jurnal Muara Ilmu Ekonomi Dan Bisnis, 3(1), 47. https://doi.org/10.24912/jmieb.v3i1.2320
Setiawan, P., & Anggraeni, E. Y. (2018). Purwarupa sistem pengairan sawah otomatis dengan arduino berbasis artificial intelegent. Explore: Jurnal Sistem Informasi Dan Telematika, 9(2). https://doi.org/10.36448/jsit.v9i2.1086
She, L., Rasiah, R., Weissmann, M. A., & Kaur, H. (2024). Using the theory of planned behaviour to explore predictors of financial behaviour among working adults in Malaysia. FIIB Business Review, 13(1), 118–135. https://doi.org/10.1177/23197145231169336
Sheeran, P. (2002). Intention behavior relations: A conceptual and empirical review. European Review of Social Psychology, 12(1), 1–36. https://doi.org/10.1080/14792772143000003
Siqueira, M. S. S., Nascimento, P. O., & Freire, A. P. (2022). Reporting behaviour of people with disabilities in relation to the lack of accessibility on government websites: Analysis in the light of the Theory of Planned Behaviour. Disability, CBR and Inclusive Development, 33(1), 52–68. https://doi.org/10.47985/dcidj.475
Soelaiman, L., Selamat, F., & Puspitowati, I. (2023). Exploring the predictive factors of gen Z readiness for entrepreneurship. International Journal of Research in Business and Social Science (2147- 4478), 12(5), 10–16. https://doi.org/10.20525/ijrbs.v12i5.2757
Sucahyo, N., Usanto, U., & Sopian, A. (2023). Peran artificial intelegent terhadap peningkatan kreativitas siswa dengan menerapkan Projek Penguatan Profil Pelajar Pancasila. Abdimas Siliwangi, 6(3), 676–686. https://doi.org/10.22460/as.v6i3.18078
Teo, T., & van Schaik, P. (2012). Understanding the intention to use technology by preservice teachers: An empirical test of competing theoretical models. International Journal of Human-Computer Interaction, 28(3), 178–188. https://doi.org/10.1080/10447318.2011.581892
Tjahyanti, L. P. A. S., Saputra, P. S., & Gitakarma, M. S. (2022). Peran Artificial Intelligence (AI) untuk mendukung pembelajaran di masa pandemi Covid-19. Ejournal.Unipas.Ac.Id. https://ejournal.unipas.ac.id/index.php/Komteks/article/view/1062
Urton, K., Wilbert, J., Krull, J., & Hennemann, T. (2023). Factors explaining teachers’ intention to implement inclusive practices in the classroom: Indications based on the theory of planned behaviour. Teaching and Teacher Education, 132. https://doi.org/10.1016/j.tate.2023.104225
Wijaya, R. (2018). Implementasi teknik artificial intelegent rough set dalam pengambilan keputusan pada proses penentuan kelulusan pelamaran pekerjaan. Rang Teknik Journal, 1(1). https://doi.org/10.31869/rtj.v1i1.613
Yulianti, S. D., & Salsabilla, S. (2022). Determinants of investment intention in sharia stocks. Asian Journal of Islamic Management (AJIM), 2022(2), 126–137. https://doi.org/10.20885/AJIM
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 agung febrianto, Akhmad Habibi, Sofyan Sofyan

This work is licensed under a Creative Commons Attribution 4.0 International License.














