Main Article Content
Abstract
Evaluating lecturers competence in Artificial Intelligence, Technological, Pedagogical, and Content Knowledge (AI-TPACK) and identifying key influencing factors are critical steps toward ensuring effective AI integration. Purpose: This study aims to explore the predictive effect of digital competence on AI-TPACK among sports education lecturers in Indonesia. Materials and methods: A correlational survey design was employed, involving 105 lecturers from Physical Education, Health, and Recreation programs (PJKR) across five teacher education institutions in West Java. Data were collected using two structured scales: AI-TPACK and digital competence. Structural Equation Modeling (SEM) was applied to analyze the relationships between variables. Results: The analysis revealed that while lecturers demonstrated above-average digital competence, their AI-TPACK competence remained below average. A significant positive correlation (r = 0.533) was found between digital competence and AI-TPACK, with digital competence emerging as a primary predictor. These findings suggest that lecturers who are more digitally competent are also more capable of integrating AI into their pedagogical practice. Conclusions: Strengthening digital competence can be a strategic foundation for building AI-related pedagogical skills. Future training programs should integrate both technical and pedagogical components of AI, tailored to the teaching context of physical education lecturers in higher education.
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Copyright (c) 2025 Ahmad Afandi Harja Afandi, Asep Rahmat, Irpan

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References
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- Ayanwale, M. A., Sanusi, I. T., Adelana, O. P., Aruleba, K. D., & Oyelere, S. S. (2022). Teachers’ readiness and intention to teach artificial intelligence in schools. Computers and Education: Artificial Intelligence, 3(June), 100099. https://doi.org/10.1016/j.caeai.2022.100099
- Basantes-Andrade, A., Casillas-Martín, S., Cabezas-González, M., Naranjo-Toro, M., & Guerra-Reyes, F. (2022). Standards of Teacher Digital Competence in Higher Education: A Systematic Literature Review. Sustainability (Switzerland), 14(21), 1–22. https://doi.org/10.3390/su142113983
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- Dogan, M. E., Goru Dogan, T., & Bozkurt, A. (2023). The Use of Artificial Intelligence (AI) in Online Learning and Distance Education Processes: A Systematic Review of Empirical Studies. Applied Sciences (Switzerland), 13(5), 1–22. https://doi.org/10.3390/app13053056
- Forero-Corba, W., & Bennasar, F. N. (2024). Techniques and applications of Machine Learning and Artificial Intelligence in education: a systematic review. RIED-Revista Iberoamericana de Educacion a Distancia, 27(1), 209–253. https://doi.org/10.5944/ried.27.1.37491
- Gligorea, I., Cioca, M., Oancea, R., Gorski, A. T., Gorski, H., & Tudorache, P. (2023). Adaptive Learning Using Artificial Intelligence in e-Learning: A Literature Review. Education Sciences, 13(12), 1–22. https://doi.org/10.3390/educsci13121216
- Ifenthaler, D., Majumdar, R., Gorissen, P., Judge, M., Mishra, S., Raffaghelli, J., & Shimada, A. (2024). Artificial Intelligence in Education: Implications for Policymakers, Researchers, and Practitioners. Technology, Knowledge and Learning, 29(4), 1693–1710. https://doi.org/10.1007/s10758-024-09747-0
- Ivanova, M., Grosseck, G., & Holotescu, C. (2024). Unveiling Insights: A Bibliometric Analysis of Artificial Intelligence in Teaching. Informatics, 11(1), 1–22. https://doi.org/10.3390/informatics11010010
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- Lan, H., Bailey, R., & Tan, W. H. (2024). Assessing the digital competence of in-service university educators in China: A systematic literature review. Heliyon, 10(16), e35675. https://doi.org/10.1016/j.heliyon.2024.e35675
- Lee, D., Arnold, M., Srivastava, A., Plastow, K., Strelan, P., Ploeckl, F., Lekkas, D., & Palmer, E. (2024). The impact of generative AI on higher education learning and teaching: A study of educators’ perspectives. Computers and Education: Artificial Intelligence, 6(October 2023), 100221. https://doi.org/10.1016/j.caeai.2024.100221
- Lucas, M., Zhang, Y., Bem-haja, P., & Vicente, P. N. (2024). The interplay between teachers’ trust in artificial intelligence and digital competence. Education and Information Technologies, 29(17), 22991–23010. https://doi.org/10.1007/s10639-024-12772-2
- Mishra, P., Warr, M., & Islam, R. (2023). TPACK in the age of ChatGPT and Generative AI. Journal of Digital Learning in Teacher Education, 1(1), 235–251. https://doi.org/10.1080/21532974.2023.2247480
- Nguyen, P. L., Nguyen, H. T. T., Truong, B. T., Mai, K. T., & Duc, M. La. (2024). Digital Competence for University Lecturers in Vietnam: A Case Study Result At 10 Universities. International Journal of Religion, 5(10), 26–42. https://doi.org/10.61707/y3867b46
- 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), 1–22. https://doi.org/10.3390/su16030978
- Ramirez-Asis, E., Huaranga-Toledo, H., Bulĺon-Miguel, Y., Rodriguez-Nomura, H., & Rodŕiguez-Orellana, H. M. (2024). Digital competencies and attitude toward the use of information technologies in secondary school teachers in a peruvian public educational institution. Technological Innovations for Business, Education and Sustainability, 1(April), 153–167. https://doi.org/10.1108/978-1-83753-106-620241011
- Salleh, M. H., Kadir, S. A., Jamaluddin, R., & Puad, M. H. M. (2022). Factors Influencing TVET Teacher’s TPACK Competencies in Peninsular Malaysia. Journal of Technical Education and Training, 14(3), 105–111. https://doi.org/10.30880/jtet.2022.14.03.010
- Sheikh, M., Iqra, F., Ambreen, H., Pravin, K. A., Ikra, M., & Chung, Y. S. (2024). Integrating artificial intelligence and high-throughput phenotyping for crop improvement. Journal of Integrative Agriculture, 23(6), 1787–1802. https://doi.org/10.1016/j.jia.2023.10.019
- Sun, T., Feng, B., Huo, J., Xiao, Y., Wang, W., Peng, J., Li, Z., Du, C., Wang, W., Zou, G., & Liu, L. (2024). Artificial Intelligence Meets Flexible Sensors: Emerging Smart Flexible Sensing Systems Driven by Machine Learning and Artificial Synapses. In Nano-Micro Letters (Vol. 16, Issue 1). Springer Nature Singapore. https://doi.org/10.1007/s40820-023-01235-x
- Utina, S. S., Chusniyah, T., Inseachiangmai, J., Zahra, G. A., & Setyo, K. (2024). A comparative study of artificial intelligence in education psychology: the cases of Indonesia and Thailand. Bulletin of Social Informatics Theory and Application, 8(1), 70–85. https://doi.org/10.31763/businta.v8il.663
- Wagner, M., Ley, T., Kammerer, L., & Helm, C. (2024). Exploring teacher educators’ challenges in the context of digital transformation and their self-reported TPACK: a mixed methods study. European Journal of Teacher Education, 1(1), 1–19. https://doi.org/10.1080/02619768.2024.2340689
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- Xu, G., Yu, A., Xu, C., Liu, X., & Trainin, G. (2024). Investigating pre-service TCSL teachers’ technology integration competency through a content-based AI-inclusive framework. Education and Information Technologies, 1(1). https://doi.org/10.1007/s10639-024-12982-8
- Yim, I. H. Y., & Su, J. (2024). Artificial intelligence (AI) learning tools in K-12 education: A scoping review. In Journal of Computers in Education (Vol. 12, Issue 1). Springer Berlin Heidelberg. https://doi.org/10.1007/s40692-023-00304-9
- Yue, M., Jong, M. S. Y., & Ng, D. T. K. (2024). Understanding K–12 teachers’ technological pedagogical content knowledge readiness and attitudes toward artificial intelligence education. In Education and Information Technologies (Vol. 29, Issue 15). Springer US. https://doi.org/10.1007/s10639-024-12621-2
- Zarei, M., Eftekhari Mamaghani, H., Abbasi, A., & Hosseini, M. S. (2024). Application of artificial intelligence in medical education: A review of benefits, challenges, and solutions. Medicina Clinica Practica, 7(2), 7–11. https://doi.org/10.1016/j.mcpsp.2023.100422
- Zhang, Z., Liu, X., Zhou, H., Xu, S., & Lee, C. (2024). Advances in Machine-Learning Enhanced Nanosensors: From Cloud Artificial Intelligence Toward Future Edge Computing at Chip Level. Small Structures, 5(1), 1–27. https://doi.org/DOI: 10.1002/sstr.202300325
References
Al-Abdullatif, A. M. (2024). Modeling Teachers’ Acceptance of Generative Artificial Intelligence Use in Higher Education: The Role of AI Literacy, Intelligent TPACK, and Perceived Trust. Education Sciences, 14(11), 1–22. https://doi.org/10.3390/educsci14111209
Al-Zahrani, A. M., & Alasmari, T. M. (2024). Exploring the impact of artificial intelligence on higher education: The dynamics of ethical, social, and educational implications. Humanities and Social Sciences Communications, 11(1), 1–12. https://doi.org/10.1057/s41599-024-03432-4
Ayanwale, M. A., Sanusi, I. T., Adelana, O. P., Aruleba, K. D., & Oyelere, S. S. (2022). Teachers’ readiness and intention to teach artificial intelligence in schools. Computers and Education: Artificial Intelligence, 3(June), 100099. https://doi.org/10.1016/j.caeai.2022.100099
Basantes-Andrade, A., Casillas-Martín, S., Cabezas-González, M., Naranjo-Toro, M., & Guerra-Reyes, F. (2022). Standards of Teacher Digital Competence in Higher Education: A Systematic Literature Review. Sustainability (Switzerland), 14(21), 1–22. https://doi.org/10.3390/su142113983
Cao, J., Bhuvaneswari, G., Arumugam, T., & Aravind, B. R. (2023). The digital edge: examining the relationship between digital competency and language learning outcomes. Frontiers in Psychology, 14(June), 1–11. https://doi.org/10.3389/fpsyg.2023.1187909
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), 1–22. https://doi.org/10.1186/s41239-023-00392-8
Dai, C. P., & Ke, F. (2022). Educational applications of artificial intelligence in simulation-based learning: A systematic mapping review. Computers and Education: Artificial Intelligence, 3(January), 100087. https://doi.org/10.1016/j.caeai.2022.100087
Demissie, E. B., Labiso, T. O., & Thuo, M. W. (2022). Teachers’ digital competencies and technology integration in education: Insights from secondary schools in Wolaita Zone, Ethiopia. Social Sciences and Humanities Open, 6(1), 100355. https://doi.org/10.1016/j.ssaho.2022.100355
Dogan, M. E., Goru Dogan, T., & Bozkurt, A. (2023). The Use of Artificial Intelligence (AI) in Online Learning and Distance Education Processes: A Systematic Review of Empirical Studies. Applied Sciences (Switzerland), 13(5), 1–22. https://doi.org/10.3390/app13053056
Forero-Corba, W., & Bennasar, F. N. (2024). Techniques and applications of Machine Learning and Artificial Intelligence in education: a systematic review. RIED-Revista Iberoamericana de Educacion a Distancia, 27(1), 209–253. https://doi.org/10.5944/ried.27.1.37491
Gligorea, I., Cioca, M., Oancea, R., Gorski, A. T., Gorski, H., & Tudorache, P. (2023). Adaptive Learning Using Artificial Intelligence in e-Learning: A Literature Review. Education Sciences, 13(12), 1–22. https://doi.org/10.3390/educsci13121216
Ifenthaler, D., Majumdar, R., Gorissen, P., Judge, M., Mishra, S., Raffaghelli, J., & Shimada, A. (2024). Artificial Intelligence in Education: Implications for Policymakers, Researchers, and Practitioners. Technology, Knowledge and Learning, 29(4), 1693–1710. https://doi.org/10.1007/s10758-024-09747-0
Ivanova, M., Grosseck, G., & Holotescu, C. (2024). Unveiling Insights: A Bibliometric Analysis of Artificial Intelligence in Teaching. Informatics, 11(1), 1–22. https://doi.org/10.3390/informatics11010010
Jarjabka, Á., Sipos, N., & Kuráth, G. (2024). Quo vadis higher education? Post-pandemic success digital competencies of the higher educators – a Hungarian university case and actions. Humanities and Social Sciences Communications, 11(1), 1–11. https://doi.org/10.1057/s41599-024-02809-9
Kalniņa, D., Nīmante, D., & Baranova, S. (2024). Artificial intelligence for higher education: benefits and challenges for pre-service teachers. Frontiers in Education, 9(1), 1–22. https://doi.org/10.3389/feduc.2024.1501819
Kavitha, K., & Joshith, V. P. (2024). The Transformative Trajectory of Artificial Intelligence in Education: The Two Decades of Bibliometric Retrospect. Journal of Educational Technology Systems, 52(3), 376–405. https://doi.org/10.1177/00472395241231815
Kim, S. W. (2024). Development of a TPACK Educational Program to Enhance Pre-service Teachers’ Teaching Expertise in Artificial Intelligence Convergence Education. International Journal on Advanced Science, Engineering and Information Technology, 14(1), 1–9. https://doi.org/10.18517/ijaseit.14.1.19552
Kindenberg, B. (2025). The Role of AI in Historical Simulation Design: A TPACK Perspective on a French Revolution Simulation Design Experience. Education Sciences, 15(2), 1–22. https://doi.org/10.3390/educsci15020192
Lan, H., Bailey, R., & Tan, W. H. (2024). Assessing the digital competence of in-service university educators in China: A systematic literature review. Heliyon, 10(16), e35675. https://doi.org/10.1016/j.heliyon.2024.e35675
Lee, D., Arnold, M., Srivastava, A., Plastow, K., Strelan, P., Ploeckl, F., Lekkas, D., & Palmer, E. (2024). The impact of generative AI on higher education learning and teaching: A study of educators’ perspectives. Computers and Education: Artificial Intelligence, 6(October 2023), 100221. https://doi.org/10.1016/j.caeai.2024.100221
Lucas, M., Zhang, Y., Bem-haja, P., & Vicente, P. N. (2024). The interplay between teachers’ trust in artificial intelligence and digital competence. Education and Information Technologies, 29(17), 22991–23010. https://doi.org/10.1007/s10639-024-12772-2
Mishra, P., Warr, M., & Islam, R. (2023). TPACK in the age of ChatGPT and Generative AI. Journal of Digital Learning in Teacher Education, 1(1), 235–251. https://doi.org/10.1080/21532974.2023.2247480
Nguyen, P. L., Nguyen, H. T. T., Truong, B. T., Mai, K. T., & Duc, M. La. (2024). Digital Competence for University Lecturers in Vietnam: A Case Study Result At 10 Universities. International Journal of Religion, 5(10), 26–42. https://doi.org/10.61707/y3867b46
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), 1–22. https://doi.org/10.3390/su16030978
Ramirez-Asis, E., Huaranga-Toledo, H., Bulĺon-Miguel, Y., Rodriguez-Nomura, H., & Rodŕiguez-Orellana, H. M. (2024). Digital competencies and attitude toward the use of information technologies in secondary school teachers in a peruvian public educational institution. Technological Innovations for Business, Education and Sustainability, 1(April), 153–167. https://doi.org/10.1108/978-1-83753-106-620241011
Salleh, M. H., Kadir, S. A., Jamaluddin, R., & Puad, M. H. M. (2022). Factors Influencing TVET Teacher’s TPACK Competencies in Peninsular Malaysia. Journal of Technical Education and Training, 14(3), 105–111. https://doi.org/10.30880/jtet.2022.14.03.010
Sheikh, M., Iqra, F., Ambreen, H., Pravin, K. A., Ikra, M., & Chung, Y. S. (2024). Integrating artificial intelligence and high-throughput phenotyping for crop improvement. Journal of Integrative Agriculture, 23(6), 1787–1802. https://doi.org/10.1016/j.jia.2023.10.019
Sun, T., Feng, B., Huo, J., Xiao, Y., Wang, W., Peng, J., Li, Z., Du, C., Wang, W., Zou, G., & Liu, L. (2024). Artificial Intelligence Meets Flexible Sensors: Emerging Smart Flexible Sensing Systems Driven by Machine Learning and Artificial Synapses. In Nano-Micro Letters (Vol. 16, Issue 1). Springer Nature Singapore. https://doi.org/10.1007/s40820-023-01235-x
Utina, S. S., Chusniyah, T., Inseachiangmai, J., Zahra, G. A., & Setyo, K. (2024). A comparative study of artificial intelligence in education psychology: the cases of Indonesia and Thailand. Bulletin of Social Informatics Theory and Application, 8(1), 70–85. https://doi.org/10.31763/businta.v8il.663
Wagner, M., Ley, T., Kammerer, L., & Helm, C. (2024). Exploring teacher educators’ challenges in the context of digital transformation and their self-reported TPACK: a mixed methods study. European Journal of Teacher Education, 1(1), 1–19. https://doi.org/10.1080/02619768.2024.2340689
Xie, Y., Boudouaia, A., Xu, J., AL-Qadri, A. H., Khattala, A., Li, Y., & Aung, Y. M. (2023). A Study on Teachers’ Continuance Intention to Use Technology in English Instruction in Western China Junior Secondary Schools. Sustainability (Switzerland), 15(5), 1–22. https://doi.org/10.3390/su15054307
Xu, G., Yu, A., Xu, C., Liu, X., & Trainin, G. (2024). Investigating pre-service TCSL teachers’ technology integration competency through a content-based AI-inclusive framework. Education and Information Technologies, 1(1). https://doi.org/10.1007/s10639-024-12982-8
Yim, I. H. Y., & Su, J. (2024). Artificial intelligence (AI) learning tools in K-12 education: A scoping review. In Journal of Computers in Education (Vol. 12, Issue 1). Springer Berlin Heidelberg. https://doi.org/10.1007/s40692-023-00304-9
Yue, M., Jong, M. S. Y., & Ng, D. T. K. (2024). Understanding K–12 teachers’ technological pedagogical content knowledge readiness and attitudes toward artificial intelligence education. In Education and Information Technologies (Vol. 29, Issue 15). Springer US. https://doi.org/10.1007/s10639-024-12621-2
Zarei, M., Eftekhari Mamaghani, H., Abbasi, A., & Hosseini, M. S. (2024). Application of artificial intelligence in medical education: A review of benefits, challenges, and solutions. Medicina Clinica Practica, 7(2), 7–11. https://doi.org/10.1016/j.mcpsp.2023.100422
Zhang, Z., Liu, X., Zhou, H., Xu, S., & Lee, C. (2024). Advances in Machine-Learning Enhanced Nanosensors: From Cloud Artificial Intelligence Toward Future Edge Computing at Chip Level. Small Structures, 5(1), 1–27. https://doi.org/DOI: 10.1002/sstr.202300325