Exploring the Impact of Professional Value and Perceived Adoption Control on Continuous Professional Development Engagement via Digital Teaching Platform : A Structural Equation Modelling Approach

Authors

DOI:

https://doi.org/10.33394/jk.v11i2.15185

Keywords:

Continuous Professional Development, Digital Platform, Professional Value, Highschool Teachers.

Abstract

This study aims to examine the impact of professional value and perceived adoption control on teachers' CPD engagement via a digital teaching platform.  This study used a quantitative approach with a survey method. It involves 313 high school teachers in Pati, Grobogan and Semarang Central Java with at least a year of experience in using the digital teaching platform. The instrument used in this study is a 5-point Likert scale item survey with 21 questions covering 11 constructs adapted from TAM. It uses Jamovi to analyze and model the data statistically. Structural Equation Modelling examines the relationship between variables proposed in the model. The result of the study shows that perceived professional value moderately impacts teachers' CPD Engagement. The constructs strongly mediate their CPD engagement through the perceived adoption control construct. The SEM analysis indicates that the proposed model is a good fit, as the fit indices show. The conceptual implication of the findings demonstrates that it extends TAM 2 in CPD context using a digital teaching platform. Practically, CPD program should align the technology tools with teachers’ professional goals and ensure it is part of the professional culture rather than leaving it as optional or voluntary practices.

References

Abdalla, R. A. M. (2024). Examining awareness, social influence, and perceived enjoyment in the TAM framework as determinants of ChatGPT. Personalization as a moderator. Journal of Open Innovation: Technology, Market, and Complexity, 10(3), 100327. https://doi.org/10.1016/j.joitmc.2024.100327

Albion, P., & Ertmer, P. a. (2001). Beyond the foundations : The role of vision and belief in teachers’ preparation for integration of technology. Tech Trends, 46(5), 34–38. https://doi.org/10.1007/BF02818306

Alyoussef, I. Y. (2022). Acceptance of a flipped classroom to improve university students’ learning: An empirical study on the TAM model and the unified theory of acceptance and use of technology (UTAUT). Heliyon, 8(12), e12529. https://doi.org/10.1016/j.heliyon.2022.e12529

Anggraeni, D., & Rizaldi, R. (2023). Sosialisasi Platform Kampus Merdeka Sebagai Wadah Berkarya Guru. Journal Of Indonesian Social Society (JISS), 1(2), 76–81. https://doi.org/10.59435/jiss.v1i2.119

Antonietti, C., Cattaneo, A., & Amenduni, F. (2022). Can teachers’ digital competence influence technology acceptance in vocational education? Computers in Human Behavior, 132(March), 107266. https://doi.org/10.1016/j.chb.2022.107266

Aurangzeb, W., Kashan, S., & Rehman, Z. U. (2024). Investigating Technology Perceptions Among Secondary School Teachers a Systematic Literature Review on Perceived Usefulness and Ease of Use. Academy of Education and Social Sciences Review, 4(2), 160–173. https://doi.org/10.48112/aessr.v4i2.746

Bleach, J. (2015). Developing professionalism through reflective practice and ongoing professional development. 1807(October). https://doi.org/10.1080/1350293X.2014.883719

Creswell, J. W. (2012). Educational research: Planning, conducting, and evaluating quantitative and qualitative research. In Educational Research (Vol. 4). Pearson. https://doi.org/10.1017/CBO9781107415324.004

Fütterer, T., Scherer, R., Scheiter, K., Stürmer, K., & Lachner, A. (2023). Will, skills, or conscientiousness: What predicts teachers’ intentions to participate in technology-related professional development? Computers and Education, 198(February), 104756. https://doi.org/10.1016/j.compedu.2023.104756

García-Vandewalle García, J. M., García-Carmona, M., Trujillo Torres, J. M., & Moya Fernández, P. (2023). Analysis of digital competence of educators (DigCompEdu) in teacher trainees: the context of Melilla, Spain. Technology, Knowledge and Learning, 28(2), 585–612. https://doi.org/10.1007/s10758-021-09546-x

Graham, C. R., Borup, J., & Smith, N. B. (2012). Using TPACK as a framework to understand teacher candidates’ technology integration decisions. Journal of Computer Assisted Learning, 28(6), 530–546. https://doi.org/10.1111/j.1365-2729.2011.00472.x

Hammond, L. D., Hyler, M. E., & Gardner, M. (2017). Effective Teacher Professional Development in the evolution of human and non-human animals. Learning Policy Institute, June.

Hancock, G. R., & Mueller, R. O. (2010). The Reviewer’s Guide to Quantitative Methods. In Health (San Francisco).

Hasmawaty, Muliati, & Bachtiar, M. Y. (2023). Optimalisasi Aplikasi Platform Merdeka Mengajar (MM) Melalui Komunitas Belajar Gugus PAUD. Madaniya, 4(2), 574–581.

Kastorff, T., Sailer, M., & Stegmann, K. (2023). A typology of adolescents’ technology use before and during the COVID-19 pandemic: A latent profile analysis. International Journal of Educational Research, 117(January), 1–13. https://doi.org/10.1016/j.ijer.2023.102136

Kemendikbudristek. (2023). Buku Saku Platform Merdeka Belajar. In Merdeka Mengajar. https://pusatinformasi.guru.kemdikbud.go.id/hc/en-us/articles/6090880411673-Apa-Itu-Platform-Merdeka-Mengajar-

Kementerian Pendidikan, Kebudayaan, R. dan T. (2022). Peran Platform Merdeka Mengajar dalam Impelementasi Kurikulum Merdeka. https://kurikulum-demo.simpkb.id/platform-merdeka-belajar/

Kementerian Pendidikan, Kebudayaan, Riset, dan T. (2020). Mengenal Platform Merdeka Mengajar. https://pusatinformasi.belajar.id/hc/id/articles/4433405881241-Mengenal-Platform-Merdeka-Mengajar#:~:text=Platform Merdeka Mengajar adalah platform, mengajar%2C belajar%2C dan berkarya.

Kong, S. C., Yang, Y., & Hou, C. (2024). Examining teachers’ behavioural intention of using generative artificial intelligence tools for teaching and learning based on the extended technology acceptance model. Computers and Education: Artificial Intelligence, 7(August), 100328. https://doi.org/10.1016/j.caeai.2024.100328

Lutabingwa, J., & Auriacombe, C. J. (2019). Data analysis in quantitative research. Handbook of Research Methods in Health Social Sciences, June, 955–969. https://doi.org/10.1007/978-981-10-5251-4_109

Marzano, A., Vegliante, R., & Angelis, M. De. (2015). Quali-Quantitative Approach in Educational Research. INTED2015 Proceedings, March, 405–412.

Muhafid, E. A., Andika, A., Hidayah, N., Mitsalina, E., & Azizah, R. N. (2023). Penguatan Implementasi Kurikulum Merdeka Melalui Pelatihan Teknis Platform Merdeka Mengajar Kosp Dan Modul Ajar Pada Mahasiswa Ilmu Pendidikan. JPM Jurnal Pengabdian Mandiri, 2(2), 455–460.

Otamirzayeva, S. (2024). Integrating Technology, Empowering Teachers : A Roadmap to Continuous Professional Advancement. 1(5).

Parsons, S. A., Hutchison, A. C., Hall, L. A., Parsons, A. W., Ives, S. T., & Leggett, A. B. (2019). U.S. teachers’ perceptions of online professional development. Teaching and Teacher Education, 82, 33–42. https://doi.org/10.1016/j.tate.2019.03.006

Rafique, S., Salsabeel, W., & Javed, I. (2024). Teachers’ Perceived Ease of Use and Perceived Usefulness of Technology at Higher Education Level. 13(4), 427–436.

Rohimat, S., Sanusi, S., & Munthahanah, M. (2022). Diseminasi Platform Merdeka Mengajar Untuk Guru Sma Negeri 6 Kota Serang. ABDIKARYA: Jurnal Pengabdian Dan Pemberdayaan Masyarakat, 4(2), 1–9. https://doi.org/10.47080/abdikarya.v4i2.2035

Schmidt, D. A., Koehler, M. J., & Shin, T. S. (2009). Technological Pedagogical Content Knowledge (TPACK ): The Development and Validation of an Assessment Instrument for Preservice Teachers. Journal of Research on Technology in Education, 42(2), 123–149.

Siminto, Lisnawati, S. D., & Muharam, S. (2023). Teacher Professionalism Development Strategy through ChatGPT Support in the Context of Education Management. Journal of Contemporary Administration and Management (ADMAN), 1(3), 150–155. https://doi.org/10.61100/adman.v1i3.65

Srianita, Y., Rahmi, A. M., & Juhriati, I. (2023). Peningkatan budaya belajar mandiri melalui platform merdeka belajar bagi guru paud. Jurnal Pendidikan Tambusai, 7(1), 3007–3013.

Surani, D., Asnawati, A. N., & Kusuma, A. W. (2022). Sosialisasi Aplikasi Merdeka Mengajar Dan Pengenalan Platform Simba Dalam Meningkatkan Pemahaman Media Pembelajaran Kepada Tenaga Pendidik Di Smpn 10 Cilegon. Jubaedah : Jurnal Pengabdian Dan Edukasi Sekolah (Indonesian Journal of Community Services and School Education), 2(2), 164–171. https://doi.org/10.46306/jub.v2i2.77

SÜRÜCÜ, L., & MASLAKÇI, A. (2020). Validity and Reliability in Quantitative Research. Business & Management Studies: An International Journal, 8(3), 2694–2726. https://doi.org/10.15295/bmij.v8i3.1540

Tan, X., Cheng, G., & Ling, M. H. (2025). Artificial intelligence in teaching and teacher professional development: A systematic review. Computers and Education: Artificial Intelligence, 8(October 2024). https://doi.org/10.1016/j.caeai.2024.100355

Teo, T. (2011a). Factors influencing teachers’ intention to use technology: Model development and test. Computers & Education, 57(4), 2432–2440. https://doi.org/10.1016/j.compedu.2011.06.008

Teo, T. (2011b). Modeling the determinants of pre-service teachers’ perceived usefulness of e-learning. Campus-Wide Information Systems, 28(2), 124–140. https://doi.org/10.1108/10650741111117824

Teo, T. (2015). Comparing pre-service and in-service teachers’ acceptance of technology: Assessment of measurement invariance and latent mean differences. Computers & Education, 83, 22–31. https://doi.org/10.1016/j.compedu.2014.11.015

UNESCO. (2018). Unesco ICT Competency Framework for Teachers (Version 3). In Journal of Chemical Information and Modeling (Vol. 53, Issue 9). https://n9.cl/x1uf

Velli, K., & Zafiropoulos, K. (2024). Factors That Affect the Acceptance of Educational AI Tools by Greek Teachers—A Structural Equation Modelling Study. European Journal of Investigation in Health, Psychology and Education, 14(9), 2560–2579. https://doi.org/10.3390/ejihpe14090169

Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315. https://doi.org/10.1111/j.1540-5915.2008.00192.x

Venkatesh, V., & Davis, F. D. (2000). Theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926

Yao, N., & Wang, Q. (2024). Factors influencing pre-service special education teachers’ intention toward AI in education: Digital literacy, teacher self-efficacy, perceived ease of use, and perceived usefulness. Heliyon, 10(14), e34894. https://doi.org/10.1016/j.heliyon.2024.e34894

Yao, Y., Wang, P., Jiang, Y. J., Li, Q., & Li, Y. (2022). Innovative online learning strategies for the successful construction of student self-awareness during the COVID-19 pandemic: Merging TAM with TPB. Journal of Innovation and Knowledge, 7(4), 100252. https://doi.org/10.1016/j.jik.2022.100252

Zhuang, T., Cheung, A. C. K., & Tam, W. (2020). Modeling undergraduate STEM students’ satisfaction with their programs in China: an empirical study. Asia Pacific

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2025-06-25

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Krismiyati, K., & Latuperissa, R. (2025). Exploring the Impact of Professional Value and Perceived Adoption Control on Continuous Professional Development Engagement via Digital Teaching Platform : A Structural Equation Modelling Approach. Jurnal Kependidikan: Jurnal Hasil Penelitian Dan Kajian Kepustakaan Di Bidang Pendidikan, Pengajaran Dan Pembelajaran, 11(2), 481–492. https://doi.org/10.33394/jk.v11i2.15185

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Vol. 11 No. 2 (2025): June

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