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All Journal JPTK: Jurnal Pendidikan Teknologi dan Kejuruan Scholaria: Jurnal Pendidikan dan Kebudayaan Jurnal Studi Komunikasi International Journal of Community Service Learning Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Psychology, Evaluation, and Technology in Educational Research International Journal of Active Learning Jurnal Teknologi Informasi dan Pendidikan Abdi Wiralodra : Jurnal Pengabdian Kepada Masyarakat Abdimasku : Jurnal Pengabdian Masyarakat Madani : Indonesian Journal of Civil Society Jurnal Abdimas Bina Bangsa Jurnal Sistem Informasi, Teknik Informatika dan Teknologi Pendidikan (JUSTIKPEN) Tsaqila Jurnal Pendidikan dan Teknologi Jurnal Pengabdian Papua Midang Jurnal Pengabdian KOLABORATIF Jurnal Abdimas Jurnal DIMASTIK
Hanita Yulia
Universitas Kristen Satya Wacana
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A Value-Based Structural Model of Generative AI Adoption for Vocational Teachers Krismiyati Krismiyati; Rudy Latuperissa; Hanita Yulia
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 15 No. 1 (2026)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v15i1.107130

Abstract

This study develops and empirically tests a value-based structural model of Generative AI adoption among vocational teachers, situating technology acceptance within a techno-pedagogy perspective. Extending the Unified Theory of Acceptance and Use of Technology (UTAUT), the model reconceptualizes performance expectancy, effort expectancy, perceived enjoyment, and computer self-efficacy as cognitive–affective antecedents of perceived AI value. Rather than treating adoption as a linear, intention-driven process, this study positions perceived AI value as the central evaluative mechanism shaping attitudes, behavioral intentions, and actual AI use in instructional contexts. A quantitative explanatory design was employed, involving 110 vocational teachers with prior experience using Generative AI tools. Data were collected using a 5-point Likert-scale instrument and analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings indicate that perceived AI value is the strongest predictor of both attitude and actual AI usage, while behavioral intention does not significantly predict usage, revealing an intention–behavior gap. Facilitating conditions were also found to be non-significant predictors of actual use. These results suggest that Generative AI adoption in vocational education is primarily value-driven rather than structurally enforced. The study contributes to the techno-pedagogy literature by demonstrating that utilitarian and hedonic value perceptions can directly activate the use of pedagogical technology, thereby extending UTAUT with a value-centered evaluative pathway. Practical implications emphasize the need for pedagogically grounded AI training that enhances perceived instructional relevance, usability, and experiential value, thereby fostering sustainable AI integration in vocational teaching environments.
Co-Authors Adi Nugroho Aditya Erwin Herlambang Adriyanto Juliastomo Gundo Agustina Tyas Asri Hardini Andreas A. Sukmana Andreas Farrel Evan Angela Atik Setiyanti Angela Atik Setyanti Anton Hermawan Anton Hermawan Bayangkariwati Tacoh, Yuliana Tien Betty E. Kristiani Birmanti Setia Utami Budhi Kristianto Chandra, Dian W. Charitas Fibriani Dian Novita Kristiyani Dwi Kurnaningsih, Yari Erwien Christianto Evangs Mailoa Hendry Hindriyanto Dwi Purnomo Jusuf Tjahjo Purnomo Krismiyati Krismiyati, - Marcelyn Budi Orikana Mawardi Mawardi Mila Chrismawati Paseleng Pratyaksa Ocsa Nugraha Saian Radius Tanone Rissal Effendi Rudy Latuperissa Saputri, Linda Wahyu Saputri Setyanti, Angela Atik Sri Kasmiyati Teguh I. Bayu Theopillus J. H. Wellem Tupessy, Pricilia Musesil Willson Mangoki Yayi Suryo Prabandari Yerymia Alfa Susetyo Yessica Nataliani Yuliana T. B. Tacoh