Bayu Ramadhani Fajri, Fathiyah Mohd Kamaruzaman, Marlissa Omar, Wiki Lofandri, Agariadne Dwinggo Samala
This study presents the design, implementation, and validation of the Smart Teaching Factory (STF) framework, which integrates Extended Reality (XR), Artificial Intelligence (AI), and animated simulation technologies to enhance vocational education. Targeting 62 electronics engineering students and 6 vocational instructors across three Indonesian public vocational schools, this quasi-experimental mixed-methods study compared the effects of STF-enhanced instruction with conventional methods. Quantitative results from pre-and post-tests revealed significant improvements in student learning outcomes (p < 0,01), while SUS usability scores reached 82,5, indicating excellent system acceptance. Interaction analytics from platform logs and classroom observations highlighted elevated student focus, collaboration, and task engagement in the experimental group. The STF model proved effective in delivering competency-based, immersive learning experiences through a data-informed, user-centered platform. These findings demonstrate STF’s potential as a scalable, adaptable framework for transforming vocational education in resource-constrained environments. © 2025; Los autores.
Universiti Kebangsaan Malaysia, Faculty of Education, Malaysia; Universitas Negeri Padang, School of Vocational Studies, Indonesia; Universitas Negeri Padang, Faculty of Engineering, Indonesia
