Development of Teaching Factory Model-Based Artificial Intelligence: Improving the Quality of Learning Vocational Schools in Indonesia - Sintha Wahjusaputri; Tashia Indah Nastiti; Bunyamin Bunyamin; Wati Sukmawati; Johan Johan (STAI Hubbulwathan Duri, 2024)
This study aims to develop an AI-based teaching factory model in Vocational High Schools (SMKs) to improve vocational education quality and align student competencies with Industry 4.0 requirements. Integrating AI is anticipated to enhance students' technical and non-technical skills, including problem-solving, creativity, and technology adaptation. The research utilized a mixed-methods approach, combining quantitative and qualitative techniques. Data were collected through surveys, interviews, and observations from teachers and students in SMKs implementing AI-based teaching factories. Analysis was conducted using Partial Least Squares Structural Equation Modelling (PLS-SEM) and in-depth teacher interviews to evaluate readiness and integration challenges. Findings reveal that AI applications in teaching factories significantly enhance students' technological proficiency, learning efficiency, and industry-readiness. Teachers reported improved teaching effectiveness, although they faced obstacles in areas like teacher training and technological infrastructure. The study highlights the potential of AI in elevating vocational education but identifies barriers requiring attention, such as the need for continuous teacher development and robust infrastructure. Recommendations include targeted training programs, increased investment in technology, and curriculum revisions to integrate AI comprehensively. Implementing AI in SMKs presents a promising strategy to address the evolving demands of Industry 4.0, enhancing educational outcomes for students and teaching effectiveness for educators.