Digital and AI-Driven Transformation of Learning in Vocational Education: Implementing an Innovative Instructional Model - Rina Novalinda; Citra Meidyna Budhipradipta; Rahmat Fadillah (Journal of Education Technology, 2026)
The rapid advancement of digital technologies and Artificial Intelligence (AI) requiring learning environments that foster analytical reasoning, autonomy, and higher-order thinking. Responding to this need, this study developed and evaluated an innovative instructional model integrating digital learning resources and AI-assisted tools to enhance students’ cognitive performance and engagement in the Klinik Refraksi course at Akademi Refraksi Optisi YLPTK Padang. The objective of the study was to examine the model’s validity, practicality, and effectiveness in improving learning outcomes, higher-order thinking skills (HOTS), and student engagement. Employing an R&D design through the ADDIE framework combined with a quasi-experimental approach, the model was implemented in one experimental class, while a parallel class received conventional instruction. Instruments included pretest–posttest assessments, HOTS rubrics, engagement observations, and AI-generated learning analytics. Results indicated high expert validation (M = 4.60) and strong practicality ratings (89.8%). The experimental group demonstrated substantial gains in learning outcomes (N-Gain = 0.63), improvements in HOTS—analysis (+27), evaluation (+32), and creation (+37)—and higher engagement across behavioral, emotional, and cognitive dimensions compared to the control group. These findings show that integrating structured digital activities with AI-supported guidance enhances conceptual understanding, reasoning, and participation. The study concludes that the model is pedagogically feasible and recommendable for broader application within digital and AI-driven vocational education contexts.