This study aimed to develop a microlearning-based digital storytelling instructional model (MICRO-DST) to enhance English speaking skills among Grade 9 EFL students and to examine its implementation effects. Employing a research and development methodology with a one-group pretest–posttest quasi-experimental design, th...
Kanyakorn Tammati, Potsirin Limpinan, Thada Jantakoon· World Journal of Education· 0 citations
Unlike conventional UTAUT assumptions that emphasize usefulness and ease of use, the findings suggest that trust, privacy awareness, social endorsement, and policy alignment are critical determinants of GenAI acceptance in administrative contexts.
Porntep Chooppawa, Potsirin Limpinan, Thada Jantakoon· World Journal of Education· 0 citations
The findings confirm that the U-SIM Model is both theoretically grounded and practically effective, offering a scalable solution for IoT education in resource-constrained vocational contexts.
The acceptance and use of GenAI among private vocational teachers in Thailand is examined through the Unified Theory of Acceptance and Use of Technology (UTAUT), with particular attention to the intention-behavior gap.
This study examines the determinants of Generative AI acceptance for supporting innovative learning among private vocational education instructors in Thailand by integrating the Information Systems Success Model, the Technology Acceptance Model, the Technology Acceptance Model, the Unified Theory of Acceptance and Use...
Ponprom Chooppawa, Potsirin Limpinan, Thada Jantakoon· World Journal of Education· 0 citations
Examination of levels of perception and opinion of vocational students toward factors influencing their acceptance and use of Generative AI for learning and a structural model of causal relationships among such factors revealed that vocational students held highly positive opinions regarding GenAI acceptance across all...
This study examined GenAI acceptance among private vocational teachers in Thailand by extending the Unified Theory of Acceptance and Use of Technology (UTAUT) with three AI-specific constructs: AI Literacy, Trust, and Perceived AI Risk and tested Behavioral Intention as an antecedent of Digital Competency.
