The Use of AI for Learning Planning Viewed from the UTAUT Perspective

Abstract

This research examines the determinants influencing vocational high school teachers’ behavioral intention and actual use of generative artificial intelligence (AI) in lesson planning, employing a modified Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework. A quantitative research design was implemented, utilizing purposive sampling to select 92 teachers from SMK Negeri 2 Salatiga who had prior experience with generative AI in instructional design. Data were collected through a structured Likert-scale questionnaire and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4, assessing construct validity, reliability, and structural relationships. The findings indicate that Behavioral Intention constitutes the most substantial predictor of Use Behavior (β = 0.958), significantly shaped by Hedonic Motivation, Habit, Price Value, Performance Expectancy, and Effort Expectancy. Notably, Lesson Planning exhibits a negative association with Use Behavior (β = -0.378), suggesting that rigid or bureaucratic planning frameworks may impede the integration of AI technologies. Demographic moderators, including age, gender, professional experience, educational attainment, and willingness, demonstrated no statistically significant effects. The study underscores that the adoption of AI in educational contexts is predominantly driven by motivational and perceptual constructs rather than demographic variables. The implications emphasize the necessity for adaptive lesson design, targeted teacher professional development focusing on technological pedagogical content knowledge (TPACK), and supportive policy frameworks to foster effective and contextually relevant AI integration in vocational education.