FACTORS INFLUENCING THE ACCEPTANCE AND USE OF ARTIFICIAL INTELLIGENCE IN TEACHING BY VOCATIONAL EDUCATION TEACHERS

Abstract

The study aims to explore the factors influencing the acceptance and use of artificial intelligence in teaching by vocational teachers through the Technology Acceptance Model. The research employs Structural Equation Modeling SEM to examine the relationships between factors such as self-efficacy, organizational support, teaching performance expectancy, and social influence on artificial intelligence acceptance behavior. Data collected from 365 teachers were analyzed using SPSS and AMOS software. Exploratory Factor Analysis and Confirmatory Factor Analysis were conducted to assess the reliability and validity of the measurement scales. The results indicate that teaching performance expectancy and social influence have a positive and statistically significant impact on teachers' use of artificial intelligence. In contrast, self-efficacy and organizational support do not have a significant impact. The study suggests that building trust in the effectiveness of artificial intelligence and fostering positive social influence are key factors in encouraging teachers to use artificial intelligence. Additionally, a clear legal framework and active organizational support are needed to facilitate the implementation of artificial intelligence in vocational training.