EXPLAINING HIGHER VOCATIONAL COMPUTER-MAJOR STUDENTS’ ATTITUDES TOWARD AN AI TEACHING PLATFORM: THE ROLES OF TASK–TECHNOLOGY FIT AND PERCEIVED USEFULNESS

Le résumé fourni par la source

As artificial intelligence continues to permeate vocational education, promoting students’ effective use of AI teaching platforms has become an important issue in instructional reform. Grounded in the Technology acceptance model (TAM), this study introduces task-technology fit (TTF) as an additional explanatory variable and examines the structural relationships among TTF, perceived usefulness (PU), and attitude toward using (ATU) AI teaching platforms among students in computer-related majors at higher vocational colleges. Using a stratified two-stage sampling method, a questionnaire survey was administered to 716 students from higher vocational colleges in Hunan Province. Structural Equation Modeling (SEM) was employed for empirical testing, and the results indicate a good model fit. The findings show that TTF has a significant positive effect on PU, suggesting that the alignment between platform functions and professional learning tasks provides an important basis for students’ usefulness perceptions. PU significantly and positively influences ATU, highlighting the critical role of perceived pragmatic value in platform acceptance. In addition, TTF also has a significant positive effect on ATU, indicating that it not only enhances students’ PU but also directly fosters positive attitudes toward platform use. Based on these findings, it is recommended that vocational colleges and platform developers optimize platform functions and learning workflows around the practical training tasks and learning scenarios of computer majors. Strengthening platform support for discipline-specific tasks can enhance students’ perceived usefulness and positive attitudes, thereby facilitating the effective application of AI in higher vocational computer education.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.