Industrial Engineering Students’ Acceptance of PLC Learning: A PLS-SEM Analysis Based on the Technology Acceptance Model
The increasing adoption of Industry 4.0 technologies has intensified the need for industrial engineering graduates to acquire competency in Programmable Logic Controller (PLC) programming and industrial automation. Despite the growing implementation of PLC simulation software and digital laboratories, limited empirical research has examined the factors influencing students' acceptance of PLC learning. This study applied the Technology Acceptance Model (TAM) to investigate the relationships among perceived ease of use (PEOU), perceived usefulness (PU), attitude toward PLC learning (ATT), and behavioral intention to use PLC learning systems (BI). A quantitative cross-sectional survey was conducted with 399 undergraduate students from Sichuan Vocational and Technical College of Communications in China who had experience in PLC-related courses. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4. The measurement model demonstrated satisfactory reliability and validity, with outer loadings ranging from 0.797 to 0.886, composite reliability values between 0.882 and 0.911, and average variance extracted (AVE) values between 0.651 and 0.773. Both the Fornell-Larcker criterion and the heterotrait-monotrait ratio confirmed adequate discriminant validity. The structural model supported all proposed hypotheses. Perceived ease of use significantly influenced perceived usefulness (β = 0.416, p < .001) and attitude (β = 0.196, p < .001), perceived usefulness positively affected attitude (β = 0.372, p < .001), and attitude exerted the strongest influence on behavioral intention (β = 0.511, p < .001). The model explained 17.3% of the variance in perceived usefulness, 23.8% in attitude, and 26.1% in behavioral intention. The findings indicate that students' acceptance of PLC learning is most strongly associated with the perceived educational value of PLC instruction, while positive attitudes serve as the most important predictor of continued intention to engage with PLC learning. Multi-group analysis, preceded by measurement invariance testing, indicated that the effect of perceived ease of use on perceived usefulness was significantly stronger for female than for male students, while the model was otherwise invariant across gender, year of study, and prior PLC experience. These results provide practical implications for designing learner-centered PLC curricula that integrate user-friendly learning environments with authentic industrial automation experiences.