Predicting teachers’ intentions to implement bring your own device and take-home student device programs: a cognitive-affective-behavior framework with sem-ann analysis

Abstract Background Limited attention has been given to teachers’ intentions to implement Bring Your Own Device (BYOD) and Take-Home Student Device (THSD) as an integrated digital learning initiative, particularly from a psychological perspective. Accordingly, this study examines K-12 teachers’ behavioral intention to implement BYOD​ and ​THSD​ programs using the Cognitive–Affective–Behavior (CAB) framework. Methods A survey was conducted with 176 K-12 teachers in Taiwan. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), Artificial Neural Network (ANN) analysis, and Importance-Performance Map Analysis (IPMA). Results Understanding, ability, and self-confidence were positively associated with behavioral intention. Self-confidence mediated the relationships between the two cognitive factors and behavioral intention. In addition, the IPMA results showed that ability had the highest importance value, followed by self-confidence, whereas understanding showed the highest performance but the lowest importance. Conclusions The findings suggest that teachers’ readiness to implement BYOD and THSD depends not only on their understanding of the programs but also on their perceived ability and confidence to manage the demands of implementation. The study extends CAB-based research on educational technology implementation and provides implications for teacher preparation and digital education policy.