Explaining primary school teachers’ intention to use digital learning platforms for students’ individualized practice: comparison of the standard UTAUT and an extended model

Introduction Though technologies for individualization appear to benefit primary school students’ learning, studies suggest that their integration remains sparse. Technology acceptance research has largely focused on exploring teachers’ general acceptance of educational technologies, although factors might predict usage intentions differently depending on the specific usage purpose of an educational technology. Digital learning platforms for individualized practice are comparably challenging and complex to use and so far, predictors of primary school teachers’ intention to integrate such technologies into lessons are largely unknown. Meanwhile, research on teachers’ technology acceptance generally lacks comparability due to the absence of a shared theoretical model and usage purpose specification. Methods In a sample of 272 German primary school teachers, this study aims to identify predictors of teachers’ acceptance of digital learning platforms for students’ individualized practice in consideration of the unified theory of acceptance and use of technology (UTAUT). To ensure a shared understanding, teachers were provided with a video which specified the addressed usage purpose. Regarding teachers’ usage intention, the explanatory power of the standard UTAUT predictors was investigated and compared with an extended UTAUT model accounting for seven additional context-specific predictors. Results The standard UTAUT significantly explained teachers’ usage intention, with performance expectancy, effort expectancy, and the availability of the necessary technical infrastructure showing significant associations with intention. However, neither a significant nor meaningful increase in explained variance was observed for the extended UTAUT model. Discussion Results suggest that the standard UTAUT model is sufficient in explaining teachers’ usage intention and that its extension by context-specific predictors provides no added value. Acceptance facilitating interventions should therefore target performance and effort expectancy as well as the availability of technical infrastructure. Thus, underlining that successful implementation of complex educational technologies should consider both, individual and structural factors.