Teachers’ technology acceptance of language skills applications use for children with autism spectrum disorders

Purpose: Digital technology fosters great opportunities to care children with autism spectrum disorders (ASD).This study investigates the key determinants for the acceptance of language skills applications among 592 teachers working with children with ASD, aged 7–10, from the country of Georgia. Materials and Methods: A modified version of the ‘Unified Theory of Acceptance and Use of Technology’ (UTAUT) model, enhanced by incorporating customization as an additional construct, was employed. The analysis utilized Structural Equation Modeling (SEM) and Artificial Neural Networks (ANN) to validate the framework. Results: SEM revealed that habit and customization significantly impact app adoption, while perceived-joyfulness had limited effects on behavioural-intention. Performance-expectancy, effort-expectancy and facilitating-conditions were found to be relevant for app adoption. ANN analysis confirmed these findings. Conclusion: Habit and customization are the most important predictors of both intention and adoption of digital applications among special education teachers to support children with ASD.