Validating a computer-assisted language learning attitude instrument used in Iranian EFL context: an evidence-based approach

A few computer-assisted language learning (CALL) instruments have been developed in Iran to measure EFL (English as a foreign language) learners' attitude toward CALL. However, these instruments have no solid validity argument and accordingly would be unable to provide a reliable measurement of attitude. The present study aimed to develop a CALL attitude instrument (CALLAI) to be used in the Iranian EFL context. A pool of 633 survey items was developed and 27 items were judged to be appropriate for measuring CALL attitude. The chosen items were translated and back-translated by experts and were administered to 1001 Iranian EFL learners. The psychometric features of the items were examined using three primary data analysis techniques: principal component analysis (PCA), confirmatory factor analysis (CFA), and the Rasch-Andrich rating scale model. Finally, a validity argument for CALLAI was developed which comprised five primary inferences. The findings from the psychometric analysis were mapped onto the validity framework. The validity framework is generally well-supported, although adding a few items could yield higher reliability coefficients.