Modeling the use behavior of interpreting technology for student interpreters: An extension of UTAUT model

The growing popularity of interpreting technology in the industry has raised awareness of incorporating it into interpreter education. However, it is unclear what factors may contribute to students’ behavioral use and the consequent effects of using it. With the addition of three external factors (motivation, task-technology fit, and technology self-efficacy) to the unified theory of acceptance and use of technology model (UTAUT), we surveyed 182 Chinese student interpreters and tested 14 proposed hypotheses using their response data. Data were analyzed using descriptive statistics and structural equation modeling (SEM). The findings indicate that students’ actual use of interpreting technology is primarily predicted by their behavioral intention, followed by facilitating conditions. Three factors are found to positively and significantly affect students’ behavioral intention, of which task-technology fit and performance expectancy have the most significant influence. Furthermore, performance expectancy can positively affect students’ motivation to learn interpreting, whereas motivation could exert an effect on use behavior. The enhanced UTAUT model identifies significant factors associated with students’ use of interpreting technology and confirms its positive effects. Theoretical implications and practical significance for interpreting teaching and education policy-making regarding the findings are also discussed.