AI Tools and Saudi University English Translation Students: A Mixed-Methods Study Based on TAM
DOI:
https://doi.org/10.17507/tpls.1512.27Keywords:
AI in education, artificial intelligence, EFL, translation studies, technology acceptance modelAbstract
The study aims to explore the acceptance and utilization of AI tools in translation courses by English language learners in Saudi Arabia using the Technology Acceptance Model (TAM) to enhance their professional translation skills. For data collection purpose, the study employed a mixed-methods design, combining a survey of 114 bachelor's and master's translation students with in-depth interviews of 10 participants. This approach explored students' perceptions, usage patterns, and barriers to AI tool adoption. The inclusion of diverse academic levels enriched the findings and enhanced the study's relevance to broader translation education context. The study investigates three research questions that focus on Saudi EFL students’ adoption rate of AI tools for translation, their participation with these tools, and their perceptions regarding the integration of AI in translation practice. The study revealed that the majority of Saudi Arabian translation students learning English as a foreign language found AI tools useful. However, they expressed concern about the potential negative impact of overuse on their translation skills. Furthermore, the findings highlight the need to integrate AI tools into university curricula to better prepare students for the demands of today's translation industry. The results indicate that translation courses at universities need to include the integration of AI tools to train students effectively for the evolving industrial requirements and technological landscape. This research contributes to the growing body of studies on using AI tools in language education and advocates for including AI literacy education within language programs to enhance translation and academic writing achievements.
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