Exploring Pathways to Enhance Students' Acceptance of an Artificial Intelligence Speech Evaluation Program for EFL Speaking Practice from a Translanguaging Perspective: An Application of the Technology Acceptance Model

In the era of globalization and digitalization, translanguaging, which integrates multimodal resources, is gaining prominence in education. As AI oral evaluation systems are increasingly used in language teaching, translanguaging practices are becoming more common. Traditional English education emphasizes basic "listening and speaking" skills, but these fall short in the multimodal educational environment, necessitating a focus on transmodal listening and speaking abilities. This paper uses the Technology Acceptance Model (TAM) to analyze its impact on students' acceptance of oral evaluation and its limitations. The study finds that most participants find the AI program useful, enjoyable, and easy to use, with a strong intention to continue. Perceived usefulness (PU) and perceived enjoyment (PE) are key predictors of behavioral intention (BI). However, issues like user interface design, automatic feedback accuracy, and the lack of face-to-face interaction are noted. Based on these findings and from a translanguaging perspective, this paper proposes ways to boost students' acceptance of AI oral evaluation systems. It suggests optimizing system design for multimodal interaction, tailoring the interface for diverse cultures, enriching content with cross-cultural elements, and using project-based and cooperative learning. These steps aim to enhance the application of educational technology and students' oral learning motivation and confidence.