This study evaluates Synthesia, an AI-driven video platform, as a computer-assisted language learning (CALL) tool in Hong Kong university English courses. Focusing on its ability to address three challenges—differentiating materials for diverse classrooms, enhancing academic English engagement, and reducing instructor workload—the research involved 6 instructors and 120 students. Synthesia’s avatars and multilingual tools were used to create context-specific resources (e.g., academic presentation exemplars). Quantitative analysis of pre/post-speaking assessments showed moderate fluency improvements (Cohen’s d = 0.42), supported by qualitative feedback on confidence gains. However, limitations included Synthesia’s inability to model natural conversational turn-taking, reflecting broader AI pragmatism constraints (Hockly, 2024).

Instructors reported 35% time savings in material creation but required post-editing to meet local English for Academic Purposes standards. Adjustable speech pacing and visual annotations strongly correlated with listening comprehension gains (r = 0.67). While Synthesia improved accessibility (e.g., academic hedging tutorials), 22% of students noted reduced motivation with excessive avatar use, highlighting risks of over-reliance (Huang et al., 2021).

The study positions Synthesia as a supplemental CALL tool within blended learning frameworks, recommending strategic integration for preparatory/reinforcement tasks. Key suggestions include pairing AI materials with live communication practice and establishing ethical guidelines for AI in language education.