Using AI to enhance digital multimodal composing: EFL learners’ semiotic decision-making, self-efficacy, enjoyment, and continuance intention

Abstract

Research has demonstrated various advantages of integrating digital multimodal composing (DMC) into the teaching and learning of English as a foreign language (EFL). However, challenges persist, particularly due to the labor-intensive nature of multimodal production. As artificial intelligence (AI) technologies evolve, they provide valuable opportunities to enhance DMC, particularly through innovations like text-to-video generation. This study implemented an AI-enhanced approach to DMC in an academic English course, where students utilized AI-powered text-to-video technology to convert technical proposals into video formats for effective technical pitching. Drawing on data from 75 students, including their video compositions, written reflections, and post-task questionnaire responses, the findings show that students critically assessed the AI-generated videos based on three key criteria: text-video consistency, visual engagement, and auditory elements. Moreover, students reported high levels of self-efficacy, enjoyment, and a strong intent to continue using the technology. This Forum paper emphasizes the necessity of aligning language education with the demands of a digitally mediated and multimodal landscape in the AI era, offering valuable insights for educators and curriculum developers.