Integrating Generative Text-to-Video AI in Linguistically Responsive Pedagogy: A Case Study of Multilingual Learners in Higher Education

Abstract

Generative Artificial Intelligence (AI) has made far-reaching changes in the educational landscape in the recent years. It has the potential to automate tasks and create adaptive and personalized learning environment. A recent development is the generation of text-to-video models driven by the development of video diffusion models. This study aims to analyze how Generative Text-to-Video (T2V) AI can enhance linguistically responsive teaching in multilingual higher education settings. Using a mixed-method approach, this research evaluates the effectiveness of AI Tools in relation to the Linguistically Responsive Teaching (LRT) framework. The findings would help the instructors to enhance content accessibility, and foster inclusive pedagogical practices.