Enhancing Literary Analysis and Appreciation Through AI-Generated Visuals
AI technologies offer innovative possibilities for enhancing literary education. Generative AI models can facilitate textual analysis, helping students understand themes, narrative structures and other elements within literary works. Moreover, some generative models can transform written narratives into vivid visual or video representations, fostering multimodal engagement with literature. However, studies also raise concerns about over-reliance on AI, which could undermine independent critical thinking, interpretative skills and creativity. This project focuses on text-to-image and text-to-video AI models. It aims to explore how AI-generated visuals - such as images and videos- can facilitate close reading of literary works. More specifically, it will investigate how students interact with AI tools to generate visuals based on the text, how those visuals influence their understanding of the text, how they interpret and respond to the visuals, and how this process supports close reading and enhances literary analysis and appreciation. This proposal outlines the main concepts of the project along with its implementation plan. The project will implement this pedagogical approach in literature courses and assess its impact through systematic research.
