The pedagogical transmission of theatrical texts within English literature often encounters limitations when confined to traditional, text-based instructional strategies. Theater, by its nature, is a performative genre intended to be seen, heard, and embodied. However, the absence of visual and kinetic stimuli in conventional classrooms may hinder students’ ability to fully interpret character psychology, emotional depth, and dramatic structure. This study investigates the educational potential of generative artificial intelligence (Gen AI) in bridging this gap. Specifically, it explores how AI-generated avatars, designed to exhibit facial expressions, gestures, vocal tones, and character-driven movements, can be utilized to recreate and simulate the performative dimensions of dramatic texts. By transforming literary characters into visually and aurally perceptible entities, this approach enhances learners’ comprehension, emotional resonance, and critical interpretation of theatrical works. The integration of Gen AI avatars is proposed not as a replacement but as an augmentation of traditional methods, offering a multimodal, experiential learning framework that aligns with the cognitive and technological orientation of 21st-century learners.
Krishna Rana (Mon,) studied this question.