ADAPTIVE AI-TUTORS FOR THEATRE AND DRAMA EDUCATION
DOI:
https://doi.org/10.29121/shodhkosh.v7.i1s.2026.7088Keywords:
Adaptive AI Tutor, Theatre Education, Drama Pedagogy, Multimodal Learning Analytics, Real-Time Feedback, Embodied Learning, Intelligent Tutoring SystemsAbstract [English]
Theatrical and dramatical pedagogy is based on the embodied and experiential learning processes where feedback plays a central role but is usually subjective, delayed, and hard to scale. The paper describes a flexible AI-tutor that can integrate with real-time, post-performance feedback to enhance the instruction of drama in the studio utilizing pedagogical theory. The suggested system includes the fusion of multimodal sensing (vocal, sight, and movement), explainable AI models, and user-oriented adaptation control to examine expressiveness, coherence, and coordination of vocal delivery, physical expression, emotional expression, and coordination between the ensemble members. The closed-loop architecture is capable of providing low-latency real-time cues to stabilize the rehearsal process along with more comprehensive post-performance analytics to aid the reflective process and self-regulation. The experimental assessment on the representative data proves that the adaptive AI-tutor can outperform traditional rehearsal and non-adaptive analytics, as it exhibits measurable gains in the pacing consistency, gesture variety, stage presence and learner confidence, and retains the creative autonomy and reasonable cognitive loads. At the system level, it has been verified that edge-based inference can meet real-time latency requirements that are appropriate when using live rehearsal. The results emphasize the significance of the correspondence of AI-informed feedback with the constructivist, experiential, and embodied principles of learning.
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Copyright (c) 2026 Dr. Biswajit Kalita, Prince Kumar, Saraswati B, Nishant Kulkarni, Dr. Yogita Deepak Sinkar, Dr. Mohammad Afsan
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