GAMIFIED LEARNING OF VISUAL CONCEPTS USING AI - Alex, Anu; Srishti, Pooja; P Thilagavathi; Nayak , Praveen Priyaranjan; Sharma, Sorabh; Keote, Minal (ShodhKosh: Journal of Visual and Performing Arts, 2025)
This paper introduces a gamified learning model based on AI and aimed at increasing the visual concept mastery with the use of adaptive instructions, real-time feedback, and motivational elements of a game. The classical methods of visual learning usually presuppose the unrestricted use of a fixed material and less personalization that leads to lower levels of involvement and poor mastering. The proposed system will overcome these shortcomings by incorporating a visual recognition module trained on deep learning, a mastery-related knowledge-tracing model, and a task selection policy that is based on reinforcement learning to establish an efficient challenge-skill balance. The framework is accompanied by a gamification engine which includes points, levels, streaks, and adaptive rewards to keep the learners motivated. The model was operationalised in a multi-layer system architecture and its performance measured using quantitative measures of performance and interaction data of actual learners. Findings indicate that recognition is high (94.7%), mastery gains are significant +0.37), learning uncertainty is low -0.92 entropy and engagement is high (91% task completion rate). There is high acceptance and usability with user experience ratings comprising of a System Usability Scale (SUS) score of 87.5. In general, the results indicate that AI-based gamification is a significant method of increasing learning efficiency, engagement and adaptability and it provides a scalable and smart intervention to educate visual concepts.