عليرضا قاسمي

This research presents an innovative solution to address learning challenges in individuals with diverse learning disabilities. Focusing on the intersection of game-based learning and interactive technologies, the research designs and develops a 3D, immersive cognitive game. The research leverages the capabilities of the Unity game engine and the C# programming language and is supported by extensive literature by comprehensively reviewing historical approaches, technological innovations, and the effectiveness of game-based learning. At the core of this research is an intelligent guidance system that is developed to improve cognitive performance and reduce confusion in users. The proposed system consists of two main parts: First, a time- and performance-based guidance system that provides textual guidance and navigation in the form of a minimap using data such as elapsed time, number of steps taken, and overall user performance. Second, the improved system uses reinforcement learning that uses the Q-Learning algorithm to optimize and adapt guidance based on the user's past experiences and current conditions. To eva‎luate the effectiveness of the proposed system, experiments were conducted with the participation of a group of individuals with learning disabilities. In these experiments, metrics such as task completion speed, accuracy, confusion level, and user satisfaction were examined. The results showed that the proposed systems were able to significantly improve users' cognitive performance and reduce confusion. In particular, the use of the Q-Learning algorithm in the guidance system led to better adaptation of guidance to the individual needs of users and provided a more personalized learning experience. The findings of this study indicate that combining game-based learning with smart technologies can be an effective solution to support individuals with learning disabilities. These results not only confirm the importance of developing smart guidance systems, but also provide a basis for future research in the field of using reinforcement learning in educational and inclusive environments. Finally, this research, by providing a practical framework for the development of intelligent guidance systems, can be used as a reference for developers and researchers in related fields. It is hoped that these achievements will be an effective step towards cognitive and learning improvement for people with learning disabilities.

سيستم‌هاي هوشمند , يادگيري‌تقويتي , اختلالات‌يادگيري , بهبود‌شناختي , الگوريتم Q-Learning , منطق فازي , يادگيري مبتني بر بازي , موتور بازي سازي يونيتي

intelligent systems , reinforcement learning , learning disorders , cognitive improvement , Q-Learning algorithm , fuzzy logic , game-based learning , Unity game engine

Alireza Ghasemi

Dr. Behrouz Minaei Bidgoli