Design and implementation of an adaptive learning environment using Arduino, sensors, and AI within a simulated setting

This research project aims to develop an adaptive learning environment for robotics education using digital technologies, microcontrollers, and artificial intelligence. Within the scope of the project, Arduino microcontrollers and various sensors will be employed to enable students to carry out practical exercises in a simulated environment. Additionally, artificial intelligence algorithms will be used to assess students' knowledge levels and generate individualized learning paths. Throughout the project, technologies for real-time data collection, analysis, and adaptive instructional guidance will be implemented. A virtual simulation environment, developed using Python and web technologies, will allow students to engage in learning activities without requiring access to physical hardware. This platform is designed to enhance the level of STEM education in local educational institutions, facilitate the digitization of hands-on training, and strengthen human resource capacity in the field of robotics. The outcomes of the project will align with digital transformation demands and contribute to the training of specialists equipped with essential digital competencies for the modern industry. The system was evaluated using simulated sensor data and AI model performance was validated using classification metrics.