This study explores the integration of humanoid robots and AI-driven speech technologies in educational settings, focusing on enhancing student engagement and learning outcomes. By employing a fine-tuned language model using the OpenAI ChatGPT API and tailored with subject-specific data, we aim to support interactive learning and motivate students. Designed to provide refined and accurate responses in targeted academic areas, this model seeks to deepen students' understanding and engagement with the curriculum. The study investigates whether this fine-tuning approach can improve student motivation, deliver more contextually relevant answers, and assist teachers in managing individualized learning paths more effectively. Through comparative analysis of student interaction, performance, and feedback, we aim to provide insights into optimizing AI and robotic technologies in the classroom. The findings will contribute to establishing best practices for deploying fine-tuned AI models in educational environments, fostering a more adaptive and responsive learning experience for students.

Keywords: Artificial intelligence, Information educational environment, Artificial intelligence in classrooms, Education.