AI-Tutor system | ||||
| Journal of the ACS Advances in Computer Science | ||||
| Volume 16, Issue 1, 2025 PDF (515.77 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/asc.2025.431303 | ||||
 View on SCiNiTO | ||||
| Author | ||||
| Mohamed Sakr | ||||
| The Higher Institute of Computer and Information Technology, El Shorouk Academy, Cairo, Egypt | ||||
| Abstract | ||||
| The AI-Tutor system is a cutting-edge educational assistant that utilizes advanced natural language processing and machine learning, particularly the Gemini model, to provide interactive lessons and tailored feedback based on users' content. It streamlines tutoring tasks and adapts to different learning styles, addressing current educational challenges more effectively than traditional methods. Evaluations suggest that it enhances learner engagement and operational efficiency while remaining scalable. The project builds on prior developments in intelligent tutoring systems, incorporating innovative features like dynamic content generation and real-time, context-aware interactions. In its development, the Agile methodology guided the process, focusing on collaboration and user feedback, while machine learning techniques enabled personalized predictions and adaptive learning paths. The system includes key components such as content ingestion and transformation, an interactive user interface, and feedback mechanisms. Evaluation results demonstrated high accuracy in content structural integrity, explanation quality, and question relevance. Overall, the AI-Tutor system represents a significant advancement in educational technology, paving the way for future enhancements and broader applications in learning environments. | ||||
| Keywords | ||||
| AI-Tutor system; machine learning; large language models LLM; Gemini model; personalized feedback; educational technology; adaptive learning; automation in education | ||||
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