Tool-Based Retrieval-Augmented Generative as an Automated Assistant in Object-Oriented Programming Course

The integration of artificial intelligence into educational tools is transforming learning environments. In computer science, students frequently encounter challenges with complex concepts and practical applications. While LLMs offer valuable support, their responses can sometimes lack precision or rely on outdated information. Addressing these limitations is essential to enhance the effectiveness of AI-based tools in educational support. The main objective of this paper is to propose a tool-based RAG as automated assistant in an OOP Course. The tool was tested using common student queries and its responses were compared with those generated by ChatGPT. Initial observations suggest that RAG consistently generated contextually relevant responses due to its ability to access pertinent information from a structured knowledge base, resulting in more precise and applicable answers for students. The introduction of a RAG-based tool in classrooms has the potential to enhance student learning by providing instant, tailored responses to specific queries.