Automated Learning and Scheduling Assistant using LLM

Large Language Models (LLMs) serve as the backbone of many AI applications, such as automatic content generation, virtual assistant and more. It is also used in automating the educational processes, such as scheduling the students’ assessments and managing teachers’ essential duties. The proposed study focuses on the design and development of an Automated Learning and Scheduling Assistant to facilitate the tasks like conducting unit test, managing internal assessment, and providing complete schedules of the students and the staff using LLM. The system is designed using the prompt engineering technique to improve the task automation efficiency. Retrieval-Augmented Generation (RAG) used helps in retrieving information and decision making, automating the test generation and the scheduling tasks. Data storage and retrieval are supported by the integration of the vector database. The primary objective of the proposed system is to enhance the educational process by automating the essential administrative and teaching functions, providing a scalable solution for the modern learning environment.