Moodle-bot: An Intelligent Teaching Assistant for Databases and Information Systems

Moodle-bot is an educational chatbot that combines Large Language Model (LLM) and Retrieval-Augmented Generation (RAG) technologies. It is designed to address problems such as difficulty understanding concepts, fragmented knowledge points, and lack of instant Q&A when students learn databases and information systems. It provides accurate, context-aware teaching support to facilitate personalized learning and efficient Q&A.

Project Background

In the study of database and information system courses, students often encounter problems such as difficulty understanding concepts, fragmented knowledge points, and no instant Q&A channels. Traditional tools only provide static document queries and cannot offer personalized explanations. Moodle-bot emerged as the times require, providing accurate, context-aware teaching support through LLM+RAG technology.

Core Architecture and Technology Selection

Driven by Large Language Model

Relying on the understanding and generation capabilities of LLM, it can answer questions about relational database design, SQL optimization, information system architecture, etc.

Retrieval-Augmented Generation (RAG)

• Knowledge base construction: Load authoritative materials such as course textbooks and reference documents
• Semantic retrieval: Retrieve the most relevant fragments when a question is asked
• Context enhancement: Inject retrieved content into LLM prompts
• Accurate answers: Generate based on real information, reducing the risk of hallucinations

This design ensures the accuracy and timeliness of answers.

Functional Features and Educational Value

Instant Q&A and Concept Clarification

Answer basic (e.g., Third Normal Form) or advanced (e.g., multi-table join optimization) questions at any time.

Context-Aware Dialogue

Supports multi-turn conversations, remembers historical context, and allows for step-by-step discussion of topics.

Personalized Adjustment

Adapts the detail level of answers according to the depth of the question to meet the needs of different students.

Resource Recommendation

Recommends resources such as textbook chapters, papers, and cases based on the question.

Application Scenarios and Practical Significance

Classroom Assistance

Teachers use it as a real-time Q&A tool to enhance interactivity and efficiency.

After-Class Self-Learning

Students can consult immediately when encountering problems, reducing reliance on teachers.

Pre-Exam Review

Quickly review knowledge points and generate review key points and practice questions.

Key Points of Technical Implementation

Knowledge Base Management

Regularly updated, supports import of formats such as Markdown/PDF/Word, making it easy for teachers to maintain.

Prompt Engineering

Carefully designed templates to specify answer style, format, and constraints.

Evaluation and Feedback

Collect student feedback, optimize retrieval strategies and prompts, and form an improvement loop.

Summary and Outlook

Moodle-bot is a beneficial attempt at the integration of education and AI, providing an innovative tool for database teaching.

For educators: Reduce the burden of Q&A and focus on in-depth tutoring; for students: Provide a learning partner available at any time and cultivate autonomous learning ability.

In the future, it may support multi-modal functions (such as code visualization), and Moodle-bot provides a reference for this direction.