Teach Mate AI Agent: A Smart Assistant for Educators

This paper introduces the Teach Mate AI Agent, an intelligent assistant designed to revolutionize the educational workflow by automating time-intensive administrative tasks for educators. The system provides a unified, AI-powered platform that integrates eight comprehensive modules to handle syllabus creation, lesson planning, assessment generation, and resource curation. By leveraging Google's advanced Gemini 1.5 model and a Retrieval-Augmented Generation (RAG) architecture, the agent edagogically sound content while ensuring factual accuracy through user-provided documents. The primary objective is to reduce the administrative burden on educators by up to 90%, thereby enabling them to dedicate more time to student engagement and mentorship. The technology stack includes Python with Streamlit for the front-end, and ChromaDB as the vector database for the RAG system.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-13
DOI
https://doi.org/10.5281/zenodo.17337482
Primary Topic
Intelligent Tutoring Systems and Adaptive Learning
Type
article
Field-Weighted Citation Impact
0.00
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article

Teach Mate AI Agent: A Smart Assistant for Educators

Zenodo (CERN European Organization for Nuclear Research)
Intelligent Tutoring Systems and Adaptive Learning
article

Teach Mate AI Agent: A Smart Assistant for Educators

article en

Abstract

This paper introduces the Teach Mate AI Agent, an intelligent assistant designed to revolutionize the educational workflow by automating time-intensive administrative tasks for educators. The system provides a unified, AI-powered platform that integrates eight comprehensive modules to handle syllabus creation, lesson planning, assessment generation, and resource curation. By leveraging Google's advanced Gemini 1.5 model and a Retrieval-Augmented Generation (RAG) architecture, the agent edagogically sound content while ensuring factual accuracy through user-provided documents. The primary objective is to reduce the administrative burden on educators by up to 90%, thereby enabling them to dedicate more time to student engagement and mentorship. The technology stack includes Python with Streamlit for the front-end, and ChromaDB as the vector database for the RAG system.

Zenodo (CERN European Organization for Nuclear Research)
PRIST University (IN)
Quality Education
Openalex Percentile: Top 24%
Intelligent Tutoring Systems and Adaptive Learning
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