Document-Grounded Generative AI for Tamil Explanations of English Engineering Materials: A Semantic Retrieval Approach
This paper presents a document-grounded educational assistant for engineering learners who prefer Tamil explanations of English study materials. The system extracts PDF text, creates chunks, encodes them with Tamil-ai/tamil-embed-base, retrieves relevant passages using FAISS, and uses Phi-3 Mini for context-based answers. The revised implementation uses the Gemini API for Tamil-language generation. Two generated quiz-answer-review reports—one based on an introductory Artificial Intelligence PDF and one based on a Python Programming PDF—each recorded 7 correct answers out of 10 (70%). These scores describe the quiz takers’ results, not the accuracy of the quiz-generation system. Inspection of the reports identified fragmented questions, PDF extraction artifacts, and generic explanations. The results therefore support the feasibility of the prototype while showing that quiz quality requires further validation.
Authors
- Jeeva S.
- Mohan Raja V.
- Kannan N
- Rosenpranav K. S.
- Dr. V. Kamalaveni
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-10-27
- DOI
- https://doi.org/10.5281/zenodo.23682704
- Primary Topic
- Artificial Intelligence in Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00