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

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
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article

Document-Grounded Generative AI for Tamil Explanations of English Engineering Materials: A Semantic Retrieval Approach

Jeeva S., Mohan Raja V., Kannan N, Rosenpranav K. S. et al.
3 links
Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Education
article

Document-Grounded Generative AI for Tamil Explanations of English Engineering Materials: A Semantic Retrieval Approach

Jeeva S., Mohan Raja V., Kannan N, Rosenpranav K. S., Dr. V. Kamalaveni
article en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
Quality education
Openalex Percentile: Top 6%
Artificial Intelligence in Education
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