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© 2026 IJSREM – International Journal of Scientific Research in Engineering and Management. This is an open-access journal. Articles are published under the Creative Commons Attribution (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM58117

Teacher Assistance Platform

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM58117

Volume:

10 |

3 |

Mar 2026

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM58117

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

ON

Omkar Nayak

MN

Mohit Nilvarn

PP

Pratham Pradeshi

RY

Ranjeet Yadav

JP

Jayashri Palkar

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Abstract

The education system is changing fast with technology. This has brought chances for teachers and students but it also means teachers have a lot more work to do. Teachers have to do things like write down what they said in class get tests give grades and talk to each student one on one. These tasks take a lot of time so teachers have time to actually teach. This paper is about a tool called the Teacher Assistance Platform that uses artificial intelligence to help teachers with these tasks. The Teacher Assistance Platform uses computers to understand what people are saying, language models that can understand a lot of things and a system that gets all the parts working together. The Teacher Assistance Platform automates the tasks that teachers have to do, like lecture documentation and assessment preparation and grading and personalized feedback generation, for students. The Teacher Assistance Platform is an AI-driven tool that can really help teachers. The proposed system converts lecture audio into structured textual content, performs abstractive summarization, generates assessments, evaluates student submissions, and delivers personalized feedback through an integrated analytics dashboard. A modular multi-agent architecture enables task parallelism, scalability, and reliability. Experimental evaluation demonstrates significant improvements in processing efficiency, grading consistency, and content quality compared to manual methods. The results confirm that agent-based AI systems can effectively augment educators, enabling a more intelligent, efficient, and data-driven educational ecosystem.

KEYWORDS

Artificial Intelligence Teacher Assistance Platform Large Language Models Multi-Agent Systems Speech-to-Text Educational Automation.

Cite This Article

Omkar Nayak, Mohit Nilvarn, Pratham Pradeshi, Ranjeet Yadav, Jayashri Palkar, "Teacher Assistance Platform," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 3, Mar 2026. https://doi.org/10.55041/IJSREM58117

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Publication Date

3/24/2026

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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