AI-Driven Automated Answer Script Evaluation System: A Literature Review

Authors

  • Rajashree M Byalal, H P Darshan Urs, K M An kumar, Koushal K Nayak, Sheshagiri KSIT, Bengaluru, India Author

DOI:

https://doi.org/10.70849/IJSCI

Keywords:

Answer sheet evaluation, AI in education, OCR, NLP, machine learning, automated grading

Abstract

Descriptive handwritten exam replies are still evaluated in a subjective and time-consuming manner. Assessment must be automated immediately due to the increasing size of classes and the necessity for prompt feedback. A survey of recent developments in automated grading employing artificial intelligence (AI), optical character recognition ( OCR), and natural language processing (NLP) is presented in this work. We examine ten significant works from 2022–2025 , contrast their methodologies, and point out any deficiencies. The motivation for our suggested intelligent evaluation system, which combines feedback generation, scoring logic, semantic natural language processing, and OCR, is also described in the study.

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Published

22-11-2025

Issue

Vol. 2 No. 11 (2025): IJSCI VOLUME-02 ISSUE-11 NOVEMBER 2025

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

How to Cite

[1]
Rajashree M Byalal, H P Darshan Urs, K M An kumar, Koushal K Nayak, Sheshagiri, “AI-Driven Automated Answer Script Evaluation System: A Literature Review”, Int. J. Sci. Inno. Eng., vol. 2, no. 11, pp. 1198–1201, Nov. 2025, doi: 10.70849/IJSCI.