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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2506.21461 |
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| _version_ | 1866915360133873664 |
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| author | Mahmud, Tamim Al Hussain, Md Gulzar Kabir, Sumaiya Ahmad, Hasnain Sobhan, Mahmudus |
| author_facet | Mahmud, Tamim Al Hussain, Md Gulzar Kabir, Sumaiya Ahmad, Hasnain Sobhan, Mahmudus |
| contents | Evaluation is the method of assessing and determining the educational system through various techniques such as verbal or viva-voice test, subjective or objective written test. This paper presents an efficient solution to evaluate the subjective answer script electronically. In this paper, we proposed and implemented an integrated system that examines and evaluates the written answer script. This article focuses on finding the keywords from the answer script and then compares them with the keywords that have been parsed from both open and closed domain. The system also checks the grammatical and spelling errors in the answer script. Our proposed system tested with answer scripts of 100 students and gives precision score 0.91. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_21461 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Keyword-Based Technique to Evaluate Broad Question Answer Script Mahmud, Tamim Al Hussain, Md Gulzar Kabir, Sumaiya Ahmad, Hasnain Sobhan, Mahmudus Machine Learning Evaluation is the method of assessing and determining the educational system through various techniques such as verbal or viva-voice test, subjective or objective written test. This paper presents an efficient solution to evaluate the subjective answer script electronically. In this paper, we proposed and implemented an integrated system that examines and evaluates the written answer script. This article focuses on finding the keywords from the answer script and then compares them with the keywords that have been parsed from both open and closed domain. The system also checks the grammatical and spelling errors in the answer script. Our proposed system tested with answer scripts of 100 students and gives precision score 0.91. |
| title | A Keyword-Based Technique to Evaluate Broad Question Answer Script |
| topic | Machine Learning |
| url | https://arxiv.org/abs/2506.21461 |