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An automated essay scoring systems: a systematic literature review
Assessment in the Education system plays a significant role in judging student performance. The present evaluation system is through human assessment. As the number of teachers' student ratio is gradually increasing, the manual evaluation process becomes complicated. The drawback of manual eval...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8460059/ https://www.ncbi.nlm.nih.gov/pubmed/34584325 http://dx.doi.org/10.1007/s10462-021-10068-2 |
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author | Ramesh, Dadi Sanampudi, Suresh Kumar |
author_facet | Ramesh, Dadi Sanampudi, Suresh Kumar |
author_sort | Ramesh, Dadi |
collection | PubMed |
description | Assessment in the Education system plays a significant role in judging student performance. The present evaluation system is through human assessment. As the number of teachers' student ratio is gradually increasing, the manual evaluation process becomes complicated. The drawback of manual evaluation is that it is time-consuming, lacks reliability, and many more. This connection online examination system evolved as an alternative tool for pen and paper-based methods. Present Computer-based evaluation system works only for multiple-choice questions, but there is no proper evaluation system for grading essays and short answers. Many researchers are working on automated essay grading and short answer scoring for the last few decades, but assessing an essay by considering all parameters like the relevance of the content to the prompt, development of ideas, Cohesion, and Coherence is a big challenge till now. Few researchers focused on Content-based evaluation, while many of them addressed style-based assessment. This paper provides a systematic literature review on automated essay scoring systems. We studied the Artificial Intelligence and Machine Learning techniques used to evaluate automatic essay scoring and analyzed the limitations of the current studies and research trends. We observed that the essay evaluation is not done based on the relevance of the content and coherence. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10462-021-10068-2. |
format | Online Article Text |
id | pubmed-8460059 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-84600592021-09-24 An automated essay scoring systems: a systematic literature review Ramesh, Dadi Sanampudi, Suresh Kumar Artif Intell Rev Article Assessment in the Education system plays a significant role in judging student performance. The present evaluation system is through human assessment. As the number of teachers' student ratio is gradually increasing, the manual evaluation process becomes complicated. The drawback of manual evaluation is that it is time-consuming, lacks reliability, and many more. This connection online examination system evolved as an alternative tool for pen and paper-based methods. Present Computer-based evaluation system works only for multiple-choice questions, but there is no proper evaluation system for grading essays and short answers. Many researchers are working on automated essay grading and short answer scoring for the last few decades, but assessing an essay by considering all parameters like the relevance of the content to the prompt, development of ideas, Cohesion, and Coherence is a big challenge till now. Few researchers focused on Content-based evaluation, while many of them addressed style-based assessment. This paper provides a systematic literature review on automated essay scoring systems. We studied the Artificial Intelligence and Machine Learning techniques used to evaluate automatic essay scoring and analyzed the limitations of the current studies and research trends. We observed that the essay evaluation is not done based on the relevance of the content and coherence. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10462-021-10068-2. Springer Netherlands 2021-09-23 2022 /pmc/articles/PMC8460059/ /pubmed/34584325 http://dx.doi.org/10.1007/s10462-021-10068-2 Text en © The Author(s), under exclusive licence to Springer Nature B.V. 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Ramesh, Dadi Sanampudi, Suresh Kumar An automated essay scoring systems: a systematic literature review |
title | An automated essay scoring systems: a systematic literature review |
title_full | An automated essay scoring systems: a systematic literature review |
title_fullStr | An automated essay scoring systems: a systematic literature review |
title_full_unstemmed | An automated essay scoring systems: a systematic literature review |
title_short | An automated essay scoring systems: a systematic literature review |
title_sort | automated essay scoring systems: a systematic literature review |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8460059/ https://www.ncbi.nlm.nih.gov/pubmed/34584325 http://dx.doi.org/10.1007/s10462-021-10068-2 |
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