Recent Trends in Answer Script Evaluation – A Literature Survey
- https://doi.org/10.2991/ahis.k.210913.014How to use a DOI?
- Answer Script Grading, Machine Learning (ML), Natural Language Processing (NLP)
Assessment of answer scripts is an integral part of an examination and education system. A fair, consistent, unbiased, and correct valuation ensures the integrity of an examination system and is important for all education institutions. Since manual valuation is cumbersome and can be biased or influenced by the perception/mood of the evaluator, automatic grading of scripts has become very relevant. Automatic short answer grading (ASAG) techniques have been widely researched in the last decade and have assumed increased relevance because of online teaching and examinations during the Covid-19 pandemic. This review paper focuses on the recent works in the area of automatic answer grading and compares the techniques, methodologies employed, and the consequent results to evaluate their effectiveness. It discusses the advantages and limitations of the techniques by systematically categorizing the questions into both long/short as well as open-ended/close-ended questions and suggests a new model for improving the grading outcomes.
- © 2021, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - A.K.R Maya AU - Javed Nazura AU - B. L Muralidhara PY - 2021 DA - 2021/09/13 TI - Recent Trends in Answer Script Evaluation – A Literature Survey BT - Proceedings of the 3rd International Conference on Integrated Intelligent Computing Communication & Security (ICIIC 2021) PB - Atlantis Press SP - 105 EP - 112 SN - 2589-4900 UR - https://doi.org/10.2991/ahis.k.210913.014 DO - https://doi.org/10.2991/ahis.k.210913.014 ID - Maya2021 ER -