Automated Subjective Answer Scoring with Natural Language Processing and Machine Learning

Authors: Ghumare Sonali, Sayyed Fazila, Rayate Abhay, Sapkal Harshal, Rokade Sharad

Country: India

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Abstract: Every year boards and universities exams are conducted offline mode. Large number of student attend subjective type exam. For evaluation of such large number of paper manually required hard efforts. Sometimes quality of evaluation may change according to mood of evaluator. The evaluation work is very lengthy and time consuming. Competitive and entrance exams typically contain objective or multiple choice questions. These exams are evaluated on machine as they conducted on machine and therefore their evaluation is easy. It also saves multiple resources and human interaction and hence it is errorless. There are multiple system are available for evaluation objective (MCQ) type question but there is no provision for subjective (Descriptive) type question. It will be very helpful for educational institutions if the process of evaluation of descriptive answers is automated to capably assess student’s exam answer sheets.

Keywords: Subjective Answer Evaluation, Big Data, Machine Learning, Natural Language Processing, Word2vec.

Paper Id: 230359

Published On: 2023-11-10

Published In: Volume 11, Issue 6, November-December 2023

Cite This: Automated Subjective Answer Scoring with Natural Language Processing and Machine Learning - Ghumare Sonali, Sayyed Fazila, Rayate Abhay, Sapkal Harshal, Rokade Sharad - IJIRMPS Volume 11, Issue 6, November-December 2023.

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