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22.11.2019

A Machine Learning Approach for Automated Evaluation of Short Answers Using Text Similarity Based on WordNet Graphs

verfasst von: Sonakshi Vij, Devendra Tayal, Amita Jain

Erschienen in: Wireless Personal Communications | Ausgabe 2/2020

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Abstract

Answer sheet evaluation is a time-consuming task that requires lot of efforts by the teachers and hence there is a strong need of automation for the same. This paper proposes a machine learning based approach that relies on WordNet graphs for finding out the text similarity between the answer provided by the student and the ideal answer provided by the teacher to facilitate the automation of answer sheet evaluation. This work is the first attempt in the field of short answer-based evaluation using WordNet graphs. Here, a novel marking algorithm is provided which can incorporate semantic relations of the answer text into consideration. The results when tested on 400 answer sheets yield promising results as compared with the state-of-art.

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Titel: A Machine Learning Approach for Automated Evaluation of Short Answers Using Text Similarity Based on WordNet Graphs
verfasst von: Sonakshi Vij
Devendra Tayal
Amita Jain
Publikationsdatum: 22.11.2019
Verlag: Springer US
Erschienen in: Wireless Personal Communications / Ausgabe 2/2020
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI: https://doi.org/10.1007/s11277-019-06913-x

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