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Automatic generation of multiple choice questions for e-assessment

Automatic generation of multiple choice questions for e-assessment It is important for students to expertise in their field of study, because there is an agile change in all the domains. Even though resources are available to learn, proper assessment helps them to improve upon their knowledge. In this paper, an automatic generation of multiple choice questions on any user-defined domain is proposed. It first extracts text relevant to the given domain from the web and summarises using fireflies-based preference learning. The sentences in the summary are transformed into stem for the MCQs. The distractors are generated using similarity metrics such as hypernyms and hyponyms. The system also generates analogy questions to test the verbal ability of the students. Keywords: analogy; e-assessment; fireflies-based preference learning; hypernym; hyponym; MCQ; natural language processing; ontology; parts-of-speech; summariser. Reference to this paper should be made as follows: Santhanavijayan, A., Balasundaram, S.R., Hari Narayanan, S., Vinod Kumar, S. and Vignesh Prasad, V. (2017) `Automatic generation of multiple choice questions for e-assessment', Int. J. Signal and Imaging Systems Engineering, Vol. 10, Nos. 1/2, pp.54­62. Biographical notes: Santhanavijayan is an Assistant Professor of CSE in the National Institute of Technology, Tiruchirappalli. He received his M.E. degree in CSE from Anna University, Chennai in 2007. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Signal and Imaging Systems Engineering Inderscience Publishers

Automatic generation of multiple choice questions for e-assessment

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Publisher
Inderscience Publishers
Copyright
Copyright © 2017 Inderscience Enterprises Ltd.
ISSN
1748-0698
eISSN
1748-0701
DOI
10.1504/IJSISE.2017.084571
Publisher site
See Article on Publisher Site

Abstract

It is important for students to expertise in their field of study, because there is an agile change in all the domains. Even though resources are available to learn, proper assessment helps them to improve upon their knowledge. In this paper, an automatic generation of multiple choice questions on any user-defined domain is proposed. It first extracts text relevant to the given domain from the web and summarises using fireflies-based preference learning. The sentences in the summary are transformed into stem for the MCQs. The distractors are generated using similarity metrics such as hypernyms and hyponyms. The system also generates analogy questions to test the verbal ability of the students. Keywords: analogy; e-assessment; fireflies-based preference learning; hypernym; hyponym; MCQ; natural language processing; ontology; parts-of-speech; summariser. Reference to this paper should be made as follows: Santhanavijayan, A., Balasundaram, S.R., Hari Narayanan, S., Vinod Kumar, S. and Vignesh Prasad, V. (2017) `Automatic generation of multiple choice questions for e-assessment', Int. J. Signal and Imaging Systems Engineering, Vol. 10, Nos. 1/2, pp.54­62. Biographical notes: Santhanavijayan is an Assistant Professor of CSE in the National Institute of Technology, Tiruchirappalli. He received his M.E. degree in CSE from Anna University, Chennai in 2007.

Journal

International Journal of Signal and Imaging Systems Engineering – Inderscience Publishers

Published: Jan 1, 2017

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