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An Algorithm for Generating Gap-Fill Multiple Choice Questions of an Expert System

2021-09-17 02:49:37
Pornpat Sirithumgul, Pimpaka Prasertsilp, Lorne Olfman
arXiv_AI
       
Abstract

This research is aimed to propose an artificial intelligence algorithm comprising an ontology-based design, text mining, and natural language processing for automatically generating gap-fill multiple choice questions (MCQs). The simulation of this research demonstrated an application of the algorithm in generating gap-fill MCQs about software testing. The simulation results revealed that by using 103 online documents as inputs, the algorithm could automatically produce more than 16 thousand valid gap-fill MCQs covering a variety of topics in the software testing domain. Finally, in the discussion section of this paper we suggest how the proposed algorithm should be applied to produce gap-fill MCQs being collected in a question pool used by a knowledge expert system.

Abstract (translated)

URL

https://arxiv.org/abs/2109.11421

PDF

https://arxiv.org/pdf/2109.11421.pdf

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