Automatic generation of analogy questions for student assessment: an Ontology-based approach
Abstract
Different computational models for generating analogies of the form ‘‘A is to B as C is to D’’ have been proposed over the past 35 years. However, analogy generation is a challenging problem that requires further research. In this article, we present a new approach for generating analogies in Multiple Choice Question (MCQ) format that can be used for students’ assessment. We propose to use existing high-quality ontologies as a source for mining analogies to avoid the classic problem of hand-coding concepts in previous methods. We also describe the characteristics of a good analogy question and report on experiments carried out to evaluate the new approach.Keywords: e-assessment; ontology; analogy questions; relational similarity; vector space model; corpus-based evaluation
(Published: 30 August 2012)
http://dx.doi.org/10.3402/rlt.v20i0.19198
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