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Automatic Generation of Analogy Questions for Student Assessment: An Ontology-Based Approach
ARTICLE

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Research in Learning Technology Volume 20, ISSN 2156-7069

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. (Contains 3 tables and 1 figure.) [This paper was published in the ALT-C 2012 Conference Proceedings.]

Citation

Alsubait, T., Parsia, B. & Sattler, U. (2012). Automatic Generation of Analogy Questions for Student Assessment: An Ontology-Based Approach. Research in Learning Technology, 20,. Retrieved December 2, 2022 from .

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