Automatic generation of analogy questions for student assessment: an Ontology-based approach

dc.creator	Bijan Parsia
dc.creator	Uli Sattler
dc.creator	Tahani Alsubait
dc.date	2012-08-01T00:00:00Z
dc.date.accessioned	2015-07-20T22:15:42Z
dc.date.available	2015-07-20T22:15:42Z
dc.identifier	10.3402/rlt.v20i0.19198
dc.identifier	2156-7069
dc.identifier	2156-7077
dc.identifier	https://doaj.org/article/ca4f30cdd6eb4016a8c7c67591c5f91b
dc.identifier.uri	http://evidence.thinkportal.org/handle/123456789/17856
dc.description	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.
dc.language	English
dc.publisher	Co-Action
dc.relation	http://www.researchinlearningtechnology.net/index.php/rlt/article/view/19198/pdf_1
dc.relation	https://doaj.org/toc/2156-7069
dc.relation	https://doaj.org/toc/2156-7077
dc.rights	CC BY
dc.source	Research in Learning Technology, Vol 20, Iss 0, Pp 1-7 (2012)
dc.subject	e-assessment
dc.subject	ontology
dc.subject	analogy questions
dc.subject	relational similarity
dc.subject	vector space model
dc.subject	corpus-based evaluation
dc.subject	Education (General)
dc.subject	L7-991
dc.subject	Education
dc.subject	L
dc.subject	DOAJ:Education
dc.subject	DOAJ:Social Sciences
dc.subject	Education (General)
dc.subject	L7-991
dc.subject	Education
dc.subject	L
dc.subject	DOAJ:Education
dc.subject	DOAJ:Social Sciences
dc.subject	Education (General)
dc.subject	L7-991
dc.subject	Education
dc.subject	L
dc.subject	Education (General)
dc.subject	L7-991
dc.subject	Education
dc.subject	L
dc.subject	Education (General)
dc.subject	L7-991
dc.subject	Education
dc.subject	L
dc.title	Automatic generation of analogy questions for student assessment: an Ontology-based approach
dc.type	article