Ontology-Based Multiple Choice Question Generation
Author
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-03-26
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
With recent advancements in Semantic Web technologies, a new trend in MCQ item generation has emerged through the use of ontologies.
Ontologies are knowledge representation structures that formally describe entities in a domain and their relationships, thus enabling automated inference and reasoning.
Ontology-based MCQ item generation is still in its infancy, but substantial research efforts are being made in the field.
However, the applicability of these models for use in an educational setting has not been thoroughly evaluated.
In this paper, we present an experimental evaluation of an ontology-based MCQ item generation system known as OntoQue.
The evaluation was conducted using two different domain ontologies.
The findings of this study show that ontology-based MCQ generation systems produce satisfactory MCQ items to a certain extent.
However, the evaluation also revealed a number of shortcomings with current ontology-based MCQ item generation systems with regard to the educational significance of an automatically constructed MCQ item, the knowledge level it addresses, and its language structure.
Furthermore, for the task to be successful in producing high-quality MCQ items for learning assessments, this study suggests a novel, holistic view that incorporates learning content, learning objectives, lexical knowledge, and scenarios into a single cohesive framework.
American Psychological Association (APA)
Al-Yahya, Maha. 2014. Ontology-Based Multiple Choice Question Generation. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1049022
Modern Language Association (MLA)
Al-Yahya, Maha. Ontology-Based Multiple Choice Question Generation. The Scientific World Journal No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-1049022
American Medical Association (AMA)
Al-Yahya, Maha. Ontology-Based Multiple Choice Question Generation. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1049022
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1049022