Automatic Generation of MCQS from Domain Ontology- A Survey
DOI:
https://doi.org/10.26438/ijcse/v6si6.99102Keywords:
Multiple Choice Questions, Distractors, OntologyAbstract
Ontologies are knowledge representation structures, that models domain knowledge by concepts, instances, rolesand their relationships. Assessment systems can exploit this knowledge by using multiple choice Questions (MCQs). Online assessment systems are mainly using MCQs instead of subjective questions for conducting the tests. Using MCQs for assessments has merits as well as demerits. For assessing wide range of knowledge, MCQs are used. It is because they require very less administrative overhead as well as provide instant feedback to test takers. There are several ontology based MCQ generation approaches proposed by many authors. These approaches generates different kinds of questions, in one approach the stem of all generated question remains the same, another one make use of the semantics of the domain, represented in the form of TBox axioms andABox axioms, to frame interesting MCQs. Some other methods differ in generating distractors for the questions. There are approaches which controls the difficulty level of generated MCQs. This paper gives a literature review and comparison of some of the methods for MCQ generation from ontology.
References
[1] F. Baader, D. Calvanese, D. L. McGuinness, D. Nardi, and P. F. (eds.) PatelSchneider. ”The Description Logic Handbook: Theory, Implementation and Applications” , Cambridge University Press, second edition, 2007.
[2] Muhammad Aun Abbas, ” A Unified Approach for Dealing with Ontology Mappings and their Defects” , Universite de Bretagne Sud, 2016.
[3] T. Alsubait, B. Parsia, U. Sattler, ” A similarity-based theory of controlling mcq difficulty” , 2013 Second International Conference on e-Learning and e- Technologies in Education (ICEEE), pp. 283-288, 2013.
[4] A. Papasalouros, K. Kanaris, K. Kotis, ” Automatic Generation of Multiple Choice Questions from Domain Ontologies” , International Association for Development of the Information Society, pp. 427-434, 2008.
[5] M. Cubric, M. Tosic, ” Towards automatic generation of e-assessment using semantic web technologies”, Proceedings of the 2010 International Computer Assisted Assessment Conference, ISSN:2045-9432, Vol.1, 2010.
[6] E. Holohan, M. Melia, D. McMullen, C. Pahl, ” Adaptive e-learning content generation based on semantic web technology” , Proceedings of Workshop on Applications of Semantic Web Technologies for e-Learning, Amsterdam, The Netherlands, pp. 29-36, 2005.
[7] M. Tosic, M. Cubric, ” SeMCQ-protege plugin for automatic ontology-driven multiple choice question tests generation” , Proceedings of the 11th International Protege Conference, 2009.
[8] B. Aitko, S. Stankov,M. Rosi, A. GrubiAi, ” Dynamic test generation over ontology-based knowledge representation in authoring shell” , Syst. Appl. 36(4), pp. 8185-8196, 2009.
[9] Ian Horrocks, Peter F.Patel- Schneider, Frank van Harmelen, ”From SHIQ and RDF to OWL: the making of a Web Ontology Language” , Web Semantics: Science, Services and Agents on the World Wide Web, Vol. 1, Issue.1, pp. 7-26, December 2003.
[10] Vinu E.V., Sreenivasa Kumar P. , ” A novel approach to generate MCQs from domain ontology: Considering DL semantics and open-world assumption” , International journal on Web Semantics: Science, Services and Agents on the World Wide Web, 2015.
[11] Tahani Alsubait, Bijan Parsia, Ulrike Sattler, ” Ontology-Based Multiple Choice Question Generation” , German Journal on Artificial Intelligence,Vol.30, Issue.2, pp. 183-188, June2016.
[12] T. Alsubait, B. Parsia, and U. Sattler, ” Measuring similarity in ontologies: How bad is a cheap measure?” ,27th Inernational Workshop on Description Logics (DL-2014), 2014.
[13] T. Alsubait, B. Parsia, U. Sattler, ” Generating multiple choice questions from ontologies: Lessons learnt” , Proceedings of the 11th International Workshop on OWL: Experiences and Directions, Vol.1265, pp. 73-84, 2014.
[14] M. Al-Yahya, ” OntoQue: a question generation engine for educational assesment based on domain ontologies” , Proceedings of the 11th IEEE International Conference on Advanced Learning Technologies (ICALT ’11), Athens, Ga, USA, pp. 393-395, July 2011.
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