Konferensartikel

Generating Multiple Questions From Ontologies: How Far Can We Go?

Tahani Alsubait
School of Computer Science, The University of Manchester, United Kingdom

Bijan Parsia
School of Computer Science, The University of Manchester, United Kingdom

Uli Sattler
School of Computer Science, The University of Manchester, United Kingdom

Ladda ner artikel

Ingår i: Proceedings from the First International Workshop on Educational Knowledge Management (EKM 2014), Linköping, November 24, 2014

Linköping Electronic Conference Proceedings 104:3, s. 19--30

Visa mer +

Publicerad: 2014-11-18

ISBN: 978-91-7519-218-5

ISSN: 1650-3686 (tryckt), 1650-3740 (online)

Abstract

Ontology-based Multiple Choice Question (MCQ) generation has a relatively short history. Many attempts have been carried out to develop methods to generate MCQs from ontologies. However, there is a still a need to understand the applicability of these methods in real educational settings. In this paper, we present an empirical evaluation of ontology-based MCQ generation. We examine the feasibility of applying ontology-based MCQ generation methods by educators with no prior experience in ontology building. The ndings of this study show that this is feasible and can result in generating a reasonable number of educationally useful questions with good predictions about their difficulty levels.

Nyckelord

Inga nyckelord är tillgängliga

Referenser

T. Alsubait, B. Parsia, and U. Sattler. Automatic generation of analogy questions for student assessment: an ontology-based approach. In ALT-C2012 ConferenceProceedings, 2012.

T. Alsubait, B. Parsia, and U. Sattler. Mining ontologies for analogy questions: A similarity-based approach. In OWLED, 2012.

T. Alsubait, B. Parsia, and U. Sattler. Next generation of e-assessment: automatic generation of questions. International Journal of Technology Enhanced Learning, 4(3/4):156–171, 2012.

T. Alsubait, B. Parsia, and U. Sattler. A similarity-based theory of controlling mcq difficulty. In Second International Conferenceon e-Learning and e-Technologies in Education (ICEEE), pages  283–288, 2013.

T. Alsubait, B. Parsia, and U. Sattler. Generating multiple choice questions from ontologies: Lessons learnt.  In The 11th OWL: Experiences and Directions Work-shop (OWLED2014), 2014.

T. Alsubait, B. Parsia, and U. Sattler. Measuring similarity in ontologies: How bad is a cheap measure?  In 27th Inernational Workshop on Description Logics(DL-2014), 2014.

F. Baader, D. Calvanese, D. L. McGuinness, D. Nardi, and P. F. (eds.) Patel-Schneider. The Description Logic Handbook: Theory, Implementation and Applications. Cambridge University Press, second edition,  2007.

B. S. Bloom and D. R. Krathwohl. Taxonomyof educational objectives: The classificationof educational goals by a committee of college and university examiners. Handbook  1. Cognitive domain. New York: Addison-Wesley, 1956.

B. G. Davis. Toolsfor Teaching. San Francisco, CA: Jossey-Bass, 2001.

T. Gavrilova, R. Farzan, and P. Brusilovsky. One practical algorithm of creating teaching ontologies. In 12th International Network-Based Education ConferenceNBE, pages 29–37, 2005.

T. M. Haladyna. Developing and validating multiple-choice test items. Hillsdale:LawrenceErlbaum, 1994.

T.M. Haladyna and S.M. Downing. How many options is enough for a multiple choice test item? Educational& Psychological Measurement, 53(4):999–1010, 1993.

M.    Horridge. A practical guide to building OWL ontologies using Prot´eg´e 4 and CO-ODE tools, edition 1.3. http://owl.cs.manchester.ac.uk/tutorials/protegeowltutorial/ [accessed: 18-04-2014], 2011.

M. Horridge and S. Bechhofer. The  OWL  API:  A  Java  API  for  working  with OWL 2 ontologies. In In Proceedings of the 6th International Workshop on OWL:Experiences and Directions (OWLED), 2009.

M. Miller, R. Linn, and N. Gronlund. Measurementand Assessment in Teaching,TenthEdition. Pearson, 2008.

R. Mitkov, L. An Ha, and N. Karamani. A computer-aided environment for gen- erating multiple-choice test items.cambridge university press. NaturalLanguageEngineering, 12(2):177–194, 2006.

A. Papasalouros, K. Kotis, and K. Kanaris.  Automatic  generation  of  multiple-choice questions from domain ontologies. In IADIS e-Learning 2008 conference, Amsterdam,  2008.

M. Paxton. A linguistic perspective on multiple choice questioning. Assessment &Evaluation in Higher Education, 25(2):109–119, 2001.

L. Rudner. Elements of adaptive testing, chapter Implementing the Graduate Man- agement Admission Test computerized adaptive test, pages 151–165. New York, NY: Springer, 2010.

J. T. Sidick, G. V. Barrett, and D. Doverspike. Three-alternative multiple-choice tests: An attractive option. Personnel Psychology, 47:829–835, 1994.

S. Sosnovsky and T. Gavrilova. Development of educational ontology for C- Programming. In Proceedingsof the XI-th International Conference Knowledge-Dialogue-Solution, vol. 1, pp. 127132. FOI ITHEA, 2006.

D. Tsarkov and I. Horrocks. FaCT++ description logic reasoner: System descrip- tion. In Proceedingsof the 3rd International Joint Conference on Automated Rea-soning (IJCAR), 2006.

S. Williams. Generating mathematical word problems. In 2011 AAAI Fall Sym-posiumSeries, 2011.

B. Zitko, S. Stankov, M. Rosic, and A. Grubisic. Dynamic test generation over ontology-based knowledge representation in authoring shell. Expert Systems with Applications: An International Journal, 36(4):8185–8196, 2008.

Citeringar i Crossref