Ontology-Based Multiple Choice Question Generation

Multiple choice questions (MCQs) are considered highly useful (being easy to take or mark) but quite difficult to create and large numbers are needed to form valid exams and associated practice materials. The idea of re-using an existing ontology to generate MCQs almost suggests itself and has been explored in various projects. In this project, we are applying suitable educational theory regarding assessments and related methods for their evaluation to ontology-based MCQ generation. In particular, we investigate whether we can measure the similarity of the concepts in an ontology with sufficient reliability so that this measure can be used to control the difficulty of the MCQs generated. In this report, we provide an overview of the background to this research, and describe the main steps taken and insights gained.

[1]  R. L. Ebel,et al.  Procedures for the Analysis of Classroom Tests , 1954 .

[2]  Diego Calvanese,et al.  The Description Logic Handbook: Theory, Implementation, and Applications , 2003, Description Logic Handbook.

[3]  Steffen Staab,et al.  On the Influence of Description Logics Ontologies on Conceptual Similarity , 2008, EKAW.

[4]  Boontawee Suntisrivaraporn,et al.  On Desirable Properties of the Structural Subsumption-Based Similarity Measure , 2014, JIST.

[5]  Maha Al-Yahya,et al.  Ontology-Based Multiple Choice Question Generation , 2014, TheScientificWorldJournal.

[6]  Andreas Papasalouros,et al.  Automatic Generation Of Multiple Choice Questions From Domain Ontologies , 2008, e-Learning.

[7]  B. Davis Tools for Teaching , 1993 .

[8]  Claus Pahl,et al.  Adaptive E-learning content generation based on semantic web technology , 2005 .

[9]  Sandra Williams,et al.  Generating Mathematical Word Problems , 2011, AAAI Fall Symposium: Question Generation.

[10]  Slavomir Stankov,et al.  Dynamic test generation over ontology-based knowledge representation in authoring shell , 2009, Expert Syst. Appl..

[11]  P. Sreenivasa Kumar,et al.  A novel approach to generate MCQs from domain ontology , 2015 .

[12]  Bijan Parsia,et al.  Measuring similarity in ontologies: a new family of measures , 2014, SEMWEB.

[13]  Diego Calvanese,et al.  The Description Logic Handbook , 2007 .

[14]  Le An Ha,et al.  A computer-aided environment for generating multiple-choice test items , 2006, Natural Language Engineering.

[15]  Joseph Lowman,et al.  Mastering the Techniques of Teaching , 1984 .

[16]  Benjamin S. Bloom,et al.  Taxonomy of Educational Objectives: The Classification of Educational Goals. , 1957 .

[17]  Marija Cubric,et al.  Towards automatic generation of e-assessment using semantic web technologies , 2011 .

[18]  Andreas Papasalouros,et al.  Automated Transformation of SWRL Rules into Multiple-Choice Questions , 2011, FLAIRS.

[19]  Anni-Yasmin Turhan,et al.  A Framework for Semantic-based Similarity Measures for ELH-Concepts , 2012 .