TY - GEN
T1 - SeMCQ – Protégé Plugin for Automatic Ontology-Driven Multiple Choice Question Tests Generation
AU - Tosic, M.
AU - Cubric, Marija
N1 - Paper can be found at: http://protege.stanford.edu/conference/2009/poster-session.html Copyright © 2010 Stanford Center for Biomedical Informatics Research
PY - 2009
Y1 - 2009
N2 - Creating fair and meaningful assessment strategy is one the most difficult areas for every educator. Objective (MCQ) testing has been extensively studied and evaluated as a method for formative and, to a lesser extent, summative assessment. While the objective tests need to be complemented by other assessment strategies in order to assess higher cognitive domains, they nonetheless provide important benefits that are directly addressing the student needs such as, providing prompt and frequent feedback (2008 UK National Students Survey [8]). Moreover, in its more advanced forms, such as Computer-Adaptive Testing, objective tests can “get closer to measuring skills and intelligence” [3]. However, creating a useful objective test is not only difficult but also very time-consuming, which prevents its more wide-spread adoption and use [1]. In this paper we are trying to address this problem, by providing a framework and a prototype of a Semantic Multiple Choice Questions (SeMCQ) generator for an arbitrary knowledge domain. The prototype is implemented as a Protégé plugin. In the following sections we describe the implementation details of the prototype as well as some areas of future work.
AB - Creating fair and meaningful assessment strategy is one the most difficult areas for every educator. Objective (MCQ) testing has been extensively studied and evaluated as a method for formative and, to a lesser extent, summative assessment. While the objective tests need to be complemented by other assessment strategies in order to assess higher cognitive domains, they nonetheless provide important benefits that are directly addressing the student needs such as, providing prompt and frequent feedback (2008 UK National Students Survey [8]). Moreover, in its more advanced forms, such as Computer-Adaptive Testing, objective tests can “get closer to measuring skills and intelligence” [3]. However, creating a useful objective test is not only difficult but also very time-consuming, which prevents its more wide-spread adoption and use [1]. In this paper we are trying to address this problem, by providing a framework and a prototype of a Semantic Multiple Choice Questions (SeMCQ) generator for an arbitrary knowledge domain. The prototype is implemented as a Protégé plugin. In the following sections we describe the implementation details of the prototype as well as some areas of future work.
M3 - Conference contribution
VL - 2009
BT - Procs of the 11th International Protege Conference
PB - Stanford Center for Biomedical Informatics Research
ER -