Title :
Complexity-based generation of multi-choice tests in AQG systems
Author :
Kovacs, Levente ; Szeman, Gabor
Author_Institution :
Dept. of Inf. Technol., Univ. of Miskolc, Miskolc, Hungary
Abstract :
This paper presents a novel method to measure the difficulty of decisions in multi-choice test questions. The concepts are presented with characteristic fuzzy functions and the entropy-based distance of the membership functions will be used to carry the difficulty level. The presented method is tested in a test automated question generation (AQG) framework.
Keywords :
computer aided instruction; entropy; fuzzy set theory; AQG systems; characteristic fuzzy functions; complexity-based generation; entropy-based distance; membership functions; multi-choice tests questions; test automated question generation framework; Concrete; Context; Entropy; Fuzzy sets; Ontologies; Semantics; Uncertainty; AQG; conceptual graph; distance; entropy; fuzzy sets;
Conference_Titel :
Cognitive Infocommunications (CogInfoCom), 2013 IEEE 4th International Conference on
Conference_Location :
Budapest
Print_ISBN :
978-1-4799-1543-9
DOI :
10.1109/CogInfoCom.2013.6719278
