Item Response Theory for Optimal Questionnaire Design

Giuseppina Lotito, Giuseppe Pirlo


Student assessment is one of the most critical aspects related to web-based learning systems. In this field, the use of on-line questionnaires - based on multiple-choice items - is one of the most widespread approaches.
This paper presents a new technique for automatic design of optimal questionnaires that uses a Genetic Algorithm for multiple-choice item selection, according to the Item Response Theory.
The experimental results, carried out on both simulated and genuine data, confirm the effectiveness of the new approach, that is able to adapt questionnaire design to the abilities of a given set of students.


Web-based Education, Learning Assessment, e-Learning, Item Response Theory, Genetic Algorithm

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Journal of e-Learning and Knowledge Society | ISSN (online) 1971 - 8829 | ISSN (paper) 1826 - 6223 © 2017 Je-LKS - Italian e-Learning Association (SIe-L).