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.
Item Response Theory for Optimal Questionnaire Design
PIRLO, Giuseppe
2013-01-01
Abstract
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.File in questo prodotto:
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