We present a generalisation of the IRT framework that allows to discriminate between examinees. Our model therefore introduces examinee parameters that can be optimised with Expectation Maximisation-like algorithms. We provide empirical results on PISA data showing that our approach leads to a more appropriate grouping of PISA countries than by test scores and socio-economic indicators.

An accurately calibrated item bank is essential for a valid computerized adaptive test. However, in some settings, such as occupational testing, there is limited access to examinees for calibration. As a result of the limited access to possible examinees, collecting data to accurately calibrate an item bank in an occupational setting is usually difficult. In such a setting, the item bank can be...

Time on task is an important predictor for how much students learn. However, students must be focused on their learning for the time invested to be productive. Unfortunately, students do not always try their hardest to solve problems presented by computer tutors. This paper explores student disengagement and proposes an approach, engagement tracing, for detecting whether a student is engaged in...

We may not be able to make you love reading, but explanatory item response models a generalized linear and nonlinear approach will lead you to love reading starting from now. Book is the window to open the new world. The world that you want is in the better stage and level. World will always guide you to even the prestige stage of the life. You know, this is some of how reading will give you th...

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In multidimensional item response theory, it is possible for the estimate of a subject’s ability in some dimension to decrease after they have answered a question correctly. When this occurs, the fairness of the estimate may be called into question. This paper investigates how and when this form of non-monotonicity occurs. We demonstrate that many response models and statistical estimates can p...

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In this paper a new technique is presented for automatic design of optimal questionnaires. The technique, that is based on the Item Response Theory, performs multiple-choice item selection by a Genetic Algorithm. The experimental results demonstrate the validity of the proposed approach to adjust the characteristics of the questionnaire to the abilities of the student class.

Multiple choice questions (MCQs) that can be generated from a domain ontology can significantly reduce human effort & time required for authoring & administering assessments in an e-Learning environment. Even though there are various methods for generating MCQs from ontologies, methods for determining the difficulty-levels of such MCQs are less explored. In this paper, we study various aspects ...