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Desmarais, Michel C.; Xu, Peng; Beheshti, Behzad – International Educational Data Mining Society, 2015
The problem of mapping items to skills is gaining interest with the emergence of recent techniques that can use data for both defining this mapping, and for refining mappings given by experts. We investigate the problem of refining mapping from an expert by combining the output of different techniques. The combination is based on a partition tree…
Descriptors: Matrices, Test Items, Skills, Expertise
Beheshti, Behzad; Desmarais, Michel C. – International Educational Data Mining Society, 2015
This study investigates the issue of the goodness of fit of different skills assessment models using both synthetic and real data. Synthetic data is generated from the different skills assessment models. The results show wide differences of performances between the skills assessment models over synthetic data sets. The set of relative performances…
Descriptors: Goodness of Fit, Student Evaluation, Skills, Models
Beheshti, Behzad; Desmarais, Michel C.; Naceur, Rhouma – International Educational Data Mining Society, 2012
Identifying the skills that determine the success or failure to exercises and question items is a difficult task. Multiple skills may be involved at various degree of importance, and skills may overlap and correlate. In an effort towards the goal of finding the skills behind a set of items, we investigate two techniques to determine the number of…
Descriptors: Prediction, Evaluation, Algebra, Mathematics