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Hauser, Carl; Thum, Yeow Meng; He, Wei; Ma, Lingling – Educational and Psychological Measurement, 2015
When conducting item reviews, analysts evaluate an array of statistical and graphical information to assess the fit of a field test (FT) item to an item response theory model. The process can be tedious, particularly when the number of human reviews (HR) to be completed is large. Furthermore, such a process leads to decisions that are susceptible…
Descriptors: Test Items, Item Response Theory, Research Methodology, Decision Making
Lamb, Richard L. – ProQuest LLC, 2013
Serious Educational Games (SEGs) have been a topic of increased popularity within the educational realm since the early millennia. SEGs are generalized form of Serious Games to mean games for purposes other than entertainment but, that also specifically include training, educational purpose and pedagogy within their design. This rise in popularity…
Descriptors: Educational Games, Models, Artificial Intelligence, Neurological Organization
Ferrando, Pere J.; Lorenzo-Seva, Urbano – Psychological Methods, 2005
This article describes a general item response theory-based factor analytic procedure that allows assessment of the equivalence between 2 administrative modes of a questionnaire: paper and pencil, and Internet based. The theoretical relations between the present procedure and other methods used in previous empirical research are shown, and the…
Descriptors: Factor Analysis, Item Response Theory, Comparative Analysis, Computer Assisted Testing
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection

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