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Panyajamorn, Titie; Suanmali, Suthathip; Kohda, Youji; Chongphaisal, Pornpimol; Supnithi, Thepchai – Malaysian Journal of Learning and Instruction, 2018
Purpose: This study proposed and examined the effectiveness of e-learning content design by considering two different subjects (mathematics and reading) and areas (metropolitan and rural). This study also investigated several variables, i.e., students' satisfaction, motivation, and experience, that influenced learning abilities. Moreover, we…
Descriptors: Electronic Learning, Technology Uses in Education, Reading Instruction, Mathematics Instruction
Rutkowski, Leslie – Applied Measurement in Education, 2014
Large-scale assessment programs such as the National Assessment of Educational Progress (NAEP), Trends in International Mathematics and Science Study (TIMSS), and Programme for International Student Assessment (PISA) use a sophisticated assessment administration design called matrix sampling that minimizes the testing burden on individual…
Descriptors: Measurement, Testing, Item Sampling, Computation
Verhelst, Norman D. – Scandinavian Journal of Educational Research, 2012
When using IRT models in Educational Achievement Testing, the model is as a rule too simple to catch all the relevant dimensions in the test. It is argued that a simple model may nevertheless be useful but that it can be complemented with additional analyses. Such an analysis, called profile analysis, is proposed and applied to the reading data of…
Descriptors: Multidimensional Scaling, Profiles, Item Response Theory, Achievement Tests
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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