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Villanueva Manjarres, Andrés; Moreno Sandoval, Luis Gabriel; Salinas Suárez, Martha Janneth – Digital Education Review, 2018
Educational Data Mining is an emerging discipline which seeks to develop methods to explore large amounts of data from educational settings, in order to understand students' behavior, interests and results in a better way. In recent years there have been various works related to this specialty and multiple data mining techniques derived from this…
Descriptors: Information Retrieval, Data Analysis, Educational Environment, Research Methodology
Fu, Jianbin; Zapata, Diego; Mavronikolas, Elia – ETS Research Report Series, 2014
Simulation or game-based assessments produce outcome data and process data. In this article, some statistical models that can potentially be used to analyze data from simulation or game-based assessments are introduced. Specifically, cognitive diagnostic models that can be used to estimate latent skills from outcome data so as to scale these…
Descriptors: Simulation, Evaluation Methods, Games, Data Collection
Levy, Roy – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2014
Digital games offer an appealing environment for assessing student proficiencies, including skills and misconceptions in a diagnostic setting. This paper proposes a dynamic Bayesian network modeling approach for observations of student performance from an educational video game. A Bayesian approach to model construction, calibration, and use in…
Descriptors: Video Games, Educational Games, Bayesian Statistics, Observation