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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
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Golubickis, Marius; Falben, Johanna K.; Cunningham, William A.; Macrae, C. Neil – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2018
Although ownership is acknowledged to exert a potent influence on various aspects of information processing, the origin of these effects remains largely unknown. Based on the demonstration that self-relevance facilitates perceptual judgments (i.e., the self-prioritization effect), here we explored the possibility that ownership enhances object…
Descriptors: Ownership, Self Concept, Stimuli, Responses
Feng, Junchen – ProQuest LLC, 2017
The future of education is human expertise and artificial intelligence working in conjunction, a revolution that will change the education as we know it. The Intelligent Tutoring System is a key component of this future. A quantitative measurement of efficacies of practice to heterogeneous learners is the cornerstone of building an effective…
Descriptors: Intelligent Tutoring Systems, Learning Processes, Bayesian Statistics, Models
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Rouder, Jeffrey N.; Yue, Yu; Speckman, Paul L.; Pratte, Michael S.; Province, Jordan M. – Psychological Review, 2010
A dominant theme in modeling human perceptual judgments is that sensory neural activity is summed or integrated until a critical bound is reached. Such models predict that, in general, the shape of response time distributions change across conditions, although in practice, this shape change may be subtle. An alternative view is that response time…
Descriptors: Reaction Time, Decision Making, Models, Statistical Analysis
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Ansari, Asim; Iyengar, Raghuram – Psychometrika, 2006
We develop semiparametric Bayesian Thurstonian models for analyzing repeated choice decisions involving multinomial, multivariate binary or multivariate ordinal data. Our modeling framework has multiple components that together yield considerable flexibility in modeling preference utilities, cross-sectional heterogeneity and parameter-driven…
Descriptors: Markov Processes, Monte Carlo Methods, Computation, Bayesian Statistics
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Almond, Russell G. – ETS Research Report Series, 2007
Over the course of instruction, instructors generally collect a great deal of information about each student. Integrating that information intelligently requires models for how a student's proficiency changes over time. Armed with such models, instructors can "filter" the data--more accurately estimate the student's current proficiency…
Descriptors: Markov Processes, Decision Making, Student Evaluation, Learning Processes