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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
Solomon, Benjamin G.; Forsberg, Ole J. – School Psychology Quarterly, 2017
Bayesian techniques have become increasingly present in the social sciences, fueled by advances in computer speed and the development of user-friendly software. In this paper, we forward the use of Bayesian Asymmetric Regression (BAR) to monitor intervention responsiveness when using Curriculum-Based Measurement (CBM) to assess oral reading…
Descriptors: Bayesian Statistics, Regression (Statistics), Least Squares Statistics, Evaluation Methods
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
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

Thornton, Gayle D.; And Others – Planning and Changing, 1975
Focuses on three management tools--the Delphi technique, Bayesian statistics, and Monte Carlo simulation--in order to simulate a problem-solving/decision-making situation with which an educational administrator may be faced. (Author)
Descriptors: Bayesian Statistics, Decision Making, Educational Administration, Elementary Secondary Education

McKenzie, Craig R. M. – Cognitive Psychology, 1994
Through Monte Carlo simulation, respective normative and intuitive strategies for covariation assessment and Bayesian inference are compared. Results indicate that better performance in both tasks results from considering alternative hypotheses, although not necessarily using a normative strategy. Conditions under which intuitive strategies may be…
Descriptors: Analysis of Covariance, Bayesian Statistics, Comparative Analysis, Decision Making