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Austerweil, Joseph L.; Sanborn, Sophia; Griffiths, Thomas L. – Cognitive Science, 2019
Generalization is a fundamental problem solved by every cognitive system in essentially every domain. Although it is known that how people generalize varies in complex ways depending on the context or domain, it is an open question how people "learn" the appropriate way to generalize for a new context. To understand this capability, we…
Descriptors: Generalization, Logical Thinking, Inferences, Bayesian Statistics
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How, Meng-Leong; Hung, Wei Loong David – Education Sciences, 2019
Artificial intelligence-enabled adaptive learning systems (AI-ALS) are increasingly being deployed in education to enhance the learning needs of students. However, educational stakeholders are required by policy-makers to conduct an independent evaluation of the AI-ALS using a small sample size in a pilot study, before that AI-ALS can be approved…
Descriptors: Stakeholders, Artificial Intelligence, Bayesian Statistics, Probability
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Gardner, Josh; Brooks, Christopher – Journal of Learning Analytics, 2018
Model evaluation -- the process of making inferences about the performance of predictive models -- is a critical component of predictive modelling research in learning analytics. We survey the state of the practice with respect to model evaluation in learning analytics, which overwhelmingly uses only naïve methods for model evaluation or…
Descriptors: Prediction, Models, Evaluation, Evaluation Methods
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Bhatia, Jaydeep-Singh; Oaksford, Mike – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2015
When directed to ignore evidence of a witness's previous bad character because of a violation of the rules of evidence, are jurors' beliefs still affected? The intuition is that they will be because in everyday argumentation, fallacies, like the ad hominem, are effective argumentative strategies. An ad hominem argument (against the person)…
Descriptors: Persuasive Discourse, Logical Thinking, Court Litigation, Bayesian Statistics
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Hilbig, Benjamin E.; Erdfelder, Edgar; Pohl, Rudiger F. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2011
A new process model of the interplay between memory and judgment processes was recently suggested, assuming that retrieval fluency--that is, the speed with which objects are recognized--will determine inferences concerning such objects in a single-cue fashion. This aspect of the fluency heuristic, an extension of the recognition heuristic, has…
Descriptors: Stimuli, Heuristics, Memory, Goodness of Fit
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Lecoutre, Bruno; Charron, Camilo – Journal of Educational and Behavioral Statistics, 2000
Illustrates procedures for prediction analysis in 2 X 2 contingency tables through the analyses of solutions of six types of problems associated with the acquisition of fractions. Reviews and extends confidence interval procedures previously proposed for an index of predictive efficiency of implication hypotheses. Compares frequentist coverage…
Descriptors: Bayesian Statistics, Hypothesis Testing, Prediction, Probability
Felipe, Abraham I. – International Education Journal, 2006
The present study tested the assumption of a positive and linear relation between years of schooling and school learning in the Philippine setting. It replicated a 1976 study that had cast doubt on this assumption in the Philippine public educational system. It tested three competing hypotheses for that finding: common sense, the 1976 arrested…
Descriptors: Grade 6, Grade 5, Grade 4, Educational Attainment
Shields, W. S. – 1974
A procedure for predicting categorical outcomes using categorical predictor variables was described by Moonan. This paper describes a related technique which uses prior probabilities, updated by joint likelihoods, as classification criteria. The procedure differs from Moonan's in that the outcome having the greatest posterior probability is…
Descriptors: Bayesian Statistics, Behavioral Science Research, Classification, Higher Education
Barnes, Tiffany, Ed.; Desmarais, Michel, Ed.; Romero, Cristobal, Ed.; Ventura, Sebastian, Ed. – International Working Group on Educational Data Mining, 2009
The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…
Descriptors: Data Analysis, Educational Research, Conferences (Gatherings), Foreign Countries