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Peer reviewed
Direct linkAnglim, Jeromy; Wynton, Sarah K. A. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2015
The current study used Bayesian hierarchical methods to challenge and extend previous work on subtask learning consistency. A general model of individual-level subtask learning was proposed focusing on power and exponential functions with constraints to test for inconsistency. To study subtask learning, we developed a novel computer-based booking…
Descriptors: Bayesian Statistics, Hierarchical Linear Modeling, Learning, Statistical Analysis
Lee, Michael D.; Paradowski, Michael J. – Journal of Problem Solving, 2007
We consider group decision-making on an optimal stopping problem, for which large and stable individual differences have previously been established. In the problem, people are presented with a sequence of five random numbers between 0 and 100, one at a time, and are required to choose the maximum of the sequence, without being allowed to return…
Descriptors: Participative Decision Making, Problem Solving, Individual Differences, Comparative Analysis
