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Articles 1 - 4 of 4
Full-Text Articles in Psychology
Mindscapes And Landscapes: Hayek And Simon On Cognitive Extension, Leslie Marsh
Mindscapes And Landscapes: Hayek And Simon On Cognitive Extension, Leslie Marsh
Leslie Marsh
Hayek’s and Simon’s social externalism runs on a shared presupposition: mind is constrained in its computational capacity to detect, harvest, and assimilate “data” generated by the infinitely fine-grained and perpetually dynamic characteristic of experience in complex social environments. For Hayek, mind and sociality are co-evolved spontaneous orders, allowing little or no prospect of comprehensive explanation, trapped in a hermeneutically sealed, i.e. inescapably context bound, eco-system. For Simon, it is the simplicity of mind that is the bottleneck, overwhelmed by the ambient complexity of the environmental. Since on Simon’s account complexity is unidirectional, Simon is far more ebullient about the prospects …
Statistical Methods Used In Gifted Education Journals, 2006-2010, Russell Warne, Maria Lazo, Tami Ramos, Nicola Ritter
Statistical Methods Used In Gifted Education Journals, 2006-2010, Russell Warne, Maria Lazo, Tami Ramos, Nicola Ritter
Russell T Warne
This article describes the statistical methods used in quantitative and mixed methods articles between 2006 and 2010 in five gifted education research journals. Results indicate that the most commonly used statistical methods are means (85.9% of articles), standard deviations (77.8%), Pearson’s r (47.8%), χ2 (32.2%), ANOVA (30.7%), t tests (30.0%), and MANOVA (23.0%). Approximately half (53.3%) of the articles included reliability reports for the data at hand; Cronbach’s alpha was the most commonly reported measure of reliability (41.5%). Some discussions of best statistical practice and implications for the field of gifted education are included.
Managing Clustered Data Using Hierarchical Linear Modeling, Russell Warne
Managing Clustered Data Using Hierarchical Linear Modeling, Russell Warne
Russell T Warne
Researchers in nutrition research often use cluster or multistage sampling to gather participants for their studies. These sampling methods often produce violations of the assumption of data independence that most traditional statistics share. Hierarchical linear modeling is a statistical method that can overcome violations of the independence assumption and lead to correct analysis of data, yet it is rarely used in nutrition research. The purpose of this viewpoint is to illustrate the benefits of hierarchical linear modeling within a nutrition research context.
Stigmergy 3.0: From Ants To Economies, Leslie Marsh, Margery Doyle
Stigmergy 3.0: From Ants To Economies, Leslie Marsh, Margery Doyle
Leslie Marsh
No abstract provided.