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Showing 1 to 15 of 16 results Save | Export
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Luke Strickland; Simon Farrell; Micah K. Wilson; Jack Hutchinson; Shayne Loft – Cognitive Research: Principles and Implications, 2024
In a range of settings, human operators make decisions with the assistance of automation, the reliability of which can vary depending upon context. Currently, the processes by which humans track the level of reliability of automation are unclear. In the current study, we test cognitive models of learning that could potentially explain how humans…
Descriptors: Automation, Reliability, Man Machine Systems, Learning Processes
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Smithson, Conor J. R.; Eichbaum, Quentin G.; Gauthier, Isabel – Cognitive Research: Principles and Implications, 2023
We investigated the relationship between category learning and domain-general object recognition ability (o). We assessed this relationship in a radiological context, using a category learning test in which participants judged whether white blood cells were cancerous. In study 1, Bayesian evidence negated a relationship between o and category…
Descriptors: Recognition (Psychology), Classification, Learning Processes, Medicine
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Raat, E. M.; Kyle-Davidson, C.; Evans, K. K. – Cognitive Research: Principles and Implications, 2023
Extraction of global structural regularities provides general 'gist' of our everyday visual environment as it does the gist of abnormality for medical experts reviewing medical images. We investigated whether naïve observers could learn this gist of medical abnormality. Fifteen participants completed nine adaptive training sessions viewing four…
Descriptors: Feedback (Response), Diagnostic Tests, Cancer, Females
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Lloyd, Kevin; Sanborn, Adam; Leslie, David; Lewandowsky, Stephan – Cognitive Science, 2019
Algorithms for approximate Bayesian inference, such as those based on sampling (i.e., Monte Carlo methods), provide a natural source of models of how people may deal with uncertainty with limited cognitive resources. Here, we consider the idea that individual differences in working memory capacity (WMC) may be usefully modeled in terms of the…
Descriptors: Short Term Memory, Bayesian Statistics, Cognitive Ability, Individual Differences
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Lai, Song; Sun, Bo; Wu, Fati; Xiao, Rong – IEEE Transactions on Learning Technologies, 2020
Adaptive e-learning can be used to personalize learning environment for students to meet their individual demands. Individual differences depend on the students' personality traits. Numerous studies have indicated that understanding the role of personality in the learning process can facilitate learning. Hence, personality identification in…
Descriptors: Personality Traits, Electronic Learning, Individual Differences, Learning Processes
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Kovack-Lesh, Kristine A.; Oakes, Lisa M.; McMurray, Bob – Infancy, 2012
We examined how infants' categorization is jointly influenced by previous experience and how much they shift their gaze back and forth between stimuli. Extending previous findings reported by K. A. Kovack-Lesh, J. S. Horst, and L. M. Oakes (2008), we found that 4-month-old infants' (N = 122) learning of the exclusive category of "cats" was related…
Descriptors: Stimuli, Classification, Infants, Attention
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Mayor, Julien; Plunkett, Kim – Psychological Review, 2010
We present a neurocomputational model with self-organizing maps that accounts for the emergence of taxonomic responding and fast mapping in early word learning, as well as a rapid increase in the rate of acquisition of words observed in late infancy. The quality and efficiency of generalization of word-object associations is directly related to…
Descriptors: Generalization, Vocabulary Development, Classification, Language Acquisition
Carnine, Douglas – Phi Delta Kappan, 1990
The doctrine of localized brain functions has strongly influenced many educators. Gerald Edelman's recent research challenges this doctrine by advancing categorization and recategorization as the brain's overriding activities. Instruction that focuses overmuch on similarities is misguided and confusing. Instead, classroom instruction should employ…
Descriptors: Classification, Elementary Education, Individual Differences, Learning Processes
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Blair, Mark; Homa, Don L. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2005
Category learning can be characterized as a process of discovering the dimensions that represent stimuli efficiently and effectively. Categories that are overlapping when represented in 1 dimensionality may be separate in a higher dimensional cue set. The authors report 2 experiments in which participants were shown an additional cue after…
Descriptors: Cues, Classification, Individual Differences, Stimuli
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Heidt, Erhard U. – British Journal of Educational Technology, 1977
The author proposes that Guilford's structure-of-intellect model be used as a starting point for researchers studying the interaction of instructional media attributes with individual differences in cognitive variables. (BD)
Descriptors: Aptitude Treatment Interaction, Classification, Cognitive Style, Educational Media
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Reardon, Richard; And Others – Perceptual and Motor Skills, 1982
Field-dependent and independent subjects sorted geometric and verbal material according to category exemplars, forcing active learning, and then recalled the category locations. Field-independent individuals generally performed better on learning and memory tasks with a more active approach. Active versus passive learning styles are discussed.…
Descriptors: Classification, Cognitive Style, Higher Education, Individual Development
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Levin, Joel R.; And Others – Journal of Educational Psychology, 1974
Descriptors: Classification, Cognitive Style, Elementary School Students, Individual Differences
Kyllonen, Patrick C.; Shute, Valerie J. – 1988
Questions concerning individual differences in learning ability may be more precisely addressed in light of an agreed-upon taxonomy of learning skills. Existing taxonomies are reviewed, and their shortcomings are described. A taxonomy is then proposed based on a synthesis of current thought consisting of four dimensions: the forms of knowledge;…
Descriptors: Aptitude Tests, Classification, Cognitive Processes, Cognitive Style
Worden, Patricia E.; Mandler, George – 1976
Mandler (1969) found that one-third of adult subjects were seriators and two-thirds were categorizers in a task where either strategy could be employed. Study 1 was a replication of his procedure with children from Grades 1, 3, 5, 7, and 9. While there was weak evidence that some older subjects chose the categorial strategy, there was little…
Descriptors: Adult Learning, Classification, Cognitive Development, Cognitive Processes
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Schwebel, Milton – 1975
This paper presents a discussion, based on current research, of what can be done to help children achieve the highest level of cognitive development (Piaget's formal operations). The four factors which Piaget found to be involved in cognitive development are discussed in relation to recent research. These factors include: (1) organic growth and…
Descriptors: Classification, Cognitive Development, Cognitive Processes, Conservation (Concept)
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