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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
Yu-Chin, Chiu – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2023
Recent context-control learning studies have shown that switch costs are reduced in a particular context predicting a high probability of switching as compared to another context predicting a low probability of switching. These context-specific switch probability effects suggest that control of task sets, through experience, can become associated…
Descriptors: Learning Processes, Prior Learning, Task Analysis, Cognitive Ability
Vogel, Tobias; Carr, Evan W.; Davis, Tyler; Winkielman, Piotr – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2018
Stimuli that capture the central tendency of presented exemplars are often preferred--a phenomenon also known as the classic beauty-in-averageness effect. However, recent studies have shown that this effect can reverse under certain conditions. We propose that a key variable for such ugliness-in-averageness effects is the category structure of the…
Descriptors: Interpersonal Attraction, Preferences, Stimuli, Experiments
Ashby, F. Gregory; Vucovich, Lauren E. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2016
Feedback is highly contingent on behavior if it eventually becomes easy to predict, and weakly contingent on behavior if it remains difficult or impossible to predict even after learning is complete. Many studies have demonstrated that humans and nonhuman animals are highly sensitive to feedback contingency, but no known studies have examined how…
Descriptors: Feedback (Response), Classification, Learning Processes, Associative Learning
Rutstein, Daisy Wise – ProQuest LLC, 2012
This research examines issues regarding model estimation and robustness in the use of Bayesian Inference Networks (BINs) for measuring Learning Progressions (LPs). It provides background information on LPs and how they might be used in practice. Two simulation studies are performed, along with real data examples. The first study examines the case…
Descriptors: Bayesian Statistics, Learning Processes, Robustness (Statistics), Statistical Inference
Lukács, Ágnes; Kemény, Ferenc – Cognitive Science, 2015
The acquisition of complex motor, cognitive, and social skills, like playing a musical instrument or mastering sports or a language, is generally associated with implicit skill learning (SL). Although it is a general view that SL is most effective in childhood, and such skills are best acquired if learning starts early, this idea has rarely been…
Descriptors: Skill Development, Psychomotor Skills, Cognitive Development, Interpersonal Competence
Özcan, Özgür – Eurasian Journal of Educational Research, 2013
Problem Statement: Difficulties in the learning process usually emerge from the problem of mental representations constructed by students in their interactions with the world. This previous knowledge and these ideas are in contradiction with scientific facts, and are known as misconceptions or alternative ideas. Thus, an analysis of the mental…
Descriptors: Schemata (Cognition), Physics, Science Instruction, Preservice Teachers
Rehder, Bob; Kim, ShinWoo – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2010
Research has documented two effects of interfeature causal knowledge on classification. A "causal status effect" occurs when features that are causes are more important to category membership than their effects. A "coherence effect" occurs when combinations of features that are consistent with causal laws provide additional…
Descriptors: Classification, Probability, Experiments, Experimental Psychology
Guo, Zhen – ProQuest LLC, 2010
A basic and classical assumption in the machine learning research area is "randomness assumption" (also known as i.i.d assumption), which states that data are assumed to be independent and identically generated by some known or unknown distribution. This assumption, which is the foundation of most existing approaches in the literature, simplifies…
Descriptors: Artificial Intelligence, Man Machine Systems, Probability, Data
Hoffman, Aaron B.; Murphy, Gregory L. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2006
Three experiments compared the learning of lower-dimensional family resemblance categories (4 dimensions) with the learning of higher-dimensional ones (8 dimensions). Category-learning models incorporating error-driven learning, hypothesis testing, or limited capacity attention predict that additional dimensions should either increase learning…
Descriptors: Experiments, Classical Conditioning, Probability, Comparative Analysis
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers