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Lee, Hee Seung; Betts, Shawn; Anderson, John R. – Journal of Experimental Education, 2017
Appreciation of problem structure is critical to successful learning. Two experiments investigated effective ways of communicating problem structure in a computer-based learning environment and tested whether verbal instruction is necessary to specify solution steps, when deep structure is already embellished by instructional examples.…
Descriptors: Computer Assisted Instruction, Teaching Methods, Verbal Communication, Problem Solving
Lee, Hee Seung; Fincham, Jon M.; Anderson, John R. – Mind, Brain, and Education, 2015
This event-related fMRI study investigated the differences between learning from examples and learning from verbal directions in mathematical problem solving and how these instruction types affect the activity of relevant brain regions during instruction and solution periods within problem-solving trials. We identified distinct neural signatures…
Descriptors: Cognitive Processes, Neurological Organization, Brain Hemisphere Functions, Mathematics Skills
Lee, Hee Seung; Betts, Shawn; Anderson, John R. – Cognitive Science, 2016
Learning to solve a class of problems can be characterized as a search through a space of hypotheses about the rules for solving these problems. A series of four experiments studied how different learning conditions affected the search among hypotheses about the solution rule for a simple computational problem. Experiment 1 showed that a problem…
Descriptors: Problem Solving, Hypothesis Testing, Experiments, Cognitive Processes
Tenison, Caitlin; Anderson, John R. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2016
A focus of early mathematics education is to build fluency through practice. Several models of skill acquisition have sought to explain the increase in fluency because of practice by modeling both the learning mechanisms driving this speedup and the changes in cognitive processes involved in executing the skill (such as transitioning from…
Descriptors: Skill Development, Mathematics Skills, Learning Processes, Markov Processes
Anderson, John R.; Fincham, Jon M. – Cognitive Science, 2014
Multi-voxel pattern recognition techniques combined with Hidden Markov models can be used to discover the mental states that people go through in performing a task. The combined method identifies both the mental states and how their durations vary with experimental conditions. We apply this method to a task where participants solve novel…
Descriptors: Cognitive Structures, Pattern Recognition, Markov Processes, Cognitive Processes
Anderson, John R. – Neuropsychologia, 2012
Multivariate pattern analysis can be combined with Hidden Markov Model algorithms to track the second-by-second thinking as people solve complex problems. Two applications of this methodology are illustrated with a data set taken from children as they interacted with an intelligent tutoring system for algebra. The first "mind reading" application…
Descriptors: Markov Processes, Intelligent Tutoring Systems, Problem Solving, Methods
Lee, Hee Seung; Anderson, Abraham; Betts, Shawn; Anderson, John R. – Online Submission, 2011
Contradictory evidence has been reported on the effects of discovery learning approach and the role of instructional explanations. By manipulating the presence of instruction (verbal explanation) and transparency of problem structures, we investigated how effects of instructional explanations differed depending on the transparency of problem…
Descriptors: Discovery Learning, Direct Instruction, Problem Solving, Learning Theories
Walsh, Matthew M.; Anderson, John R. – Cognitive Psychology, 2009
In two experiments, we studied how people's strategy choices emerge through an initial and then a more considered evaluation of available strategies. The experiments employed a computer-based paradigm where participants solved multiplication problems using mental and calculator solutions. In addition to recording responses and solution times, we…
Descriptors: Change Strategies, Cognitive Processes, Computer Mediated Communication, Models
Anderson, John R.; Carter, Cameron S.; Fincham, Jon M.; Qin, Yulin; Ravizza, Susan M.; Rosenberg-Lee, Miriam – Cognitive Science, 2008
This article investigates the potential of fMRI to test assumptions about different components in models of complex cognitive tasks. If the components of a model can be associated with specific brain regions, one can make predictions for the temporal course of the BOLD response in these regions. An event-locked procedure is described for dealing…
Descriptors: Brain, Cognitive Processes, Diagnostic Tests, Brain Hemisphere Functions
Anderson, John R. – Oxford University Press, 2007
"The question for me is how can the human mind occur in the physical universe. We now know that the world is governed by physics. We now understand the way biology nestles comfortably within that. The issue is how will the mind do that as well."--Allen Newell, December 4, 1991, Carnegie Mellon University. The argument John Anderson gives…
Descriptors: Cognitive Processes, Cognitive Structures, Abstract Reasoning, Problem Solving

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