Literature DB >> 24746954

Discovering the structure of mathematical problem solving.

John R Anderson1, Hee Seung Lee2, Jon M Fincham3.   

Abstract

The goal of this research is to discover the stages of mathematical problem solving, the factors that influence the duration of these stages, and how these stages are related to the learning of a new mathematical competence. Using a combination of multivariate pattern analysis (MVPA) and hidden Markov models (HMM), we found that participants went through 5 major phases in solving a class of problems: A Define Phase where they identified the problem to be solved, an Encode Phase where they encoded the needed information, a Compute Phase where they performed the necessary arithmetic calculations, a Transform Phase where they performed any mathematical transformations, and a Respond Phase where they entered an answer. The Define Phase is characterized by activity in visual attention and default network regions, the Encode Phase by activity in visual regions, the Compute Phase by activity in regions active in mathematical tasks, the Transform Phase by activity in mathematical and response regions, and the Respond phase by activity in motor regions. The duration of the Compute and Transform Phases were the only ones that varied with condition. Two features distinguished the mastery trials on which participants came to understand a new problem type. First, the duration of late phases of the problem solution increased. Second, there was increased activation in the rostrolateral prefrontal cortex (RLPFC) and angular gyrus (AG), regions associated with metacognition. This indicates the importance of reflection to successful learning.
Copyright © 2014 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Hidden Markov model; Mathematical problem solving; Multivariate pattern analysis; fMRI

Mesh:

Year:  2014        PMID: 24746954     DOI: 10.1016/j.neuroimage.2014.04.031

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  8 in total

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Review 3.  Behavioral Studies Using Large-Scale Brain Networks - Methods and Validations.

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4.  The discovery of processing stages: Extension of Sternberg's method.

Authors:  John R Anderson; Qiong Zhang; Jelmer P Borst; Matthew M Walsh
Journal:  Psychol Rev       Date:  2016-04-28       Impact factor: 8.934

5.  Spatiotemporal analysis of event-related fMRI to reveal cognitive states.

Authors:  Jon M Fincham; Hee Seung Lee; John R Anderson
Journal:  Hum Brain Mapp       Date:  2019-11-14       Impact factor: 5.038

6.  A statistical approach for segregating cognitive task stages from multivariate fMRI BOLD time series.

Authors:  Charmaine Demanuele; Florian Bähner; Michael M Plichta; Peter Kirsch; Heike Tost; Andreas Meyer-Lindenberg; Daniel Durstewitz
Journal:  Front Hum Neurosci       Date:  2015-10-07       Impact factor: 3.169

7.  Real World Problem-Solving.

Authors:  Vasanth Sarathy
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8.  Faster learners transfer their knowledge better: Behavioral, mnemonic, and neural mechanisms of individual differences in children's learning.

Authors:  Hyesang Chang; Miriam Rosenberg-Lee; Shaozheng Qin; Vinod Menon
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  8 in total

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