Literature DB >> 25164400

Probably good diagrams for learning: representational epistemic recodification of probability theory.

Peter C-H Cheng1.   

Abstract

The representational epistemic approach to the design of visual displays and notation systems advocates encoding the fundamental conceptual structure of a knowledge domain directly in the structure of a representational system. It is claimed that representations so designed will benefit from greater semantic transparency, which enhances comprehension and ease of learning, and plastic generativity, which makes the meaningful manipulation of the representation easier and less error prone. Epistemic principles for encoding fundamental conceptual structures directly in representational schemes are described. The diagrammatic recodification of probability theory is undertaken to demonstrate how the fundamental conceptual structure of a knowledge domain can be analyzed, how the identified conceptual structure may be encoded in a representational system, and the cognitive benefits that follow. An experiment shows the new probability space diagrams are superior to the conventional approach for learning this conceptually challenging topic.
Copyright © 2009 Cognitive Science Society, Inc.

Keywords:  Diagrams; Learning; Probability; Problem solving; Representation

Mesh:

Year:  2009        PMID: 25164400     DOI: 10.1111/j.1756-8765.2009.01065.x

Source DB:  PubMed          Journal:  Top Cogn Sci        ISSN: 1756-8757


  1 in total

1.  The efficacy of Euler diagrams and linear diagrams for visualizing set cardinality using proportions and numbers.

Authors:  Gem Stapleton; Peter Chapman; Peter Rodgers; Anestis Touloumis; Andrew Blake; Aidan Delaney
Journal:  PLoS One       Date:  2019-03-28       Impact factor: 3.240

  1 in total

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