Literature DB >> 23516801

The effect of Gestalt laws of perceptual organization on the comprehension of three-variable bar and line graphs.

Nadia Ali1, David Peebles.   

Abstract

OBJECTIVE: We report three experiments investigating the ability of undergraduate college students to comprehend 2 x 2 "interaction" graphs from two-way factorial research designs.
BACKGROUND: Factorial research designs are an invaluable research tool widely used in all branches of the natural and social sciences, and the teaching of such designs lies at the core of many college curricula. Such data can be represented in bar or line graph form. Previous studies have shown, however, that people interpret these two graphical forms differently.
METHOD: In Experiment 1, participants were required to interpret interaction data in either bar or line graphs while thinking aloud. Verbal protocol analysis revealed that line graph users were significantly more likely to misinterpret the data or fail to interpret the graph altogether.
RESULTS: The patterns of errors line graph users made were interpreted as arising from the operation of Gestalt principles of perceptual organization, and this interpretation was used to develop two modified versions of the line graph, which were then tested in two further experiments. One of the modifications resulted in a significant improvement in performance.
CONCLUSION: Results of the three experiments support the proposed explanation and demonstrate the effects (both positive and negative) of Gestalt principles of perceptual organization on graph comprehension. APPLICATION: We propose that our new design provides a more balanced representation of the data than the standard line graph for nonexpert users to comprehend the full range of relationships in two-way factorial research designs and may therefore be considered a more appropriate representation for use in educational and other nonexpert contexts.

Entities:  

Mesh:

Year:  2013        PMID: 23516801     DOI: 10.1177/0018720812452592

Source DB:  PubMed          Journal:  Hum Factors        ISSN: 0018-7208            Impact factor:   2.888


  4 in total

1.  Clinical gestalt and the prediction of massive transfusion after trauma.

Authors:  Matthew J Pommerening; Michael D Goodman; John B Holcomb; Charles E Wade; Erin E Fox; Deborah J Del Junco; Karen J Brasel; Eileen M Bulger; Mitch J Cohen; Louis H Alarcon; Martin A Schreiber; John G Myers; Herb A Phelan; Peter Muskat; Mohammad Rahbar; Bryan A Cotton
Journal:  Injury       Date:  2015-02-04       Impact factor: 2.586

2.  Comparing the Efficacy of Static and Dynamic Graph Types in Communicating Complex Statistical Relationships.

Authors:  Jeffrey Chase Hood; Cade Graber; Gary L Brase
Journal:  Front Psychol       Date:  2020-01-17

3.  Best Graph Type to Compare Discrete Groups: Bar, Dot, and Tally.

Authors:  Fang Zhao; Robert Gaschler
Journal:  Front Psychol       Date:  2021-12-24

4.  Expert interpretation of bar and line graphs: the role of graphicacy in reducing the effect of graph format.

Authors:  David Peebles; Nadia Ali
Journal:  Front Psychol       Date:  2015-10-30
  4 in total

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