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Implications of Desnoyers' Taxonomy for Standardization of Data Visualization: A Study of Students' Choice and Knowledge

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Purpose: Current research on data visuals focuses on their creation and use; however, there are few attempts at standardizing data visuals to help facilitate better interdisciplinary communication. Can Desnoyers' taxonomy facilitate better interdisciplinary communication in STEM (Science, Technology, Engineering, and Mathematics) fields by helping practitioners choose more efficient data visuals? In addition, would adopting Desnoyers' taxonomy bypass the current discrepancies between academic and journal data visuals?

Methods: To test Desnoyers' taxonomy's impact on efficient use of data visuals, I did an exploratory, pretest/posttest survey of 101 STEM students and their choices of data visuals before and after exposure to Desnoyers' taxonomy.

Results: Students chose more complex and more efficient data visuals on the posttest, after exposure to Desnoyers' taxonomy. However, level in school did not change the effect of exposure.

Conclusion: Students' reported use of data visuals supports prior research about discrepancies between academic and journal data visuals. Additionally, students might benefit from having more exposure and training in efficient data visuals. Further control group studies are needed to show if Desnoyers' taxonomy itself can increase students' comprehension and use of efficient data visuals as compared to pure explanation of data visuals. If the further studies demonstrate that, then researchers and creators in the field of data visualization could confidently adopt Desnoyers' taxonomy as a way to teach and reference data visuals consistently.
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Keywords: DATA VISUALS; GRAPHS AND CHARTS; INTERDISCIPLINARY COMMUNICATION; TAXONOMY; VISUALIZATION

Document Type: Research Article

Publication date: August 1, 2015

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