Do Demographics and the Type of Data Visualization Influence the Interpretation of Data?

Presentation Type

Poster

Student

Yes

Track

Other

Abstract

The literature review indicates that as students get older, they improve their critical thinking skills. Data can be hard to explain with words or numbers, so there needs to be a way to present data that allows it to be translated into information and knowledge that can be used to guide people to make well-informed decisions. The data should be presented with a medium that aids each person in making these decisions. We used survey and data visualization research to create a survey to investigate our research question with different data visualizations. We considered types of graphs, colors, fonts, and styles when creating our visualizations. The responses to our survey were analyzed to determine the difference between undergraduate and graduate students’ responses to see if the level of life experience and age influences the correct interpretation of the data visualizations. Future data analysis will allow us to analyze if there is a significant difference in the interpretation of the data visualizations based on the subgroups of gender and age.

Start Date

2-11-2020 1:00 PM

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Feb 11th, 1:00 PM

Do Demographics and the Type of Data Visualization Influence the Interpretation of Data?

Volstorff A

The literature review indicates that as students get older, they improve their critical thinking skills. Data can be hard to explain with words or numbers, so there needs to be a way to present data that allows it to be translated into information and knowledge that can be used to guide people to make well-informed decisions. The data should be presented with a medium that aids each person in making these decisions. We used survey and data visualization research to create a survey to investigate our research question with different data visualizations. We considered types of graphs, colors, fonts, and styles when creating our visualizations. The responses to our survey were analyzed to determine the difference between undergraduate and graduate students’ responses to see if the level of life experience and age influences the correct interpretation of the data visualizations. Future data analysis will allow us to analyze if there is a significant difference in the interpretation of the data visualizations based on the subgroups of gender and age.