Analysis Tools

Data analysis tools help researchers make sense of the data collected. It enables them to report results and make interpretations. How the data is analyzed depends on the goals of the project and the type of data collected. Some studies focus on qualitative data, others on quantitative data, and many on both (mixed-methods studies); examples of these can be found in a NAGT-GER Division hosted collection of presentations on Methods for Conducting GER. The Analytical Tool collection includes examples in these areas, as well as special types of analytical tool used for data specific applications and data visualizations. Quantitative and Qualitative methods both use deductive, inductive, and adductive processes to understand a process or phenomenon, just in different ways using different data.

Quantitative Analysis

Quantitative analysis uses numerical data to identify statistical relationships between variables. Quantitative data are numerical, ordinal, nominal. For example, surveys, questionnaires, and evaluations that include multiple choice items and ratings (e.g., Likert scale) provide quantitative data for analysis.

Qualitative Analysis

Qualitative analysis uses descriptive data to understand processes (e.g., how students learn in a group), develop insights into the form of sensitizing concepts, and present the view of the world from the point of view of the participants (e.g., the teachers, students and others related to the classroom). Qualitative data are descriptive. For example, field notes, interviews, video, audio, open-ended survey questions all provide qualitative data for analysis.

Tool Collection

Browse the collection of the most commonly used qualitative and quantitative analysis tools here. Submit a Tool to the Collection »

Special Types of Analyses

Some types of special analyses in geoscience education research depend on data analysis tools original developed for other purposes in the sciences or social sciences. In this section you can find descriptions of some of those tools, including eye tracking analysis software and data visualization tools (e.g., Generic Mapping Tools, MatLab, ArGIS).


Special thanks to Todd Ellis, Jason Jones, Heather Lehto, Steve Reynolds, Julie Rooney-Varga, and Stefany Sit who were part of a working group that helped develop this section of the toolbox.

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