Big data to support geoscience recruitment: Novel adoption of topological data analysis in geoscience education

Abstract

As the need for a well-trained science, technology, engineering, and mathematics (STEM) workforce continuously grows, the need for science majors—including geoscience majors—is ever increasing. Despite this, low numbers of majors across geoscience programs continue to persist and may be the result of many students not being exposed to geoscience concepts early in their education or having misconceptions about who is able to participate in geoscience and what these careers may look like. The application of topological data analysis (TDA), an algorithm that allows researchers to explore multidimensional data with more nuance than traditional clustering methods, represents a new tool for quantitative investigation within geoscience education. The results of TDA from a large-n survey of students in introductory geoscience classes about their perceptions of geoscience and likelihood of pursuing geoscience careers provides insight into students, including those traditionally underrepresented in geoscience, who could be recruited into the discipline. Insights into this novel application of data science methodology to educational research are provided alongside recruitment recommendations for students traditionally underrepresented in the geosciences.