TOPOLOGICAL DATA ANALYSIS AS A TOOL TO ASSESS GEOSCIENCE STUDENT RECRUITMENT POTENTIAL
Students taking an introductory geoscience course (n=1681) at an institution in the southeastern United States completed a survey early in the semester that addressed their intentions for continuing in the geosciences, perceptions of the learning environment, career motivations, sense of belonging, connectedness to nature, attitudes towards scientific research, and perceptions of geoscience. The results of this survey can give an indication of these student’s recruitment potential into the geosciences.
Responses were sorted into ten groups using Topological Data Analysis (TDA). Originally designed as a way of describing the topology of datasets for image processing, TDA is an emerging method to assist in categorization of survey responses. An algorithm clusters responses together based on similarities. This analysis produced ten groups, which were further merged by the researchers into three primary groups based on recruitment potential: high (14% of the population), moderate (58%), and low (28%).
The highly recruitable group identified by TDA analysis is >200 students, approximately twice the number of students who indicated that they were likely or very likely to add/change their major to geology when asked directly. Effectively recruiting even a fraction of these ‘highly recruitable’ students will make a significant impact on the total number of geoscience students and increase the number of students considering geoscience as at least part of their future careers. Topological data analysis can be useful in identifying and understanding students that could be interested in the geosciences but have not yet had enough exposure or experience to identify this interest, thus shaping future recruitment practices and broadening student awareness of their (geoscience) career options.