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The ability to analyze, interpret, and draw insights from data and data visualizations is quickly becoming a necessary skill for success across multiple disciplines and careers. However, people struggle to make meaning from data, and traditional data-science curriculum falls short of emphasizing its relevance to underrepresented students. To create opportunities for meaningful applications of data-science for diverse students, we developed and implemented an online learning module focused on engaging N = 298 undergraduate students at a Hispanic Serving Institution (HSI) in an analysis of place-based soil data. Using a pretest posttest study design, we found that student’s perceptions of data-science relevance microbiology knowledge improved. We also inductively coded qualitative survey responses and used automated text analysis to explore how students framed “relevance” and how perceptions changed from pretest-to-posttest.
Ian Thacker, University of Texas at San Antonio
Rebecca Schroeder, University of Texas at San Antonio
Sara Shields-Menard, University of Texas at San Antonio
Corina Lopez, University of Texas at San Antonio
Sandrina Ramirez, University of Texas at San Antonio
Tanvir Alam, University of Texas at San Antonio