Grounded relevance: how exploring soil data can promote perceptions of data relevance, data literacy, learning, and...

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 curricula fall short of emphasizing its relevance to underrepresented students. To create opportunities for meaningful applications of data science for racially/ethnically 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 focused on identifying factors related to antibiotic-producing bacteria. Using a pretest-posttest study design, we found that students' perceptions of data science relevance (Cohen's d = 0.33) and microbiology knowledge (d = 0.39) significantly improved. We also inductively coded qualitative survey responses to explore how students framed "relevance" and how their perceptions changed from pretest to posttest, revealing that students perceived data tools as offering new scientific insights and applications across multiple disciplines, although changes over time were not significant. Automated text analysis of students' analytical thinking using LIWC (Linguistic Inquiry and Word Count) revealed that students tended to use significantly less "discrepant" (d =-0.22) and "tentative" (d = -0.19) language over time, suggesting that they increased their level of certainty from pretest to posttest. We also found that students identified more relevant and specific environmental- and soil-specific variables for data investigations at posttest compared to pretest. Overall, our findings provide evidence that interdisciplinary and place-based approaches to microbiology and data literacy instruction support learning and motivation for racially/ethnically diverse groups of students.