Background/Question/Methods: The fast pace of biological data generated nowadays calls for our biology students to be proficient in quantitative skills such as data analysis. This study examined how well undergraduate students can develop data analysis skills relevant to ecology and conservation biology over the course of a single semester. Students completed two data analysis exercises, pre and post self-assessments of confidence in data analysis skills, a classroom discussion, and pre/post content assessments. The two data analysis exercises were adapted from the free online teaching modules on the Network of Conservation Educators and Practitioners website (www.ncep.amnh.org). Between the first exercise (a demography problem involving palm harvests and parrots) and second exercise (calculating diversity indices for spider communities), a data analysis teaching intervention was administered in all classes. Instructional and assessment materials were created and validated by 24 conservation educators led by the Center for Biodiversity and Conservation at AMNH.
Results/Conclusions: Results from one semester show that students scored significantly higher on post-content assessments for both conservation exercises (N1 = 207 students; N2 = 199; P \u3c 0.01 for both). We also found significant increases in student self-assessment of confidence in data analysis skills (N = 87). However, when evaluated at the level of different skill dimensions, students’ ability to represent and interpret data improved between exercises (N = 257; P \u3c 0.01), but ability to complete calculations and draw conclusions was significantly worse on the second exercise (P \u3c 0.01). While our study demonstrates that direct instruction in data analysis does improve student performance overall, there is a disconnect between student self-assessment of their data analysis skills and their actual ability. This indicates that some aspects of data analysis may require different teaching intervention approaches
