Using Models From the Literature and Iterative Feedback to Teach Students to Construct Effective Data Figures for Poster Presentations

Analyzing, interpreting, and clearly presenting real data are skills we hope to develop in all students, majors and nonmajors alike. These process skills require lots of practice coupled with targeted feedback from instructors or mentors. Here we present a pedagogy implemented within a course-based research experience that is designed to help students to develop and practice these skills, while generating proper data figures for use in posters. Students use models derived from the literature to identify essential elements of effective data figures, along with iterative feedback from their instructors, to prepare their own figures for data they have collected over the course of the term. In the process, students think more deeply about what they did, why they did it, and why it is important. Students begin to move from seeking a "correct" answer toward deeper engagement in the scientific process. This instructional approach facilitated positive gains in the quality of student figures. Though our student-prepared figures were for poster presentations, the same process could be used to generate data figures for lab reports or research papers.