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The analysis of quantitative data and its display in visual formats to explore patterns and communicate the findings is an important practice across many disciplines within and beyond STEM. However, creating effective and appropriate displays of data is a multi-faceted and reflective task. It requires knowledge of and reasoning with relevant disciplinary concepts of the system under study, methodologies and measurements, mathematics/statistics, and visualizations. Undergraduate biology students have the opportunity to analyze, display, and interpret data in their lectures, laboratory courses and as part of research lab apprenticeships. However, we have had an incomplete understanding of the areas in which students have difficulty and competence in order to make evidence-based instructional decisions. We have built from our previous research in interview contexts to develop a digital performance-based assessment tool with the potential to gather data on the graphing practices from large numbers of students. In this session participants will: (1) learn about a framework we developed that can guide learning objectives for teaching and assessment, (2) learn about common areas of student competence and difficulty with graphing based on data from our large-scale student use of our digital assessment across the U.S. and (3) share experiences and work together to outline a lesson plan to support students in developing their graphing skills.