DataVersify: A framework for data literacy instruction featuring scientist stories

Abstract

Developing student data literacy is a core goal of biology education, yet many students struggle to engage with scientific research and data. DataVersify is a resource designed to support data literacy while simultaneously humanizing science. These activities integrate two established programs, Data Nuggets and Project Biodiversify, to engage students in the work of scientists and introduce them to the people behind the research. Within each activity, students encounter a scientist profile, read about a study, explore and visualize a dataset, construct evidence-based explanations, and ask questions of their own. Here, we synthesize over a decade of resource development and classroom-based research to share the features of DataVersify activities, and examine how they influence student engagement with data literacy activities and perceptions of scientists. We found that pairing data literacy activities with humanizing details about a scientist’s life in and out of science increases students’ ability to relate to scientists and engage with course materials. We present six evidence-based recommendations for using DataVersify to teach effectively in the classroom, including emphasizing authenticity, pairing data with scientist stories, and highlighting a variety of contemporary role models. Together, our work demonstrates how integrating authentic data experiences with scientist stories can support student outcomes in data literacy and biology education.