This collaborative research project, funded by NSF, aims to co-design and study approaches that integrate art and mathematics to promote data literacy learning and instruction for middle school students and teachers. Many existing efforts to promote data literacy are grounded in mathematical concepts of measures of center and standard deviation or narrowly focused in single subject domains, such as science and math. Taking an art-based perspective on data science has the potential to promote student relevance, accessibility, engagement, reasoning, and meaning-making with data science. However, little research has examined how to equip teachers to develop such interdisciplinary pedagogical approaches to cultivate their students’ data literacy. This project asks: (1) How do we support effective co-design of data literacy units among art teachers, mathematics teachers, and researchers? (2) How are teachers able to use the unit materials in their classrooms to engage students in data literacy? And (3) How does an art-based approach support students’ data literacy? Answers to these questions will build an understanding of how to support interdisciplinary curriculum design collaborations among researchers and teachers. They will also show how art-integrated, maker-oriented activities can support middle school learners’ data literacy development; and how to design technologies that are accessible and powerful to teachers and learners in these interdisciplinary environments.
This research project is led by Megan Silander at EDC, Camillia Matuk and Kayla DesPortes at NYU, and Ralph Vacca at Fordham University.
This project is funded by the National Science Foundation, grant # 1908030. Any opinions, findings, and conclusions or recommendations expressed in these materials are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.