Data Visualization Literacy: Investigating Data Interpretation Along the Novice—Expert Continuum

• Published in: Journal of college science teaching 2015-09, Vol.45 (1), p.84-90
• Main Authors: Maltese, Adam V., Harsh, Joseph A., Svetina, Dubravka
• Format: Article
• Language: English
• Subjects: College science; College students; Data analysis; Data Interpretation; Data visualization; Educational research; Graduate students; Graph representations; Individualized Instruction; International environmental cooperation; Kinematics; Mathematical data; Mathematics education; Psychometrics; RESEARCH AND TEACHING; Scientific Literacy; STEM education; Visualization
• ISSN: 0047-231X; 1943-4898
• DOI: 10.2505/4/jcst15_045_01_84

In the STEM fields, adequate proficiency in reading and interpreting graphs is widely held as a central element for scientific literacy given the importance of data visualizations to succinctly present complex information. Although prior research espouses methods to improve graphing proficiencies, there is little understanding about when and how students develop these skills during the course of their education. To address this gap in the research, we sought to create an assessment tool to measure differences in these abilities across groups with varied levels of experience in science, technology, engineering, and mathematics. This study presents results from a data visualization literacy assessment we created to begin to understand the development of expertise in this domain. Initial results indicate significant differences in the skill levels of expert and novice end-members, but little differentiation between the groups across the middle of this spectrum. Psychometric properties of the assessment are presented, and suggested implications for instruction are discussed.