With the growing interest in Big Data, researchers are calling for a reframing of key questions about what constitutes knowledge found in very large data settings (Boyd & Crawford, 2012). Many researchers are developing new ways to access and organize Big Data, and many academic institutions are offering new courses that focus on analyzing Big Data. Many Big Data course syllabi require statistics and programming as prerequisites (Friedman, 2017). It is common for instructors to report resistance from students to learning statistics (Schoenfeld, 1992). There are a variety of reasons for this resistance—for example, students may feel that statistics lack vividness or the ability to engage their emotions (Hill, 2004). While there is already a large body of research on the benefits of visuals in education (Gilbert, 2008), a review of this literature could not produce a detailed model for a visualization- centric statistics curriculum at the undergraduate level.
2018 Friedman, A & Schneider, E. “Developing a Visualization Education Curriculum in the Age of Big Data Using the Dick and Carey Model.” Visual Communication Quarterly 25(4) .
