TY - CONF T1 - Bringing Interactive Visual Analytics to the Classroom for Developing EDA Skills T2 - Proceedings of the 33rd Annual Consortium of Computing Sciences in Colleges (CCSC) Eastern Regional Conference Y1 - 2017 A1 - Self, Jessica Zeitz A1 - Self, Nathan A1 - House, Leanna A1 - Jane Robertson Evia A1 - Leman, Scotland A1 - North, Chris JF - Proceedings of the 33rd Annual Consortium of Computing Sciences in Colleges (CCSC) Eastern Regional Conference ER - TY - RPRT T1 - Bringing Interactive Visual Analytics to the Classroom for Developing EDA Skills Y1 - 2015 A1 - Self, Jessica Zeitz A1 - Self, Nathan A1 - House, Leanna A1 - Jane Robertson Evia A1 - Leman, Scotland A1 - North, Chris KW - dimension reduction KW - education KW - multidimensional scaling KW - multivariate analysis KW - Visual Analytics AB - This paper addresses the use of visual analytics in education for teaching what we call cognitive dimensionality (CD) and other EDA skills. We present the concept of CD to characterize students' capacity for making dimensionally complex insights from data. Using this concept, we build a vocabulary and methodology to support a student’s progression in terms of growth from low cognitive dimensionality (LCD) to high cognitive dimensionality (HCD). Crucially, students do not need high-level math skills to develop HCD. Rather, we use our own tool called Andromeda that enables human-computer interaction with a common, easy to interpret visualization method called Weighted Multidimensional Scaling (WMDS) to promote the idea of making high-dimensional insights. In this paper, we present Andromeda and report findings from a series of classroom assignments to 18 graduate students. These assignments progress from spreadsheet manipulations to statistical software such as R and finally to the use of Andromeda. In parallel with the assignments, we saw students' CD begin low and improve. PB - Virginia Tech CY - Blacksburg ER - TY - RPRT T1 - Improving Students' Cognitive Dimensionality through Education with Object-Level Interaction Y1 - 2014 A1 - Self, Jessica Zeitz A1 - Self, Nathan A1 - House, Leanna A1 - Leman, Scotland A1 - North, Chris KW - multivariate data analysis KW - object level interaction KW - Visual Analytics AB - This paper addresses the use of visual analytics techniques in education to advance students' cognitive dimensionality. Students naturally tend to characterize data in simplistic one dimensional terms using metrics such as mean, median, mode. Real- world data, however, is more complex and students need to learn to recognize and create high-dimensional arguments. Data exploration methods can encourage thinking beyond traditional one dimensional insights. In particular, visual analytics tools that afford object-level interaction (OLI) allow for generation of more complex insights, despite inexperience with multivariate data. With these tools, students’ insights are of higher complexity in terms of dimensionality and cardinality and built on more diverse interactions. We present the concept of cognitive dimensionality to characterize students' capacity for dimensionally complex insights. Using this concept, we build a vocabulary and methodology to support a student’s progression in terms of growth from low to high cognitive dimensionality. We report findings from a series of classroom assignments with increasingly complex analysis tools. These assignments progressed from spreadsheet manipulations to statistical software such as R and finally to an OLI application, Andromeda. Our findings suggest that students' cognitive dimensionality can be improved and further research on the impact of visual analytics tools on education for cognitive dimensionality is warranted. PB - Virginia Tech CY - Blacksburg ER -