TY - JOUR T1 - Be the Data: Embodied Visual Analytics JF - IEEE Transactions on Learning Technologies Y1 - 2018 A1 - Xin Chen A1 - Self, Jessica Zeitz A1 - House, Leanna A1 - Wenskovitch, John A1 - Sun, Maoyuan A1 - Nathan Wycoff A1 - Jane Robertson Evia A1 - Leman, Scotland A1 - North, Chris VL - 11 IS - 1 ER - 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 - CONF T1 - Be the Data: An Embodied Experience for Data Analytics T2 - 2016 Annual Meeting of the American Educational Research Association (AERA) Y1 - 2016 A1 - Xin Chen A1 - House, Leanna A1 - Self, Jessica Zeitz A1 - Leman, Scotland A1 - Jane Robertson Evia A1 - James Thomas Fry A1 - North, Chris JF - 2016 Annual Meeting of the American Educational Research Association (AERA) 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 -