@article {DOI269,
	title = {Be the Data: Embodied Visual Analytics},
	journal = {IEEE Transactions on Learning Technologies},
	volume = {11},
	year = {2018},
	pages = {81-95},
	doi = {10.1109/TLT.2017.2757481},
	author = {Xin Chen and Self, Jessica Zeitz and House, Leanna and Wenskovitch, John and Sun, Maoyuan and Nathan Wycoff and Jane Robertson Evia and Leman, Scotland and North, Chris}
}
@conference {DOI265,
	title = {Bringing Interactive Visual Analytics to the Classroom for Developing EDA Skills},
	booktitle = {Proceedings of the 33rd Annual Consortium of Computing Sciences in Colleges (CCSC) Eastern Regional Conference},
	year = {2017},
	month = {10/2017},
	pages = {10},
	author = {Self, Jessica Zeitz and Self, Nathan and House, Leanna and Jane Robertson Evia and Leman, Scotland and North, Chris}
}
@conference {DOI245,
	title = {Be the Data: An Embodied Experience for Data Analytics},
	booktitle = { 2016 Annual Meeting of the American Educational Research Association (AERA)},
	year = {2016},
	month = {04/2016},
	pages = {20},
	author = {Xin Chen and House, Leanna and Self, Jessica Zeitz and Leman, Scotland and Jane Robertson Evia and James Thomas Fry and North, Chris}
}
@article {DOI244,
	title = {Bringing Interactive Visual Analytics to the Classroom for Developing EDA Skills},
	year = {2015},
	institution = {Virginia Tech},
	type = {Technical Report},
	address = {Blacksburg},
	abstract = {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{\textquoteright} capacity for making dimensionally complex insights from data. Using this concept, we build a vocabulary and methodology to support a student{\textquoteright}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{\textquoteright} CD begin low and improve.},
	keywords = {dimension reduction, education, multidimensional scaling, multivariate analysis, Visual Analytics},
	author = {Self, Jessica Zeitz and Self, Nathan and House, Leanna and Jane Robertson Evia and Leman, Scotland and North, Chris}
}
