@article{(Open Science Index):https://publications.waset.org/pdf/10001100,
	  title     = {Visual Analytics in K 12 Education - Emerging Dimensions of Complexity},
	  author    = {Linnea Stenliden},
	  country	= {},
	  institution	= {},
	  abstract     = {The aim of this paper is to understand emerging
learning conditions, when a visual analytics is implemented and used
in K 12 (education). To date, little attention has been paid to the role
visual analytics (digital media and technology that highlight visual
data communication in order to support analytical tasks) can play in
education, and to the extent to which these tools can process
actionable data for young students. This study was conducted in three
public K 12 schools, in four social science classes with students aged
10 to 13 years, over a period of two to four weeks at each school.
Empirical data were generated using video observations and analyzed
with help of metaphors within Actor-network theory (ANT). The
learning conditions are found to be distinguished by broad
complexity, characterized by four dimensions. These emerge from
the actors’ deeply intertwined relations in the activities. The paper
argues in relation to the found dimensions that novel approaches to
teaching and learning could benefit students’ knowledge building as
they work with visual analytics, analyzing visualized data.
},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {9},
	  number    = {2},
	  year      = {2015},
	  pages     = {663 - 671},
	  ee        = {https://publications.waset.org/pdf/10001100},
	  url   	= {https://publications.waset.org/vol/98},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 98, 2015},
	}