Abstract—This paper aims to determine the distribution of
problem spaces in learning activities, when geovisual analytics is
introduced into social science education. We know that various
dimensions of complexity emerge in learning activities including
this kind of technology. This paper clarifies the features of the
problem spaces in such activities. The study was conducted in
three middle schools in Sweden, in four social science classes
with students aged 10 to 13 years. The specific geovisual
analytics platform used was Statistics eXplorer. The learning
activities were followed for two to four weeks at each school
using video observations. Drawing on actor–network theory, we
conducted material discursive analyses of the learning activities.
The geovisual analytics generally support student
understandings, but the didactic design of the classroom was not
completely supportive. Six central aspects were found in the
distribution of problem spaces within the learning activities.
Novel approaches to pedagogy and teaching employing
geovisual analytics could benefit students’ knowledge building
as they work with visualized data.
Index Terms—Geovisual analytics, visual data, statistics,
visual storytelling, problem spaces, pedagogy, instruction,
analytical reasoning.
L. Stenliden is with the Department of Social and Welfare Studies at
Linköping University, Sweden (e-mail: linnea.stenliden@liu.se).
Cite: Linnéa Stenliden, "Geovisual Analytics in School: Challenges for the Didactic Design of the Classroom," International Journal of Information and Education Technology vol. 8, no. 3, pp. 178-185, 2018.