Visual Analytics in K 12 Education - Emerging Dimensions of Complexity
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.
[1] Hilbert, M.; López, P. The world’s technological capacity to store,
communicate, and compute information. Science 2011, 1 April, 60-65.
[2] Chakravarty, R. Information literacy in the knowledge society
empowering learners for a better tomorrow. In Trends and strategic
issues for libraries in global information society, Chandigarh, India, 18-
19 March 2008. Eds. Mahajan, P., Vohra, R., & Chakravarty, R. Patiala:
Twenty First Century Publications: 2008, pp 303.
[3] Manyika, J.; Chui, M.; Brown, B.; Bughin, J.; Dobbs, R.; Roxburgh, C.;
Hung Byers, A. Big data: the next frontier for innovation, competition,
and productivity. 2011, May.
[4] Ludvigsen, S. R. What counts as knowledge: learning to use categories
in computer environments. Learning, Media and Technology2012, 37,
40-52.
[5] Tomaszewski, B. Producing geo-historical context from implicit
sources: a geovisual analytics approach. Cartographic Journal 2008, 45,
165.
[6] Keim, D.; Andrienko, G.; Fekete, J.; Görg, C.; Kohlhammer, J.;
Melançon, G. Visual analytics: definition, process, and challenges;
information visualization - human-centered issues and perspectives.
(Lecture Notes in Computer Science (including subseries Lecture Notes
in Artificial Intelligence and Lecture Notes in Bioinformatics); 2008;
Vol. 4950 LNCS, pp 154-175.
[7] Tomaszewski, B. M.; Robinson, A. C.; Weaver, C.; Stryker, M.;
Maceachren, A. M. In Geovisual analytics and crisis management;
proceedings of the 4th international ISCRAM Conference, May 13-16,
2007, pp 173-179.
[8] Ongstad, S. In Fag i endring. om didaktisering av kunnskap; Ongstad,
S., Ed.; Fag og didaktikk i laererutdanning. Kunnskap i grenseland;
Universitetsforlaget, 2006; pp 19-57.
[9] Andrienko, G,; Andrienko, N.; Demsar, U.; Dransch, D.; Dykes, J.;
Fabrikant, S. R.; Jern, M.; Kraak, M. H.; Schumann, H.; Tominski, C.
Space, time and visual analytics. International Journal of Geographical
Information Science, Special Issue: Geospatial Visual Analytics: Focus
on Time Special Issue of the ICA Commission on GeoVisualization.2010,
Volume 24.
[10] Fenwick, T. J.; Edwards, R. Actor-network theory in education.
Routledge: London; New York, 2010.
[11] Halverson, R.; Shapiro, R. B. Technologies for education and
technologies for learners: how information technologies are (and should
be) changing schools. (WCER Working Paper No. 2012-6). Retrieved
from University of Wisconsin–Madison, Wisconsin Center for
Education Research website 2012.
[12] Gagné, R. M. The Conditions of learning and theory of instruction.CBS
College Publishing. New York, 1985; Vol. New York: CBS College
Publishing.
[13] Latour, B. Artefaktens återkomst, ett möte mellan organisationsteori och
tingens sociologi. Nerenius & Santérus: Stockholm, 1998.
[14] Reynolds, R.; Vinterek, M. Globalization and classroom practice:
insights on learning about the world in Swedish and Australian schools.
Nordidactica, 2013, pp. 104-130.
[15] Kjällander, S. Designs for learning in an extended digital environment
case studies of social interaction in the social science classroom.
Stockholm: Department of Education, Stockholm University, 2011.
[16] Nicholson, J.; Ridgway, J.; Mccusker, S. Enhancing Statistical Literacy
– Multivariate Thinking in Precollege. Statistical institute: Proc. 58th
world statistical congress. Dublin. (Session STS008), 2011.
[17] Stenliden, L.; Jern, M. Visual Storytelling – Knowledge and
Understanding. Education. Journal of Systemics, Cybernetics and
Informatics 2012, 10, 7-13.
[18] Spanget Christensen, T. Interdisciplinarity and self-reflection in civic
education. Nordidactica 2013, 201-226.
[19] Gärdén, C. Verktyg för lärande: Informationssökning och
informationsanvändning i kommunal vuxenutbildning, Borås: Valfrid.
Diss. Göteborgs universitet, 2010.
[20] Francke, H.; Gärdén, C. In Forskning om informationskompetens i
skolsammanhang; Limberg, L., Lundh, A. H., Eds.; Skolbibliotekets
roller i förändrade landskap; BTJ Förlag.: Lind, 2013; .
[21] Alexandersson, M.; Limberg, L. Constructing meaning through
information artefacts. The New Review of Information Behaviour
Research 2003, 4, pp.17-30.
[22] Kress, G. R. Multimodality a social semiotic approach to contemporary
communication; Routledge: London, 2010.
[23] Auletta, K., Ed. Googled. The end of the world as we know it. Virgin
Books: London, 2009.
[24] Alexandersson, M.; Limberg, L.; Lantz-Andersson, A.; Kylemark, M.
Textflytt och sökslump - informationssökning via skolbibliotek.
Stockholm: Myndigheten för skolutveckling: 2007;
[25] Limberg, L.; Alexandersson, M.; Lantz-Andersson, A., Eds.to be lost
and to be a loser through the web. Handbook of research on digital
information technologies: innovations, methods, and ethical issues.
2008, pp. 249-263.
[26] Lundh, A.; Limberg, L. Information practices in elementary school. libri,
58(2), pp. 63-135. 2008.
[27] Limberg, L. Experiencing information seeking and learning research on
patterns of variation; Wilson, T., Maceviciute, E., Eds. Introducing
information management an information research reader; 2005; pp. 68-
80.
[28] Alexandersson, M.; Limberg, L. Conditions for information use and
learning in swedish schools: a synthesis of research. HumanIT, 2012, 11,
pp.131-154.
[29] Sandahl, J. Att ta sig an världen, lärare diskuterar innehåll och mål i
samhällskunskapsämnet. Karlstad: Karlstad University Press, 2011.
[30] Latour, B. Reassembling the social an introduction to actor-networktheory,
Oxford University Press: Oxford, 2005.
[31] Pinch, T. J.; Bijker, W. The social construction of facts and artifacts or
how the sociology of science and the sociology of technology might
benefit each other; Wiebe, E., Bijker, Thomas, P., Hughes, Trevor, J.
and Pinch, T. J., Eds.; In The social construction of technological
systems, new directions in the sociology and history of technology, MIT
Press: Cambridge, Mass., 1987; pp. 17-50.
[32] Lantz-Andersson, A. Framing in educational practices, learning
activity, digital technology and the logic of situated action. Göteborg:
Acta Universitatis Gothoburgensis, 2009.
[33] Latour, B. We have never been modern. Harvard Univ. Press:
Cambridge, Mass., 1993.
[34] Gill, T. G.; Hicks, R. C. Task complexity and informing science: a
synthesis. Informing Science Journal, 2006, 9.
[35] Patton, M. Q. Qualitative research & evaluation methods.SAGE:
London, 2004.[36] Ho, Q.; Lundblad, P.; Åström, T.; Jern, M. A Web-enabled visualization
toolkit for geovisual analytics visualisation and data analysis; 2011;
Information Visualization 11(1), pp. 22-42.
[37] Lundblad, P. Applied geovisual analytics and storytelling. 2013, 59.
linköping, the department of science and technology, Linköping
University.
[38] Lundblad, P.; Stenliden, L. VISE - Visual storytelling in school,
courseresources. http://ncomva.se/vise/(Accessed 09/30, 2013).
[39] Heath, C.; Hindmarsh, J.; Luff, P. Video in qualitative research
analysing social interaction in everyday life.SAGE: Los Angeles, 2010.
[40] Jordan, B.; Henderson, A. Interaction Analyses: Fondations and
Practics. 1995, 4, pp. 39-103.
[41] TechSmith Corporation.Camtasia Studio. 12 October, 2010. Retrieved
19 June 2011.
[42] Callon, M.; Law, J.; Rip, A. Mapping the dynamics of science and
technology, sociology of science in the real world. London: Macmillan
1986.
[43] Stafford, B.; Terpak, F. Revealing technologies - magical domains;
Devices of wonder: from the world in a box to images on a screen; Getty
Research Institute, Los Angeles, 2001; pp. 1-109.
[44] Wood, R. E. Task complexity: definition of the construct. Organ. Behav.
Hum. Decis. Process. 1986, 37, pp.60-82.
[45] Campbell, D. J. Task complexity: a review and analysis. Academy of
Management Review 1988, 13, pp. 40-52.
[46] Sandahl, J. Being Engaged and knowledgeable: social science thinking
concepts and students’ civic engagement in teaching on globalisation.
Nordidactica.2013, pp. 158-179.
[47] Hmelo-Silver, C. E. Creating a learning space in problem-based
learning. Interdisciplinary Journal of Problem-based Learning, 2013, 7.
[1] Hilbert, M.; López, P. The world’s technological capacity to store,
communicate, and compute information. Science 2011, 1 April, 60-65.
[2] Chakravarty, R. Information literacy in the knowledge society
empowering learners for a better tomorrow. In Trends and strategic
issues for libraries in global information society, Chandigarh, India, 18-
19 March 2008. Eds. Mahajan, P., Vohra, R., & Chakravarty, R. Patiala:
Twenty First Century Publications: 2008, pp 303.
[3] Manyika, J.; Chui, M.; Brown, B.; Bughin, J.; Dobbs, R.; Roxburgh, C.;
Hung Byers, A. Big data: the next frontier for innovation, competition,
and productivity. 2011, May.
[4] Ludvigsen, S. R. What counts as knowledge: learning to use categories
in computer environments. Learning, Media and Technology2012, 37,
40-52.
[5] Tomaszewski, B. Producing geo-historical context from implicit
sources: a geovisual analytics approach. Cartographic Journal 2008, 45,
165.
[6] Keim, D.; Andrienko, G.; Fekete, J.; Görg, C.; Kohlhammer, J.;
Melançon, G. Visual analytics: definition, process, and challenges;
information visualization - human-centered issues and perspectives.
(Lecture Notes in Computer Science (including subseries Lecture Notes
in Artificial Intelligence and Lecture Notes in Bioinformatics); 2008;
Vol. 4950 LNCS, pp 154-175.
[7] Tomaszewski, B. M.; Robinson, A. C.; Weaver, C.; Stryker, M.;
Maceachren, A. M. In Geovisual analytics and crisis management;
proceedings of the 4th international ISCRAM Conference, May 13-16,
2007, pp 173-179.
[8] Ongstad, S. In Fag i endring. om didaktisering av kunnskap; Ongstad,
S., Ed.; Fag og didaktikk i laererutdanning. Kunnskap i grenseland;
Universitetsforlaget, 2006; pp 19-57.
[9] Andrienko, G,; Andrienko, N.; Demsar, U.; Dransch, D.; Dykes, J.;
Fabrikant, S. R.; Jern, M.; Kraak, M. H.; Schumann, H.; Tominski, C.
Space, time and visual analytics. International Journal of Geographical
Information Science, Special Issue: Geospatial Visual Analytics: Focus
on Time Special Issue of the ICA Commission on GeoVisualization.2010,
Volume 24.
[10] Fenwick, T. J.; Edwards, R. Actor-network theory in education.
Routledge: London; New York, 2010.
[11] Halverson, R.; Shapiro, R. B. Technologies for education and
technologies for learners: how information technologies are (and should
be) changing schools. (WCER Working Paper No. 2012-6). Retrieved
from University of Wisconsin–Madison, Wisconsin Center for
Education Research website 2012.
[12] Gagné, R. M. The Conditions of learning and theory of instruction.CBS
College Publishing. New York, 1985; Vol. New York: CBS College
Publishing.
[13] Latour, B. Artefaktens återkomst, ett möte mellan organisationsteori och
tingens sociologi. Nerenius & Santérus: Stockholm, 1998.
[14] Reynolds, R.; Vinterek, M. Globalization and classroom practice:
insights on learning about the world in Swedish and Australian schools.
Nordidactica, 2013, pp. 104-130.
[15] Kjällander, S. Designs for learning in an extended digital environment
case studies of social interaction in the social science classroom.
Stockholm: Department of Education, Stockholm University, 2011.
[16] Nicholson, J.; Ridgway, J.; Mccusker, S. Enhancing Statistical Literacy
– Multivariate Thinking in Precollege. Statistical institute: Proc. 58th
world statistical congress. Dublin. (Session STS008), 2011.
[17] Stenliden, L.; Jern, M. Visual Storytelling – Knowledge and
Understanding. Education. Journal of Systemics, Cybernetics and
Informatics 2012, 10, 7-13.
[18] Spanget Christensen, T. Interdisciplinarity and self-reflection in civic
education. Nordidactica 2013, 201-226.
[19] Gärdén, C. Verktyg för lärande: Informationssökning och
informationsanvändning i kommunal vuxenutbildning, Borås: Valfrid.
Diss. Göteborgs universitet, 2010.
[20] Francke, H.; Gärdén, C. In Forskning om informationskompetens i
skolsammanhang; Limberg, L., Lundh, A. H., Eds.; Skolbibliotekets
roller i förändrade landskap; BTJ Förlag.: Lind, 2013; .
[21] Alexandersson, M.; Limberg, L. Constructing meaning through
information artefacts. The New Review of Information Behaviour
Research 2003, 4, pp.17-30.
[22] Kress, G. R. Multimodality a social semiotic approach to contemporary
communication; Routledge: London, 2010.
[23] Auletta, K., Ed. Googled. The end of the world as we know it. Virgin
Books: London, 2009.
[24] Alexandersson, M.; Limberg, L.; Lantz-Andersson, A.; Kylemark, M.
Textflytt och sökslump - informationssökning via skolbibliotek.
Stockholm: Myndigheten för skolutveckling: 2007;
[25] Limberg, L.; Alexandersson, M.; Lantz-Andersson, A., Eds.to be lost
and to be a loser through the web. Handbook of research on digital
information technologies: innovations, methods, and ethical issues.
2008, pp. 249-263.
[26] Lundh, A.; Limberg, L. Information practices in elementary school. libri,
58(2), pp. 63-135. 2008.
[27] Limberg, L. Experiencing information seeking and learning research on
patterns of variation; Wilson, T., Maceviciute, E., Eds. Introducing
information management an information research reader; 2005; pp. 68-
80.
[28] Alexandersson, M.; Limberg, L. Conditions for information use and
learning in swedish schools: a synthesis of research. HumanIT, 2012, 11,
pp.131-154.
[29] Sandahl, J. Att ta sig an världen, lärare diskuterar innehåll och mål i
samhällskunskapsämnet. Karlstad: Karlstad University Press, 2011.
[30] Latour, B. Reassembling the social an introduction to actor-networktheory,
Oxford University Press: Oxford, 2005.
[31] Pinch, T. J.; Bijker, W. The social construction of facts and artifacts or
how the sociology of science and the sociology of technology might
benefit each other; Wiebe, E., Bijker, Thomas, P., Hughes, Trevor, J.
and Pinch, T. J., Eds.; In The social construction of technological
systems, new directions in the sociology and history of technology, MIT
Press: Cambridge, Mass., 1987; pp. 17-50.
[32] Lantz-Andersson, A. Framing in educational practices, learning
activity, digital technology and the logic of situated action. Göteborg:
Acta Universitatis Gothoburgensis, 2009.
[33] Latour, B. We have never been modern. Harvard Univ. Press:
Cambridge, Mass., 1993.
[34] Gill, T. G.; Hicks, R. C. Task complexity and informing science: a
synthesis. Informing Science Journal, 2006, 9.
[35] Patton, M. Q. Qualitative research & evaluation methods.SAGE:
London, 2004.[36] Ho, Q.; Lundblad, P.; Åström, T.; Jern, M. A Web-enabled visualization
toolkit for geovisual analytics visualisation and data analysis; 2011;
Information Visualization 11(1), pp. 22-42.
[37] Lundblad, P. Applied geovisual analytics and storytelling. 2013, 59.
linköping, the department of science and technology, Linköping
University.
[38] Lundblad, P.; Stenliden, L. VISE - Visual storytelling in school,
courseresources. http://ncomva.se/vise/(Accessed 09/30, 2013).
[39] Heath, C.; Hindmarsh, J.; Luff, P. Video in qualitative research
analysing social interaction in everyday life.SAGE: Los Angeles, 2010.
[40] Jordan, B.; Henderson, A. Interaction Analyses: Fondations and
Practics. 1995, 4, pp. 39-103.
[41] TechSmith Corporation.Camtasia Studio. 12 October, 2010. Retrieved
19 June 2011.
[42] Callon, M.; Law, J.; Rip, A. Mapping the dynamics of science and
technology, sociology of science in the real world. London: Macmillan
1986.
[43] Stafford, B.; Terpak, F. Revealing technologies - magical domains;
Devices of wonder: from the world in a box to images on a screen; Getty
Research Institute, Los Angeles, 2001; pp. 1-109.
[44] Wood, R. E. Task complexity: definition of the construct. Organ. Behav.
Hum. Decis. Process. 1986, 37, pp.60-82.
[45] Campbell, D. J. Task complexity: a review and analysis. Academy of
Management Review 1988, 13, pp. 40-52.
[46] Sandahl, J. Being Engaged and knowledgeable: social science thinking
concepts and students’ civic engagement in teaching on globalisation.
Nordidactica.2013, pp. 158-179.
[47] Hmelo-Silver, C. E. Creating a learning space in problem-based
learning. Interdisciplinary Journal of Problem-based Learning, 2013, 7.
@article{"International Journal of Business, Human and Social Sciences:69631", author = "Linnea Stenliden", title = "Visual Analytics in K 12 Education - Emerging Dimensions of Complexity", 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.
", keywords = "Analytical reasoning, complexity, data use, problem
space, visual analytics, visual storytelling, translation.", volume = "9", number = "2", pages = "656-9", }
