Visualizing Data to Support Judgement, Inference, and Decision Making in Learning Analytics: Insights from Cognitive Psychology and Visualization Science

Autor/in	Alhadad, Sakinah S. J.
Titel	Visualizing Data to Support Judgement, Inference, and Decision Making in Learning Analytics: Insights from Cognitive Psychology and Visualization Science
Quelle	In: Journal of Learning Analytics, 5 (2018) 2, S.60-85 (26 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1929-7750
Schlagwörter	Visualization; Data Analysis; Evaluative Thinking; Statistical Inference; Decision Making; Cognitive Psychology; Research Methodology; Cognitive Processes; Design; Research Design + Suchen Sie Ihr Suchwort? Visualisation; Visualisierung; Auswertung; Inferential statistics; Schließende Statistik; Decision-making; Entscheidungsfindung; Kognitive Psychologie; Research method; Forschungsmethode; Cognitive process; Kognitiver Prozess; Forschungsdesign
Abstract	Understanding human judgement and decision making during visual inspection of data is of both practical and theoretical interest. While visualizing data is a commonly employed mechanism to support complex cognitive processes such as inference, judgement, and decision making, the process of supporting and scaffolding cognition through effective design is less well understood. Applying insights from cognitive psychology and visualization science, this paper critically discusses the role of human factors -- visual attention, perception, judgement, and decision making -- toward informing methodological choices when visualizing data. The value of visualizing data is discussed in two key domains: (1) visualizing data as a means of communication; and (2) visualizing data as research methodology. The first applies cognitive science principles and research evidence to inform data visualization design for communication. The second applies data- and cognitive-science to deepen our understanding of data, of its uncertainty, and of analysis when making inferences. The evidence for human capacity limitations -- attention and cognition -- are discussed in the context of data visualizations to support inference-making in both domains, and are followed by recommendations. Finally, how learning analytics can further research on understanding the role data visualizations can play in supporting complex cognition is proposed. (As Provided).
Anmerkungen	Society for Learning Analytics Research. 121 Pointe Marsan, Beaumont, AB T4X 0A2, Canada. Tel: +61-429-920-838; e-mail: info@solaresearch.org; Web site: http://learning-analytics.info/journals/index.php/JLA/
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01