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Representation Effects and Loss Aversion in Analytical Behaviour: An Experimental Study into Decision Making Facilitated by Visual Analytics
This paper presents the results of an experiment into the relationship between the representation of data and decision-making. Three hundred participants online, were asked to choose between a series of financial investment opportunities using data presented in line charts. A single dependent variable of investment choice was examined over four levels of varying display conditions and randomised data. Three variations to line chart visualisations provided a controlled factor between subjects divided into three groups; -˜standard’ line charts, -˜tall’ line charts, and one dual-series line chart. The final results revealed a consistent main effect and two other interactions between certain display conditions and decision-making. The findings of this paper are significant to the study visualisation and to the field of visual analytics. This experiment was devised as part of a study into Analytical Behaviour, defined as decision-making facilitated by visual analytics - a new topic that encompasses existing research and real-world applications
The four faces of information visualization: A conceptual framework for a postgraduate program
The multidisciplinary nature of information visualization is today fairly consensual in both professional and academic communities: data analysis, information design, storytelling, among other subjects, are common drivers in this field. The systematic study of this cross-fertilization, patent in the way the concept's definition varies according to the perspective being adopted, represents an important and needed addition to the critical mass of a relatively recent area of knowledge. The proposal of a single unified definition of information visualisation being beyond the scope of this paper, it instead summons and discusses its multiple viewpoints to help designing a postgraduate program on the topic, aiming to simultaneously start an open debate as its implementation phase goes on and new questions are subsequently raised.info:eu-repo/semantics/acceptedVersio
Dashboards and visualisation tools for enhancing creativity in business master students
[EN] Dashboards are a basic element in Data Science. Well planned dashboards help the staff of a
company at all levels of the organization. They allow them to ask questions and respond them in real
time. As a result, this information allows them to make appropriate decisions and facilitates innovation.
A fundamental component in the dashboards are the visualizations by means of dynamic graphic
objects that can be explored. These visualizations must be analyzed dynamically so that business
master students can intuitively arrive at a series of insights that bring them closer to the nature of the
problems.
Learning by doing and consulting. We are going to use a dashboard about innovation elaborated by
Bankinter Fundation in the Platform Google Data Analytics. The proposed teaching dynamic includes
the formation of work teams of 5-7 students. The challenge start when each group pose several
questions to the rest of the teams. To answer these questions the students must consult the proposed
dashboard. There is a time limit to answer each question. The winner is the team that answers
correctly more questions and explains the way to obtain this information. This way, students get used
to dashboards and visualisation tools and start learning with a good dashboard model that prepares
them to later select and design proper tools. As a further result, we have appreciated that using
visualisation in teaching can increase student engagement and performance.González-Ladrón-De-Guevara, F.; Fernández-Diego, M. (2021). Dashboards and visualisation tools for enhancing creativity in business master students. IATED. 8799-8804. https://doi.org/10.21125/inted.2021.1836S8799880
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