Benefits and trade-offs of different model representations in decision support systems for non-expert users

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Abstract

Researchers have reported a lack of experience and low graph literacy as significant problems when making visual analytics applications available to a general audience. Therefore, it is fundamental to understand the strengths and weaknesses of different visualizations in the decision-making process. This paper explores the benefits and challenges of an intuitive, a compact, and a detailed visualization for supporting non-expert users. Using objective and subjective means proposed by earlier work, we determine the benefits and trade-offs of these visualizations for different task complexity levels. We found that while an intuitive visualization can be a good choice for easy level and medium level tasks, hard level tasks are best supported with a richer, yet visually more demanding visualization.

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Gutiérrez, F., Ochoa, X., Seipp, K., Broos, T., & Verbert, K. (2019). Benefits and trade-offs of different model representations in decision support systems for non-expert users. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11747 LNCS, pp. 576–597). Springer Verlag. https://doi.org/10.1007/978-3-030-29384-0_35

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