How Does This Look? Desirability Methods for Evaluating Visual Design

Guzman, Edward S. De; Schiller, Julie

doi:10.1007/978-3-642-22098-2_25

Cited by 5 publications

(4 citation statements)

References 8 publications

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“…The choice of visualisation however largely depends on the context and type of audience. Images that arouse an emotional response are known to influence first impressions and can affect usability and trust (Guzman and Schiller 2011). While visuals might be considered more accessible than other forms of communication they are however commonly misunderstood (Shah and Hoeffner 2002).…”

Section: Theory Of Visualisationmentioning

confidence: 99%

The unseen uncertainties in climate change: reviewing comprehension of an IPCC scenario graph

2015

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The reports published by the Intergovernmental Panel on Climate Change (IPCC) are comprehensive assessments of the scientific knowledge and uncertainties surrounding climate projections. They combine well-formed language with supporting graphical evidence and have the objective to inform policymakers. One of the most discussed and widely distributed visual in these reports is the graph, showing the global surface temperature evolution for the 21st century as simulated by climate models for various emission scenarios, which is part of the Summary for Policymakers (SPM) and the Working Group I contribution to the Fourth Assessment Report (AR4). It displays two types of uncertainties, namely the socio-economic scenarios and response uncertainty due to imperfect knowledge and models. Through 43 in-depth interviews this graph and caption was empirically tested with a sample of people analogous to the SPM target audience. It was found that novice readers were unable to identify the two different types of uncertainties in this graph without substantial guidance. Instead they saw a great deal of uncertainty but falsely attributed it to the climate model(s) and ignored the scenario uncertainties. Our findings demonstrate how the choice of display can directly impact a reader's perception of the scientific message. A failure to distinguish between these two types of uncertainties could lead to an overestimate of the response uncertainties, and an underestimation of socio-economic choices. We test this assumption and identify the difficulties non-technical audiences have with this graph and how this could inevitably impede its value as a decision support tool.

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Section: Theory Of Visualisationmentioning

confidence: 99%

The unseen uncertainties in climate change: reviewing comprehension of an IPCC scenario graph

2015

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“…Results of reaction cards can be analysed and used in a variety of ways, but they are still most commonly presented in form of a word cloud [4,7,8]. The most comprehensive but basic description of possible analysis has so far been provided by Barnum and Palmer [10], who reported on using the following methods in their experiments with reaction cards: a) the number of positive cards b) the percentage of positive vs. negative chosen words c) mapping the frequency of a few chosen cards on a radar graph d) presenting the frequency of selected cards in a graph or a word cloud, and e) creating meaningful clusters.…”

Section: Reaction Card Methodsmentioning

confidence: 99%

Evaluation of information visualization techniques

Merčun

2014

Proceedings of the Fifth Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization

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The paper originates from the idea that in the field of information visualization, positive user experience is extremely important if we wish to see users adopt and engage with the novel information visualization tools. Suggesting the use of product reaction card method to evaluate user experience, the paper gives an example of FrbrVis prototype to demonstrate how the results of this method could be analysed and used for comparing different designs. The authors also propose five dimensions of user experience (UX) that could be gathered from reaction cards and conclude that the results from reaction cards mirror and add to other performance and preference indicators.

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“…Table 1 summarizes the methodologies used in each of the three rounds of research. The research strategy builds on [3] which focused solely on the VDCS and lacked a comparison of the data from VDCS with any other technique (row 1). In the second round of research (row 2) we compared VDCS with data from a think aloud protocol.…”

Section: Methodsmentioning

confidence: 99%

“…In [3] De Guzman and Schiller described the Visual Design Card Sort (VDCS) as a technique to assess visual design and presented several explorations of visualizations for presenting data from this method. The work in this paper builds upon this previous research in two ways.…”

Section: Introduction and Related Workmentioning

confidence: 99%

Desirability Methods for Evaluating Visual Design

Schiller

Guzman

2013

Communications in Computer and Information Science

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Previous studies show that traditional usability evaluation methods can be problematic for collecting feedback on visual design [1]. Desirability studies have been used by usability practitioners to collect feedback on the affective response to interactive systems, but none allow end users to contribute feedback in the language of visual design experts. We describe how we adapted two traditional user research techniques (card sort, directed storytelling) to collect feedback on visual design. We then compare and contrast the kinds of data gathered from these methods with data gathered in a think-aloud exercise. A mixed-methods research strategy that includes methods adapted for visual design offers a path to engaging end users in a conversation that results in concise and actionable feedback for visual designers.

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How Does This Look? Desirability Methods for Evaluating Visual Design

Cited by 5 publications

References 8 publications

The unseen uncertainties in climate change: reviewing comprehension of an IPCC scenario graph

The unseen uncertainties in climate change: reviewing comprehension of an IPCC scenario graph

Evaluation of information visualization techniques

Desirability Methods for Evaluating Visual Design

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