Cognitive tools shape thought: diagrams in design

Nickerson, Jeffrey V.; Corter, James E.; Tversky, Barbara; Rho, Yun Jin; Zahner, Doris; Yu, Lixiu

doi:10.1007/s10339-013-0547-3

Cited by 18 publications

(15 citation statements)

References 56 publications

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“…Diagrams of complex information use marks and place on the page to convey information effectively (e.g., Tversky, 2011;Nickerson, Corter, Tversky, Rho, Zahner & Yu, 2013). Such diagrams are meant to spur a wide range of conclusions, inferences, and hypotheses.…”

Section: Discussionmentioning

confidence: 99%

People, Place, and Time: Inferences from Diagrams

Tversky

Gao

Corter

et al. 2016

Lecture Notes in Computer Science

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Keeping track of things as they move in space and time is a task common to scientists, marketers, spies, coaches, and more. Visualizations of complex information aid drawing inferences and conclusions but there are many ways to represent data. Here we show that the kinds of inferences people draw depend on the kind of visualization, boxes in tables or lines in graphs. Lines link and boxes contain; they both direct attention and create meaning.

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Section: Discussionmentioning

confidence: 99%

People, Place, and Time: Inferences from Diagrams

Tversky

Gao

Corter

et al. 2016

Lecture Notes in Computer Science

Self Cite

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“…Recent research developed a number of approaches to analyse design based on semantic networks (Yamamoto et al, 2009;Georgiev et al, 2010;Georgiev and Georgiev 2018). Semantic-based graphs are used to quantify the collective wisdom in a design class (Nickerson et al, 2013). Semantic-based algorithmic methods have been used to score creativity-related divergent thinking (Beketayev and Runco 2016).…”

Section: Semantic Analysis With Semantic Networkmentioning

confidence: 99%

Semantic Analysis Approach to Studying Design Problem Solving

Georgiev

2019

Proc. Int. Conf. Eng. Des.

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To objectively and quantitatively study transcribed protocols of design problem solving conversations, we propose a semantic analysis approach based on dynamic semantic networks of nouns constructed with WordNet 3.1 lexical database. We examined the applicability of the semantic approach focused on a dynamic evaluation of the design problem solving process in educational settings. Using a case of real- world design problem-solving conversations, we show that the approach is able to determine the time dynamics of semantic factors such as level of abstraction, polysemy or information content, and quantify convergence/divergence of semantic similarity in design conversations between students, instructors and real clients. The approach can also be used to evaluate the aforementioned semantic factors for successful and unsuccessful ideas generated in the process of design problem solving, or to assess the effect of external feedback on the developed design solution. The proposed semantic analysis approach allows fast computation of the semantic factors in real time thereby demavonstrating a potential for both monitoring and support of the design problem solving process.

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“…Well-designed diagrams can be a powerful means of visually communicating information about complex problem situations that can be difficult for most people to understand (Joffe andMindell 2006, Parsons andSedig 2014). Good visual designs make use of humans' inherent and highly developed spatial reasoning skills to reduce the cognitive effort of understanding a concept or set of relationships (Kirsh 2004, Heer and Agrawala 2008, Corter et al 2011, Nickerson et al 2013. For example, we readily understand the meaning of a diagram when the spatial organization on the page matches our nonconscious spatial expectations, e.g., time flows in the direction in which we read text and objects placed higher are larger or more powerful than those below them.…”

Section: Information-rich Diagrams Of the Problem Situationmentioning

confidence: 99%

Improving problem definition and project planning in complex natural resource management problem situations using knowledge brokers and visual design principles

Beratan¹

2019

E&S

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Collaborative adaptive management (CAM) has proved difficult to implement successfully. Insufficient attention to the problem definition process contributes to disappointing outcomes because that step sets the problem-solving approach and the attitudes of key partners. The exploratory problem assessment (EA) approach is a practical and cost-effective way for CAM project managers to learn enough about a problem situation quickly enough to identify critical partners and incorporate their input into problem definition and project planning. EA is a facilitated conceptual modeling approach built around two basic ideas: knowledge-focused facilitation can improve the problem definition process, and information design concepts can assist in building common understandings of complex situations. A facilitator with knowledge-brokering skills gathers and integrates information from people with diverse experiential and technical knowledge of the problem situation. The results are presented as information-rich and readily understandable diagrammatic conceptual models that can function as change theories for project planning. The EA approach and visual design strategy are described, with two illustrative cases showing how the approach can be applied in practice.

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Cognitive tools shape thought: diagrams in design

Cited by 18 publications

References 56 publications

People, Place, and Time: Inferences from Diagrams

People, Place, and Time: Inferences from Diagrams

Semantic Analysis Approach to Studying Design Problem Solving

Improving problem definition and project planning in complex natural resource management problem situations using knowledge brokers and visual design principles

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