Abstract

Information organization and utilization are integral to the design and development of creative ideas. However, navigating this often complex information space can be challenging, even for experienced designers. Therefore, a deep analysis of how expert software designers utilize and organize information is needed to provide qualitative insights into their information organization strategies. To address this, four professionals in the software design and development field were recruited for individual 3-hour design sessions. They were asked to generate ideas for a design challenge (reducing distraction-based pedestrian accidents) using information sheets specifically developed to contain different types of information, as identified by prior work. Results reveal individual differences in information approach and categorization, although these were motivated by similar underlying patterns of evaluating the relevance of the information for its ability to inform the project constraints, resources, or (user) requirements. Designer experience and use of design processes and knowledge transfer tools enhanced their ability to turn information into insights.

1 Introduction

Technological and recent information technology trends such as big data and cloud computing are lowering the barriers to innovation by commoditizing information. Despite these changes, successfully harnessing information to produce actionable design goals remains a challenge. This is because more information does not necessarily lead to better design outcomes. Indeed, too much information can lead to information overload [1]. This is especially true for less experienced designers who run the risk of encountering “design paralysis” when confronted with more information than they necessarily know what to do with [2]. As the potential information space has essentially become infinite, designers are limited by their bounded rationality and may struggle with systematically evaluating which sources of inspiration to attend to during the design decision-making process.

In addition to the availability of information, certain information characteristics, dimensions, and forms have also been shown to play a vital role in the design process. For example, design teams have been shown to focus on the end goals of the project [3] and engineering designers engage in abstract levels of information processing as a way to facilitate their solution development strategies [4]. The use of examples has also been found to be a staple activity for software and product designers and is often utilized throughout the design process for multiple reasons, such as evaluating essential and desirable features from similar solutions [5]. However, research also cautions against the use of examples, as they increase the chance of the designer becoming fixated. Fixation was originally defined as “a blind adherence to a set of ideas or concepts limiting the output of conceptual design” [6]. While design fixation reduces the creativity, researchers have also expressed doubt at the perception that design fixation is always a bad thing, noting that fixation might be observed at one level while creativity is observed at another [7]. Designers must manage the tension between utilizing rich inspiration sources while carefully controlling the exploration of the solution space. This requires a combination of sophisticated information organization strategies and design process knowledge. As such, research that critically explores the influence of information during the design process can help the design discipline respond to this tension and can contribute to our understanding of how to effectively support design activity. Therefore, this study seeks to understand the strategies that expert software designers use to organize relevant design information during a design task. This is achieved through a detailed analysis of the behaviors of expert user-experience designers in the context of understanding, structuring, and responding to information early in the design process. The findings indicate that software designers purposefully move through information by restructuring it according to its perceived purpose in the design process. The designers also highlight the use of knowledge transfer tools to facilitate information usage across time and projects. The theoretical basis, methodology, and analysis are discussed in detail in this paper.

1.1 Design Cognition.

Theoretical models of creative cognition have explored the factors influencing design practice and developed models to represent the design process [8,9]. Research in this space has shown that design cognition relies on a combination of domain knowledge, or expertise [10], and effective application of required processes [11]. This can be done through the use of knowledge structures, which are thought to consist of knowledge that is schematic, associational, or case-based. Schematic knowledge is semantic in nature, based on concepts and principles abstracted from past experiences (e.g., birds fly and have feathers), associational knowledge contains associated concepts (e.g., early morning is associated with bird song) while case-based knowledge contains contextual information to guide behavior in similar situations (e.g., goals, key actions, outcomes, contingencies, restrictions, and potential opportunities) [12]. These knowledge structures have been linked to the generation of creative ideas, although there does not appear to be one ideal knowledge structure for idea generation. Prompting a single knowledge structure was found to generate more high-quality ideas, but prompting multiple knowledge structures was related to more high-quality and more original ideas for Psychology undergraduates [12]. While specific to psychology students, this result indicates that employing multiple knowledge structures may play a role in addressing complex problems such as those found in design. In addition, the designers’ ability to reorganize their own knowledge basis was found to be related to more innovative ideas [13], indicating a potential benefit of self-awareness and metacognition in building design expertise.

These knowledge structures are also influenced by expertise. Experts are known to be able to handle more information than novices [14], a finding often attributed to their ability to chunk information in their domain of expertise [15]. Additionally, the application of relevant processes also plays a role in successful problem-solving in design. Although novices initially approach problems using a basic surface-level structure, when they were trained in relevant problem-solving principles they were able to approach problems more similarly to experts. This provides support for a shift in people’s knowledge base as these become richer with experience [16]. Many of such similar factors have been formalized into a process like the Design Thinking methodology [2] or through a set of design principles which may or may not be explicitly codified [17]. Indeed, “it is not simply general abilities, such as memory or intelligence, nor the use of general strategies that differentiate experts from novices. Instead, experts have acquired extensive knowledge that affects what they notice and how they organize, represent, and interpret information in their environment. This, in turn, affects their abilities to remember, reason, and solve problems [18]. Therefore, it is expected that expert designers will display an advantage in structuring information over novice designers, the exact nature of which is the purpose of this study.

1.2 Information Structuring.

Information plays a major role throughout the design process. While the specific information required may vary according to a variety of factors [19], engineering designers have had to develop numerous routes and strategies to acquire the necessary key information [20]. With the rise of big data, the increase in the availability of information has gone hand in hand with increasing information variety, velocity, value, and complexity [21]. This has implications for the designers’ ability to subsequently utilize this information, as design rationale is “often inferred from available information, rather than stored and looked up en masse” [22]. Therefore, the value that information brings to the design process depends on many factors, including the characteristics of the information itself and how the designer subsequently utilizes that information [23]. Knowledge on how these information characteristics interact with each other to influence the design process is critical but understanding what these factors are is complicated due to the dispersed literature on this topic. Research is spread across various disciplines such as operational research [24], business [25], information science [26], engineering [27], and marketing [28]. To address this issue, prior work has begun the development of a typological framework for characterizing design information [29]. The following sections discuss the initial development of the Information Archetypes Framework.

1.3 Understanding Design Information Through Dimensions and Archetypes.

The previous sections highlight the need for a systematic investigation of the relationship between information types and the design process. One way to support this is by following a typological approach to building theory, as outlined by Ref. [30], and has been applied in other fields such as organizational science and social psychology (see Refs. [3134]). According to this approach, a theoretical understanding of applied phenomena can be captured through the development of dimensions and archetypes. First, dimensions are developed in order to capture specific aspects of an entity. Then, more complex phenomena are understood as unique combinations of multiple dimensions that describe sets of ideal types, also known as Archetypes. A deeper understanding of the observed space is obtained through the process of developing these archetypes.

Closely following this approach, prior work has begun the development of the Information Archetypes Framework by classifying information used during design decision-making in an open-source context [29]. This work was focused on understanding the types of information used by designers based on a subset of interview and focus group data from a larger field study conducted over a five-year period. This resulted in the discovery of several information dimensions through a series of discussions, preliminary analysis of the transcribed interviews, reflective experiences gained during the field study, and review of related work. These information dimensions were then refined using a rigorous coding process conducted on the interview transcripts, following the principles of deductive content analysis [35]. The resulting findings were incorporated into a preliminary framework consisting of five main information dimensions with each two corresponded levels. The details of each dimension [29] can be found in Table 1.

Table 1

Overview of the five main information dimensions and their sublevels [29]

DimensionsLevelsDefinitions
Source:
Where information originates from
InternalWithin the individual, team, or organization
ExternalOutside the individual, team, or organization
Abstraction:
Level of detail in
the information
AbstractVague, conceptual
ConcreteDetailed, descriptive, and relates to specific events
Generality:
How generalizable information is across domains
Cross-cuttingCan be widely generalized across various design domains
Domain SpecificIs exclusive within one domain of design
Effectuation: Approach taken when presented a design problemEffectualCreating a design with available resources in mind
CausalCreating a design with an end goal in mind
Representation:
How information is delivered to designers
AsynchronousCommunication not in person or real time
SynchronousCommunication in person or in real time
DimensionsLevelsDefinitions
Source:
Where information originates from
InternalWithin the individual, team, or organization
ExternalOutside the individual, team, or organization
Abstraction:
Level of detail in
the information
AbstractVague, conceptual
ConcreteDetailed, descriptive, and relates to specific events
Generality:
How generalizable information is across domains
Cross-cuttingCan be widely generalized across various design domains
Domain SpecificIs exclusive within one domain of design
Effectuation: Approach taken when presented a design problemEffectualCreating a design with available resources in mind
CausalCreating a design with an end goal in mind
Representation:
How information is delivered to designers
AsynchronousCommunication not in person or real time
SynchronousCommunication in person or in real time

This initial framework provides a basis to build theory around the use of information in the design process and enables researchers to empirically test the impact of specific types of information on design outcomes. As this is a preliminary framework, further empirical validation is necessary to advance its predictive and explanatory capabilities. This study uses this framework as a basis for investigating how designers use and structure information in the early phases of the design process. The goal of this study is to understand the information-structuring behaviors of expert software designers when presented with relevant design information. The aim of this work is not to validate this framework, but rather using the information dimensions as a basis for generating relevant design information to be used during this study. A detailed and systematic investigation into expert designers’ strategies, reasoning, and methods for engaging with large volumes of relevant information early in the design process will provide insights into the cognitive processes employed to make sense of this complex space [36]. Sec 1.4 presents the main goal of this research in response to this need.

1.4 Research Objectives.

The previous sections highlight the role and importance of information on the creative outcomes of the design process. While it is clear that information can shape decision-making, it is less clear how the characteristics of said information might impact designer behavior and cognition. Research on the information processing strategies of designers is needed to extend the existing body of work on the design process. Furthermore, research conducted with practicing designers will shed light on the complex processes employed in the field and add to our understanding of how experts have learned to engage with this information during design. Therefore, this work is guided by the following main research objective:

Understand the strategies used by expert designers to organize relevant design information during an early-phase design task.

Designers are known to draw upon various forms of information during a design task such as exemplars [5] and user requirements [37]. However, not all information is equally important to the design process. It is important to carefully examine the types of information being utilized during the design process to ensure that new design practices and approaches enhance, not undermine, the creative process. Therefore, investigating the ways in which designers organize and make sense of the available design information will shed light on the ways in which the use of information influences the (early phase) design process. This study focuses on increasing the understanding of both designers’ reasoning process of developing organization strategies and the resulting scheme for organizing information to address the conceptual phases of a design task.

Specifically, this research goal will be addressed by analyzing (1) how designers visually organize relevant information prior to idea generation, (2) what designers’ reasoning process for developing organizational strategies are, and (3) how designers typically engage with and structure information in their everyday practice.

2 Methodology

An in-depth qualitative study was conducted with a total of four expert designers. All these designers practice design, carry between 3 and 8 years of experience, and were employed by small to medium software design and development companies in the US midwestern metropolitan area (see Table 2 for relevant participant characteristics). All participants were identified through the authors’ professional networks and snowball sampling. Only designers who had obtained at least 3 years of software design experience (through educational training, certification, or job training) and currently engage in design activities as their primary function in their full-time jobs was recruited for this study. To reduce domain as a confounding factor, only software designers were included in this iteration of the study. It must be noted that while all participants currently work in the software development field, they received training in a variety of other fields, such as Nanotechnology, Psychology, Graphic Design, and IT Innovation. While this study investigates the underlying information-structuring strategies of design experts, it only serves as a starting point, and generalizability to other domains of design is beyond the scope of this paper.

Table 2

Relevant characteristics of the designers

Participant numberDesign experiencePosition title and time in positionOrganization size and sectorTypical work activities
D18 YearsUser-experience lead, 2 years 11 months∼51–200, mobile development and integrationLead the design of online banking applications for mobile platforms through research, user flows, user personas, journey maps, and design reviews
D27 YearsProduct designer, 6 months∼51–200, managed hosting and web designImprove and expand website designs through research, user interviews, and low- to high-fidelity mock-ups
D33 YearsCTO, 9 months∼1–50, custom software development and designOversee and conduct design and development of mobile applications and websites through research, wireframes, and design implementation
D46 YearsFounder and CEO 2 years 4 months∼1–50, custom software development and designDevelop business strategies and plans for the design and development of mobile applications and websites through research and client interviews
Participant numberDesign experiencePosition title and time in positionOrganization size and sectorTypical work activities
D18 YearsUser-experience lead, 2 years 11 months∼51–200, mobile development and integrationLead the design of online banking applications for mobile platforms through research, user flows, user personas, journey maps, and design reviews
D27 YearsProduct designer, 6 months∼51–200, managed hosting and web designImprove and expand website designs through research, user interviews, and low- to high-fidelity mock-ups
D33 YearsCTO, 9 months∼1–50, custom software development and designOversee and conduct design and development of mobile applications and websites through research, wireframes, and design implementation
D46 YearsFounder and CEO 2 years 4 months∼1–50, custom software development and designDevelop business strategies and plans for the design and development of mobile applications and websites through research and client interviews

Despite the small sample size of participants in this study, purposeful sampling and deep analysis of expert behaviors in the context of interest are an effective method for studying thinking styles and knowledge representation. While the power of probability sampling is to select a “truly random and statistically representative sample that will permit confident generalization from the sample to a larger population” [31], the focus of purposeful sampling is to select information-rich cases for in-depth study, in order to gain great insight into issues of central importance to the research [38]. In this work, we employ the method of Intensity Sampling, whereby specific cases (expert designers) are chosen that intensely manifest the phenomenon of interest (information utilization and structuring as a routine practice) [38]. Rather than extreme or unusual cases, excellent and prototypical examples of the phenomenon of interest are used to gain a deeper understanding of the practice of design. This method of sampling and analysis has been used in numerous studies in cognitive science [36,39,40] and engineering [41] to uncover valuable insights into complex phenomena and human experience through a detailed analysis of in-depth protocol studies on behavioral patterns, performance, and reflections. In this case, the designers spend a good proportion of their work on acquiring, filtering, and organizing information from various sources to incorporate into the design artifact.

2.1 Procedure.

The designers were invited to attend 2–3 h of individual design sessions in a quiet and controlled environment, for which they were compensated with a 100 USD Amazon gift card. During these sessions, they were asked to engage with a hypothetical design challenge using information sheets provided to them. An overview of the study procedure can be found in Fig. 1, and the following sections present each phase of the study in detail.

Fig. 1
Overview of the study procedure
Fig. 1
Overview of the study procedure
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2.1.1 Introduction and Training Phase.

After a brief introduction to the purpose and procedures of the study, informed consent was obtained from all designers. Then, designers were briefed on the training task to be completed before other design activities. The training phase utilized 12 cards from the visual perception card game “SET”.2 These cards were chosen because each card always has a unique combination of four features: Symbols (oval, squiggle, or diamond), Colors (red, green, or purple), Number of shapes (one, two, or three), and Shading of the shape (solid, striped, or empty). As such, the SET cards represented an abstraction of the ways that entities, such as design information, can vary and be grouped with one another. The purpose of this training session was to allow the designers to practice thinking about design information by their characteristics (symbols, colors, numbers, and shading) and how they can be grouped using common traits to form archetypes. It was important that designers practiced this form of archetype grouping removed from the context of any design information to minimize any training effects in this study. During this training phase, no details of the design challenge and relevant information were provided, nor was there any explicit link made between actual information and the SET cards. All designers were provided with the same 12 cards (Fig. 2) in a randomly shuffled stack, and they were asked to organize the cards in any way that made sense to them by laying the cards out on a whiteboard and drawing their organization with a whiteboard marker. These specific cards were selected because there is no perfect way to categorize all of them due to the amount of overlap between the cards. Thus, they reflect the unstructured and nature of information. The designers were asked to use any organizational scheme, annotations, and reasoning that they wanted to and were asked to complete the task while thinking aloud and verbalizing their thought process.

Fig. 2
12 Set cards presented to each designer
Fig. 2
12 Set cards presented to each designer
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2.1.2 The Design Challenge and Information Sheets.

After the designers completed the training phase, they were introduced to the design challenge of developing solutions for reducing pedestrian accident rates. The problem itself was intentionally kept open-ended so that the participants were not limited to phone applications or system-level designs, but could generate any ideas they wanted regardless of the complexity or scope. The design prompt was: “Your task is to develop concepts for a new, innovative product or system that will reduce pedestrian accident rates due to distraction from mobile devices.” To account for time constraints and equal familiarity to all participants, the problem centered around the city the designers live in and was presented through a written design prompt that described the motivation and background behind the problem domain. While the emotional connection or personal interest in the problem was not measured, all the designers acknowledged the importance of addressing the design problem at some point during the study, indicating a base level of shared ownership over the problem.

Once this task was understood and any questions were answered, the designers were provided with 15 min to familiarize themselves with 16 design information sheets (Table 3). The researchers specifically developed and pilot-tested the design information sheets to represent the range of information typically used by designers to address a design problem. This was based on the framework described in Sec. 1.3 (see Ref. [29] for related work that forms the basis of the types of information found in this study).

Table 3

The information dimensions and titles of each corresponding information sheet

DimensionSublevelTitle of design information sheets
SourceInternalExpected time to completeCompany culture
ExternalPhone usage in trafficGeneral smart phone usage
GeneralityDomain SpecificAbout OmahaDistracted driving
Cross-cuttingCauses of distractionHearing and vision
AbstractionConcreteFrequency and time of accidentsWearable technology & smartphone functionality
AbstractNon-driver related causes to car accidentsBehavioral change programs
EffectuationEffectualAvailable university departmentsAvailable company resources
CausalCity requirementsDangerous driving
DimensionSublevelTitle of design information sheets
SourceInternalExpected time to completeCompany culture
ExternalPhone usage in trafficGeneral smart phone usage
GeneralityDomain SpecificAbout OmahaDistracted driving
Cross-cuttingCauses of distractionHearing and vision
AbstractionConcreteFrequency and time of accidentsWearable technology & smartphone functionality
AbstractNon-driver related causes to car accidentsBehavioral change programs
EffectuationEffectualAvailable university departmentsAvailable company resources
CausalCity requirementsDangerous driving

In total, only four information dimensions were used for this study. The fifth dimension, Representation of Information, was not included in these information sheets since the form in which information is presented cannot be studied through an artificial research setting (i.e., by nature of the study, all information was asynchronous). Two information sheets were developed for each sublevel of the remaining four dimensions, resulting in the creation of 16 information sheets (four dimensions × two levels × two sheets) for this study (Table 3).

For example, four information sheets were created for the dimension “Abstraction of information”; two containing more abstract information (i.e., information about the use of behavioral change programs to influence behavior), and two containing detailed information about the hypothetical design task (i.e., information on the frequency and time of accidents). These information sheets were developed through a rigorous iterative process to ensure that each information sheet contained similar amounts of information, were roughly equivalent in length (∼200 words each), and had minimal overlap with other information dimensions. For example, the concrete information sheet provides specific numbers about the “Frequency and time of accidents,” such as “on average there is one car crash every 15 minutes,” while the Abstract information sheet describes these “Non-driver related causes to car accidents” more vaguely “The physical condition of the roadway can also play a significant role in causing a car accident.” The full list of information sheets used for this study can be found online.3 During this stage, the designers were explicitly instructed to not yet start ideation instead to focus on the understanding each of the provided information sheets.

Next, similar to the SET task, the designers were asked to organize these information sheets in a way that made sense to them using any organizational schemes, annotations, and reasoning that they wanted to while verbalizing their thought process and using the whiteboard and marker to visualize it.

Once the designers had completed their organization of the sheets of information, they were asked to provide a high-level explanation and overview of the reasoning behind the organizational scheme to the researchers.

2.1.3 Idea Generation.

Once the designers had explained their organization of the information sheets, they were given 20 min for idea generation. To reduce pressure on the designer, the researchers physically left the room during this time and they were free to brainstorm as many ideas as they could address the design challenge. Once 20 min had passed, the researchers reentered the study room and asked the designers to explain their ideas and describe how they were related to the provided information sheets. For this paper, the focus was on the way that designers’ approach and interact with design information, thus the generated ideas and any relationships with those were not further considered.

2.1.4 Interview About Information Organization Experience.

Lastly, a semi-structured interview was conducted to better understand how designers build a conceptual map of the design problem and information typically used during this stage. The following questions were asked during this interview:

  1. Describe your general process of gathering information to help you solve a design problem.

  2. How do you organize or group this information during this process?

  3. How do you typically filter and use information to make design decisions?

  4. What do you typically base your design decisions on?

  5. To what extent does the availability of different types of information have an influence on your design process?

  6. Think about the information provided to you during the study. How similar were these to information you would normally gather during your design process?

  7. Were you missing information to solve the challenge, if so, what information would you have liked to see?

  8. What does your ideal design process look like compared to what typically happens at your work?

3 Qualitative Coding Analysis and Results

In order to understand how designers organize information, a similar process was followed for collecting and analyzing the 12 SET cards and the 16 design information sheets. In both cases, the designer was provided with their materials and asked to organize it by drawing on a whiteboard while thinking aloud, and then explain their organization to the researchers when they were done. This process was videotaped and audio-recorded, and their final output was photographed before being digitally recreated (Tables 4 and 5) to increase readability but otherwise remained unaltered. The videotaped process was analyzed to better understand their visual organization and to extract the thinking patterns and organizational strategies employed by the designers. The interviews were transcribed and analyzed for reoccurring patterns and themes using the inductive content analysis. During the analysis, the material was analyzed with the following questions in mind: (1) How do designers visualize their organization? (2W what do they say their organizational strategies are? and (3) How do they typically organize design information in their everyday practice? The resulting patterns that emerged from these analyses are presented through the lens of these questions. They are detailed in the following sections in the order of the tasks completed by the designers in this study.

Table 4

Organization of the 12 set cards by the designers

Table 5

Organization of the design information sheets by the designers

3.1 Results of Card-Organizing Task.

An overview of the final visual organizations created by the designers can be found in Table 4. While all four designers had unique approaches, two preliminary patterns started to emerge:

3.1.1 Approaching the Problem by Understanding the Space.

Three designers began by laying out all 12 cards on the table so that they could get an overview of what they were working with. These designers did not begin categorizing cards until they had viewed all 12 cards on the table, similar to the practice of understanding the problem space before beginning design activities. In contrast, one designer started categorizing cards as soon as they drew them from the stack while noting its features. As more cards (i.e., information) were revealed this designer dynamically adjusted their organization scheme by expanding, collapsing, and modifying categories.

3.1.2 Dynamically Generated Groups Versus Pre-conceptualized Categories.

Eventually, half of the designers chose a top-down approach (designers D1 and D3, (Table 4)), in which they conceptualized a table or grid that incorporated all the existing card features along its axes, and cards were placed into their spot in accordance with their features. Designers who used this approach first identified the characteristics of the cards that distinguished them from others (e.g., color and shape) to enable logical categorization. This approach generated “gaps” in the organizational table because not all cells in the table could be filled by the available cards. Interestingly, both designers who chose this approach also showed how their “completed” grid would look if more cards had been available. For D1 that meant filling up the grid with colors of the cards that would go there, while D3 illustrated their expected shading sequence.

In contrast, the two other designers opted for a bottom-up approach (D2 and D4, (Table 4)), in which they dynamically added groups and subgroups of shared characteristics as card features became apparent to them. Designers who used this approach analyzed each card separately and then used the cards’ characteristics to draw similarities with existing groups that were already created or made new groups if the card was sufficiently unique compared to existing cards. Using this approach, cards were placed in groups that often shared more than one characteristic (e.g., D2 created a group of one, diamond shapes but different colors and shading) since the focus was on generating groups which consisted of both high within-group similarity and high between-group difference.

While both approaches resulted in nested groups, the top-down approach revealed gaps or missing cards while the bottom-up approach highlighted the existing relationships between sets of card features as they organically emerged, without emphasis on exhaustive categorization or mutually exclusive groups.

3.2 Results of Design Information Organizing Task.

A similar approach was taken for analyzing designers’ behavior while organizing the provided design information sheets, resulting in several preliminary patterns. An overview of the resulting visual organization can be found in Table 5.

While all participants were given 15 min to review each information piece individually, several metrics were computed to provide an indication of the range of participants’ behavior during the information-structuring activity in this study. It should be noted that the protocol was administered in a semi-structured manner to facilitate an organic approach to the problem, and thus, participants frequently paused their information-structuring activities to discuss their results and thought process with the researcher. In addition, participants routinely changed the organization of the information pieces during their explanation of the structure to the researcher. These behaviors do not allow for systematic protocol analysis of participants’ activities, but these metrics provide a high-level indication of participants’ behaviors during the study (Table 6).

Table 6

High-level summary metrics of the participants’ behaviors during the information-structuring activity

D1D2D3D4
Total time (in minutes) spent organizing and explaining their information structure248138
Number of groups5 (+3 “wishlist” groups they added themselves)557
Range of number of cards in each group (minimum–maximum number of cards)2–42–42–51–5
D1D2D3D4
Total time (in minutes) spent organizing and explaining their information structure248138
Number of groups5 (+3 “wishlist” groups they added themselves)557
Range of number of cards in each group (minimum–maximum number of cards)2–42–42–51–5

3.2.1 Visual Organizational Scheme.

Designers found it difficult to inhibit organizing the provided design information sheets while they were familiarizing themselves with the relevant information. Two designers already began organizing the information sheets while they were reading them, and the third designer reported that they had consciously stopped themselves from doing so.

Overall, all designers shared a similar initial approach of placing the information sheets in dynamically created categories, after which they further adapted it to fit their individual needs. However, while this resulted in two tabular structures with the SET cards, the organizational schemes of the information sheets were all group-based. Visually D1 and D2 might appear to follow the tabular arrangement, but there are no “rows” that go with the “columns” that resulted from them placing their groups next to each other and drawing vertical lines between them to mark which cards belong to which group. Typically, the designers grouped the 16 information sheets into five categories consisting of between two and five information sheets, as best exemplified by D2 (Table 6).

After this shared “baseline,” each designer personalized their outputs. Most notably, D4 deviated from this by having seven groups, including one with a single card (“Available university departments”) in the category named “Client,” despite the design brief not explicitly stating a client. While D1 and D2 shared a tabular structure, both D3 and D4 needed more dimensions to accommodate the relationships they had drawn between the information sheets. For instance, D3 created subscales within some groups to represent the internal structure of the group, while D4 created subgroups (“Dangerous driving” within “Driving”) and an overlapping group (“Distraction”). In addition, D4 also represented relationships between the different groups using arrows to indicate how, for example, “Generic information” would inform the “Requirements,” which in turn would inform the “Client,” who also had a direct bidirectional relationship with “Generic information” (see D4 in Table 5 and Fig. 3).

Fig. 3
D4 Grouping information sheets
Fig. 3
D4 Grouping information sheets
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3.2.2 The Use of Goals, Constraints, and Resources.

All four designers sought to organize information according to their perceived purpose in the project. These evaluative factors were similar across designers, in the sense that all designers highlighted the importance of identifying and leveraging project requirements (or goals), constraints (or limitations), and capabilities (or resources). Together, these factors shaped the designers’ understanding of the project scope and problem–solution space. This enabled the designers to create a high-level distinction between information that was directly related or relevant to the problem and information that was nice to know but not critical to the problem. In addition to the specific categories in which they group information, D1 also circled in red “what are essentially requirements, resources and limitations,” which they see as belonging to their own category that is “very specific to this project” while “everything else is kinda its own general information category.” For the other designers too, this focus on goals, constraints, and resources would not have been discernable from the category names alone, as these would, at first glance, appear to be content-based. Instead, these became apparent as designers explained their organization to the researchers. This is best illustrated by the creation of a “background research” category by three designers, which framed the problem–solution space differently depending on how the designer used it. For example, D2 used this background information as a way to, in their words, “set the scene” for the project, while D3 and D4 considered their background category more as a way to capture the capabilities and constraints of the humans and technology involved in the project.

While designers relied on similar categories, they often placed the same information sheet in different categories. For example, D2 mentioned that information about the hypothetical company was something that they would keep in the back of their mind but not something that they considered as relevant as some of the other information. In contrast, D4 considered this hypothetical company information to be crucial in determining what solutions they could (not) develop.

Additionally, designers often designated information as having multiple purposes, for example informing “both resources and requirements” (D3), or “acting as both capabilities (if coming from the designers’ company) and constraints (if coming from the client company) to their potential solution(s)” (D4). D4 reflects that this might be influenced by their personal experience, as “my brain immediately goes into thinking about requirements and capabilities because that’s what I manage on a regular basis.” The next three sections discuss these evaluative factors (goals, constraints, and resources) and their role in shaping designers’ approach to solving the problem in more detail.

3.2.3 Utilizing Project Goals to Evaluate Information Relevance.

Project goals were approached as ways to identify the requirements for the project to be considered successful. D4 uses them as reference points: “I usually at some point during the process review the requirements to make sure that we're hitting what they actually asked for.” While for D3, the project goals shape the design in very tangible ways: “Just the general goal of the project affects how we do the design. So, if one project is more about taking in data and then creating a report about it, then that’s going to be a lot more like tables and visualizations and things like that. In one of our other projects we’re taking children through the transplant process and getting them familiar with all the equipment and things like that. Sure, we could have made it black and white and said, ‘this is a breathing tube, and this is how a doctor is going to be putting it into you while you're strapped to a bed’. But that's kind of horrifying! So instead it's more like a gentle cartoony storybook version of that, where it doesn't hold any punches necessarily, but it shows it in a comfortable way so that the kid can get used to it. So, knowing the general purpose inevitably does affect how we design it.”

The guiding role of the design brief was also illustrated by the way that the designers often referred back to the design challenge to guide their focus as they went through the information sheets. While these were initially extracted from the problem brief, other information was used to support and augment the identified goals. D2 explained the need to evaluate the solution based on requirements from different stakeholders: “then evaluating after that based on your requirements and restrictions, that are set by both environment or your company or the end user such as disabilities and things like that, to hone down your final solution into something that fits all of those qualities.”

During the study, it became apparent to all four designers that the information sheets focused more on the driver side, while the design brief leaned more toward pedestrian-oriented solutions. To resolve this apparent discrepancy, two designers created a client and user role even though these were not explicitly provided. D1 designated the city as the client and “people and people’s behavior” as the customer, while D4 considered the university as the client. Where D1 took a broad view of the situation by targeting “the experience of walking around,” D3 and D4 focused primarily on distracted pedestrians. D3 made a conscious effort to focus on pedestrians over distracted drivers based on information in the project brief: “I stuck closely to [the design brief] when they said that they're looking for devices for when students are walking around and they trip and fall and things like that.” This pattern of behavior highlights the importance of the initial framing of the design challenge through the use of the design prompt. Overall, designers considered the importance and utility of each sheet of information through the lens of who they identified as their primary stakeholder, placing more or less importance on different sheets of information depending on its perceived utility. Thus, information sheets provided during this design exploration stage can be understood as dynamic inputs to the design process, sensitive to the context that the designer finds themselves in.

3.2.4 Applying Constraints to Scope and Explore the Problem–Solution Space.

Another group of considerations that designers frequently utilize to structure the information pieces included constraints to the scope of the problem. Designers used constraints as a way to both scope the project and provide an indication on where to direct their attention to find potential solutions to the problem. For D2, this was the category they first started creating: “I started putting things that are constraints to the project, company things like ‘Time to complete’, ‘Company culture’, the budget…”.4 This did not mean that these constrains were considered non-negotiable. D3 asserts that “I would rather not put a time constraint on the usability testing and the user feedback section because it saves a lot more money and time in the long run.”

When reflecting about their work, D1 used constraints as a way to scope the project as well: “we generally like to do an analysis of any limitations because we know the kind of the frame that we can work inside of,” clarifying that “our solution was based on those limitations (…) because it's financial data. There are certain restrictions like legal, or privacy concerns. I think there are limitations within any project. Even if it's not on a high level like, you'll probably find some limitations within some type of feature that you're eventually going to try to release.”

For the design problem in this study, D1 also saw constraints as an opportunity to find inspiration for new solutions: “I’d also like to know general transportation technology information. Whether it’s opportunities or limitations. Maybe there are some things that have been tested but they’re too expensive, or there something out there that we are simply not aware of. It doesn’t have to be directly related but we might be able to borrow facets of it.”

3.2.5 Leveraging Resources to Increase Project Success.

The last group of considerations that designers used to structure information during the design process was capabilities or resources that they might be able to leverage during the project, both during our study and self-reported in their daily practice. While three designers focused on only using the information provided to them in the study, D1 went further by also wanting to consider information that was not directly available to them. Specifically, D1 wanted to use their “Causes/behavioral” and “Causal data” categories to find potential solutions but deemed the provided information sheets to be too general in nature. To express this, they created hypothetical information sheets with topics they would have liked to see (indicated as gray rounded squares in Table 5). These would contain more detailed information, such as the specifics about accidents that happened in that particular city.

D1 also included a “Persona” card, which would contain patterns of characteristics shared between people who have been in the situations described by the project brief. The designer explained that they often employ personas at their company as a tool to turn general information into actionable insights. None of the other designers, who all worked at different companies, mentioned the use of personas. Additionally, D1 observed that the data were skewed toward quantitative data (a sentiment that was echoed by D3), and they expressed a desire to see more qualitative data, preferably from actual users, or in this case, people who had been in the situations as described by the design challenge.

3.3 Results of the Interviews.

The results of the semi-structured interviews at the end of the study provided insights into the findings presented in the previous sections. Emergent patterns from designers’ retrospective reflection of the activity provide a deeper understanding of their information structuring and utilization behaviors during design activities. These patterns are discussed in the following sections.

3.3.1 Offloading Cognition onto External Tools.

All four designers discussed some form of externalizing information during their typical design activities but described different means of doing so. While D1 did not identify a personal organization style, they highlighted the value of a customer journey map. In this designer’s everyday design practice, these maps are generated as quickly and with as many relevant stakeholders as possible so that it can serve as a guiding document throughout the project. D3 also mentioned the use of a collaborative document-editing tool, but they relied more on mentally aggregating relevant information into actionable heuristics. They did the same for the design challenge in this study, stating that they had generated a mental rule that the solution “should be something to make pedestrians run into less things and make it so that people with disabilities can use it.” Both D2 and D4 used lists to organize information. D2 kept more “high-level bulleted lists of the key things about the project that we need to be addressing,” while D4 depended heavily on electronic lists to keep track of all kinds of information.

3.3.2 Determining Design Goals.

All designers stressed the importance of user or customer feedback and usability testing for providing focus and priorities throughout the design process. Additionally, they also highlighted the role of goals, requirements, and constraints as a means for determining the solution space. As D1 puts it “We generally like to do an analysis of any limitations because then we know the frame we can work in.” The process by which designers seek specific information was also influenced by their role in the company. This is best exemplified by D3 and D4, who work in the same company but have different responsibilities. Both designers seek information to gain an understanding of the solution space and consequentially scope of the project. As D3 (similar to D1 and D2, although for different companies) primarily operated in the design stage and secondarily in the development stage, they sought user requirements (through usability testing and user feedback), while D4 appeared to predominately work in the proposal stage that preceded the design stage and thus was more concerned with technological capabilities and client relations.

Procedurally, the information-gathering process for D4 began with reaching out to experts on the topic to acquire know-how and advice on what information is important and where to find it. In addition, they would supplement this with the resources that they found on the internet that fit the requirements. After narrowing down the top three best options, D4 would test each option themselves to determine fit and viability for this project before discussing the direction of the project with the client. In contrast to D4’s solution-oriented process, D3 indicated that their main stakeholder was the customer or end user. When asked about what design decisions are typically based on, D3 responded with “It's pretty much solely from customer feedback and general usability guidelines.” Their objective was to understand people’s needs in order to determine what the core problem was and who the end users were, typically through desk research and in-person interviews. Therefore, they pointed at the use of the project brief and project goals as guiding direction in the very early stages of the project, but then using customer goals to validate and narrow down solutions as the project progresses.

3.3.3 Knowledge Transfer.

The value of expertise was brought up by the designers as valuable for both within in a domain as well as something that carried over between projects. For D1, expertise took the form of a knowledge library and a set of core features required for applications in their domain of expertise: “One of my main specialties is mobile banking. So, there's a lot of core features that you definitely need in a mobile banking app, and we've got a library of competitor analyses in the mobile banking space which is really nice. So, we know all of the major banks and what primary features that they offer. We generally know what you cannot ignore as a mobile banking app when you're putting it out on the market.” In the case of D3 and D4, a prior experience with a client led them to create a template that they required their future clients to fill out prior to the design engagement. This was used to facilitate discussion on the design process, as they had found out that clients often lack knowledge about the design process and the value of usability testing.

3.3.4 Iterative Information Seeking.

Although D3 and D4 preferred to do the bulk of the project design prior to development and make small adjustments while developing, all designers used minimum viable products (MVP) in their design process. D2 used customer information to determine what should be part of each MVP release, while D1 expressed a preference for quickly and frequently building testable prototypes to acquire customer feedback to validate or disprove hypotheses and patterns. This was echoed by D2, who used the usability tests to identify patterns of people struggling with something as the basis of improvement for the next round of testing. D1 summarized their general process of information filtering and management as “We’re expanding out as we’re always trying to learn more as we’re going, but then always going back to the problem we’re actually trying to solve, and how does this new information relate to how we’re approaching the problem.”

4 Discussion

The main purpose of this study was to investigate the strategies used by expert software designers to organize relevant information during a design task. The main findings of this study are as follows:

  • – Regardless of the domain (SET cards versus information sheets), all four designers displayed similar patterns in how they approached and structured information, although their outcomes differed.

  • – Software designers considered the information space either from an organic approach in which categories were dynamically formed as information was encountered, versus a more holistic approach in which the fully available information space was considered before forming categories.

  • – Information was evaluated based on its ability to serve as a project or user requirement, constraint, or resource.

  • – Software designers “scaffold” information by employing knowledge transfer tools such as heuristics, standardized project templates, lists, and journey maps to structure and keep track of complex information within and across projects.

The findings of this study provide further evidence for the importance of goals, constraints, and resources on how designers frame their information organization strategies [42]. Designers use these as means by which they can exercise power in the design process, realize intentions, and accomplish goals [43]. To reduce complexity and cognitive load, designers formulate generic approaches that they can apply across domains and projects. These findings support prior research that showed evidence for the transfer of skills, competencies, principles, and reasoning through generative heritages [44]. While all four software designers observed general design best practices, they augmented these with individual and company experience to create their unique processes. One designer (D3) was found to apply their typical style of reasoning in the design challenge as well, transforming the information provided into explicitly formulated prescriptive design principles [17]. These principles guided the direction of the design task and shaped how they evaluated subsequent information. Another designer (D2) adopted more descriptive design principles [17], using them more as a way to understand the space than to guide action. The use of heuristics has been noted in prior research, which cites the primary purpose of heuristics as a way to move the designer into a more creative mindset in which they can explore the space for potential solutions [36]. These results demonstrate the creation and the use of heuristics in the information-structuring phase prior to idea generation.

4.1 Study Limitations and Future Work.

This study builds on a previous work investigating the types of information that designers use during the design process using reflective interviews [29]. To better understand how designers utilize these different types of information, this study set out to investigate how designers approach, structure, and organize information in a more controlled setting. Doing so simplified the situation to one where the designer was the only person working on the (hypothetical) design challenge, the problem and information were already provided to them, and they did not interact with a client or a user. While this method reduces the effect of potential confounds, it does not accurately reflect everyday design experiences. One notable difference is that this study took place at one moment in time, while knowledge structuring in the real world takes place over a period of several weeks, months, or even years. Additionally, although client tasks may be presented in ways that are similar to the brief in this study, they are also often negotiated through extended dialog with the client, often beyond the bounds of a design brief, which in the context of this study was not possible. In addition, due to the nature of the laboratory study, participants’ personal connection with the problem was not controlled, and more follow-up studies using different types of problems in different contexts are needed to explore the relationship between design problem and information-structuring strategies of designers. Therefore, the results of this study would benefit from supplementation of longitudinal and field data.

Additionally, the information sheets provided to the designers was based on the Typological Framework of Design Information developed in previous work [29], so that they would reflect the types of information designers would typically encounter. Indeed, the framework proved helpful in creating a representative information space, as creating truly mutually exclusive categories of information is not feasible, nor is it representative of information encountered during design practice. Future work could look into expanding the Typological Framework of Design Information by investigating how the framework relates to designers and their daily practice. This would strengthen and extend the practical applicability of the framework beyond theoretical implications. Future work should also analyze the ideas generated by the designers during the ideation phase to identify any transfer of information or expertise during this process.

Furthermore, in order to capture the cognitive processes that are not directly observable in more naturalistic design environments, this study included a training task in the protocol. This training task was aimed at having the designers practice a visualization method that would bring out these cognitive processes, as natural design behavior is usually more concerned with the application of cognitive processes than a systematic reflection on them. Similar to how the text on the information sheets can be categorized into dimensions from the Information Archetype Framework, so can the visual characteristics on the SET cards be categorized into the high-level attributes of symbols, colors, numbers, and shading. As such, the SET cards are similar enough to enable the participants to practice this more reflective thinking, while more abstract information that is sufficiently removed from a design context that it would have limited influence on the actual design task. While both the familiarity with the SET card game and the personal relevance with the design task were not assessed, the participants were free to organize both the SET cards and the information sheets, however they wanted and for as long as they wanted. Future work should explore different paradigms of organizing information, including protocol analysis of design expert behaviors during a longitudinal design task using design tools and methods.

Lastly, the sample size of this study is relatively small. This is a result of the Intensity Sampling method [38], which was purposefully employed to collect detailed insight into expert designers’ strategies, reasoning, and methods for engaging with large volumes of relevant information early in the design process. This targeted, in-depth interaction involved prototypical software designers with at least three years of experience working in the design and development field. As the designers come from only one subdiscipline of design, the findings are not intended to generalize across other design areas. To address this, current efforts are undertaken to incorporate the design cognition of expert designers in other fields, such as web design and development. Additionally, a separate study that specifically looks into the validation of this framework across a large number of designers while capturing meaningful individual differences would also provide insight into how individual behaviors relate to more generalizable patterns.

5 Conclusion

This study provides preliminary support for the existence of shared underlying patterns in how expert designers approach, organize, and utilize information in the early phases of the design process. The designers were found to evaluate the relevance of the information for its ability to inform the project or user requirements, constraints, or resources. Although all designers sought to turn the available data into actionable insight, their differences and experiences led to unique results. These findings contribute to the understanding of how designers navigate complex information to generate creative solutions and highlight the value of design expertise in this process.

Footnotes

4

“Time to complete” and “Company culture” are the titles of two information sheets while the budget was discussed in “Time to complete.”

Acknowledgment

We would like to thank our research group, the BRIDGE lab,5 and our participants for their help in this project.

Funding Data

This material is based upon work supported by the National Science Foundation (NSF, Grant No. 1755864).

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