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While prototypes are critical to the creation of successful products and innovative solutions, building a prototype is characterized by large sunk costs and a plethora of unknowns. The versatility and effectiveness of prototypes paired with the ambiguous nature of developing a prototype can lead to wasted resources. Recent studies support this claim, demonstrating that under certain circumstances, designers often prototype without a clear purpose, building prototypes as a function of the design process rather than as a function of the design. These findings motivated the creation of the Prototyping Canvas, a tool to aid designers in planning for purposeful prototypes by identifying critical assumptions and questions to guide development. Business and engineering design literature influenced the development of the canvas, which was first tested with a client project in the SUTD-MIT International Design Centre (IDC). The feedback and insights from the design team guided revisions to the canvas. The updated canvas was then validated with 55 professionals during a design project sprint. The purpose of this paper is to present the Prototyping Canvas as a valid and effective design tool.
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Cite this article: Lauff, C., Menold, J., Wood, K.L. (2019) ‘Prototyping Canvas: Design Tool for Planning Purposeful
Prototypes’, in Proceedings of the 22nd International Conference on Engineering Design (ICED19), Delft, The
Netherlands, 5-8 August 2019. DOI:10.1017/dsi.2019.162
Lauff, Carlye (1); Menold, Jessica (2); Wood, Kristin L. (1)
1: SUTD-MIT International Design Centre; 2: Pennsylvania State University
While prototypes are critical to the creation of successful products and innovative solutions, building a
prototype is characterized by large sunk costs and a plethora of unknowns. The versatility and
effectiveness of prototypes paired with the ambiguous nature of developing a prototype can lead to
wasted resources. Recent studies support this claim, demonstrating that under certain circumstances,
designers often prototype without a clear purpose, building prototypes as a function of the design process
rather than as a function of the design. These findings motivated the creation of the Prototyping Canvas,
a tool to aid designers in planning for purposeful prototypes by identifying critical assumptions and
questions to guide development. Business and engineering design literature influenced the development
of the canvas, which was first tested with a client project in the SUTD-MIT International Design Centre
(IDC). The feedback and insights from the design team guided revisions to the canvas. The updated
canvas was then validated with 55 professionals during a design project sprint. The purpose of this paper
is to present the Prototyping Canvas as a valid and effective design tool.
Keywords: Design methods, Prototype, Design practice, New product development
Lauff, Carlye Anne
International Design Centre
1.1 Importance of prototyping
Prototyping is an important design activity that can enhance communication (Buchenau and Suri, 2000;
Brandt, 2007), learning (Leifer and Steinert, 2011), and decision making (Kriesi et al., 2016) throughout
the entire design process (Ulrich and Eppinger, 2000; Otto and Wood, 2001; Lauff et al., 2018a). A
prototype refers to both physical and digital representations of a design, regardless of fidelity, that serves to
answer a question or test an assumption (Lauff, 2018; Menold et al., 2018). Prototypes can be classified as
a stage of the design process; they can also be described as a tool to further product development.
Prototypes are essential to all design process models, ranging from waterfall, V-model, to sprint-scrum.
Previous work has highlighted the ability of prototypes to improve students technical understanding of the
design space and help designers uncover unknown unknowns, as well as explore fundamental user
insights (Jensen et al., 2017; Tiong, et al., 2018). Andreasen and Hein (1987), for example, demonstrated
that building prototypes in the early stages of the design process can help students visualize problems and
highlight incorrect design assumptions. Additionally, prototypes have been shown to boost design
performance (Neeley et al., 2013; Dow et al., 2009), influence stakeholder buy in (Greenberg et al., 2013),
supplement designers mental models (Lin and Seepersad, 2007; Lemons et al., 2010), and enhance both
technical and social skills development (Lauff et al., 2018b). Observational and ethnographic work from
the fields of cognitive psychology and sociology further demonstrate the importance of prototypes in
organizations, through their ability to create shared tacit knowledge (Rhinow et al., 2012; Henderson,
1991), enhance stakeholder communication (Star, 2010), and improve design outcomes (Bucciarelli, 2002;
Schrage, 2000).
Prototypes clearly offer a myriad of benefits to both professional designers and students, yet multiple
studies point to students tendency to limit prototyping activities to later stage design during authentic
design challenges (Deineger et al., 2017). Research has also shown that engineering students often have a
narrow perception of prototypes, believing that prototypes are only meant to test functionality of a full-
scale final design (Lauff et al., 2017). Further, while studies underscore the abilities of professional
designers to leverage prototypes more effectively than student designers in many cases, professionals still
face uncertainty (Gerber and Carroll, 2012) and must balance competing demands due to budget and
schedule constraints (Moe et al., 2004). This work is motivated by the belief that prototypes are necessary
tools during the design process, and that both professional and student designers could benefit from
additional guidance in prototype development efforts.
1.2 The need for the prototyping Canvas
To increase the efficiency and effectiveness of prototype practice, researchers have proposed multiple
prototyping methods and strategies from the Prototype for X (PFX) framework (Menold et al., 2017) to a
strategic design prototyping methodology that includes seven prototyping techniques (Camburn et al.,
2015). Please refer to Menolds dissertation for an extensive review of current prototyping strategies
(Menold, 2017), including these additional references (Camburn et al., 2017a; Christie et al., 2012; Hamon,
2017; Moe et al., 2004; Dunlap et al., 2014). Many of these strategies have been tested with student
designers and are helpful in guiding them through prototyping practices, while also teaching fundamental
principles about the importance of prototypes. While these methods and strategies are useful for designers
and are grounded in best practices and empirical studies, research from Menold et al. (2018) demonstrates
that students lacked a fundamental awareness of their own prototyping behaviors, even when prototyping
strategies or methods were introduced through educational modules. In other words, this study found that
while these methods and strategies were beneficial and lead to improved design outcomes, students may
not be aware of these methods, and may be less likely to implement these methods independently during
authentic design challenges (Menold et al., 2018). While previous research has been incredibly valuable
and has empirically validated the utility and effectiveness of prototyping methods and strategies, to date,
researchers have not explored how communication of these methodologies affects their adoption. We
hypothesize that that by building upon past work and improving the delivery modes of prototyping
methods, we can increase their use by practitioners and students. As such, the purpose of this work is to
propose a new prototyping planning tool drawing on the empirical evidence of previous literature, that can
be more readily implemented in design practice.
There are several design tools that have been adopted by universities and corporations and are grounded in
empirical evidence and best practices from literature. Yilmaz, Seifert, and Daly, for example, developed the
77 design heuristic cards (Daly et al., 2012; Yilmez et al., 2016), which have been widely adopted as
simple, yet effective tool during concept generation. Gerber developed Mockups as a tool to teach
prototyping principles and mindsets, while engaging teams at the start of a project (Gerber, 2015). User
journey diagrams, empathy maps, and personas are commonly used tools during the discovery phase of a
project to gain empathy and understanding of the opportunity and users (IDEO, 2015; Camburn et al.,
2017b). The popularity of online platforms that share design tools and methods, like IDEOs Design Kit
(; IDEO, 2015) or Berkeley and MITs Design Exchange (; Roshuni
et al., 2015), points to the utility and need for such design tools.
A common theme amongst these tools is their simplicity; each tool can be easily integrated into existing
design practices increasing the likelihood of their adoption by practitioners, educators, and students. We
argue that while many researchers have identified prototyping best practices, and have empirically
validated these practices with students, findings from research remain difficult to translate to practice due to
the lack of simple and effective design tools for prototyping. In this work, we propose the Prototyping
Canvas, a design tool that effectively guides designers through prototyping processes, facilitates a common
prototyping language amongst team members, and encourages intentional prototyping practice. The
following sections describe the development of the Prototyping Canvas tool, which includes testing its
usefulness during an industry project and then iterating on the tool and testing it again with 55 professionals
during multi-day design innovation project sprints.
2.1 Inspiration from Business Model Canvas
The structure of the Prototyping Canvas was heavily influenced by the success of the Business Model
Canvas (BMC). The Business Model Canvas translates key business activities into a simple, yet effective
tool for companies to rapidly create and validate business models (Osterwalder and Pigneur, 2010). The
BMC is arguably the most recognizable and successful business design tool in use. Strategyzer reports that
in 2015 there were over 5 million downloads of the canvas ( Research has found that
using the BMC leads to shared language amongst teams, better conversations on strategy, more ideas
shared, and a structured plan to implement concepts (Amarsy, 2015). The BMC has been adapted for other
situations, such as the Mission Model Canvas for mission-driven organizations (Blank, 2016) and the Lean
Canvas for start-ups (Maurya, 2010). Likewise, we have evolved the BMC for prototyping during product
development, thus creating the Prototyping Canvas.
2.2 Methodology for development
The main contribution of this paper is the development of the Prototyping Canvas planning tool, which is
grounded in existing evidence and translates validated prototyping methods to practice. The methodology
for developing the Prototyping Canvas is depicted in Figure 1. The process began with a literature review
surveying relevant prototyping literature in engineering design to build a strong evidence base. From these
articles, prototyping strategies, frameworks, and approaches were identified. Findings from research were
used as the building blocks for the content of version 1 (V1) of the Prototyping Canvas, which was then
tested with an industry project in the SUTD-MIT International Design Centre (IDC, Four
professional designers, with industrial design and engineering backgrounds, used the Prototyping Canvas
during this project and provided continuous feedback to improve the tool. From their feedback, version 2
(V2) of the Prototyping Canvas was developed. Then, the revised V2 canvas was tested with 55
professionals during 2 and 3-day design sprints to validate the usefulness of the canvas. Future research
studies will be conducted to further validate the utility of the Prototyping Canvas. The remainder of this
section details the development and validation of the Prototyping Canvas.
Figure 1. Methodology for developing and revising the prototyping Canvas
Distill Key
Aspects in
Canvas V1
Pilot Test V1
with an Industry
Canvas tool into
Validate V2
usefulness with
55 Professionals
2.3 Synthesizing prototyping literature into Prototyping Canvas V1
The content of the Prototyping Canvas is grounded in empirical evidence from literature. Most notably, the
two dissertations from the co-authors influenced the development of the canvas as they were on the topics
of prototyping in the wild studying companies usage of prototypes throughout the entire design process
(Lauff, 2018), and developing a “prototyping for x” (PFX) framework to prototype creation (Menold,
2017). After surveying literature in the field of engineering design, three principles were identified as
critical to prototyping efforts: identifying the (1) purpose of the prototype, (2) resources to build the
prototype, and (3) strategy to execute building and testing the prototype. The literature related to each of
these principles is listed below, and exemplars of each principle are described in Table 1.
Purpose: All prototypes should answer a question, and thus have a purpose for the prototype
development. One must identify assumptions and questions that motivate the need to build and test a
prototype. This was based on the following literature: (Lauff, 2018; Lauff et al., 2018a; Houde and
Hill, 1997; Rhinow et al., 2012; Lande and Leifer, 2009; Deiniger et al., 2017; Ulrich and Eppinger,
2000; Otto and Wood, 2001). On the canvas, this motivates the creation of three categories:
Stakeholders, “Assumptions and Questions” and Critical Assumption/Question.
Resources: When building a prototype, one must take note of all the resources that are available and
sources for these resources, including the materials, time, and cost, to guide development of the
simplest prototype possible. This was based on the following literature: (Yang, 2005; Menold, 2017;
Menold et al., 2017; Thomke, 1998; Dow et al., 2009; Buchenau and Suri, 2000; Gerber and Carroll,
2009; Viswanathan and Linsey, 2011). On the canvas, this motivates the creation of one category:
Resources Available.
Strategy: To prototype effectively, one should formulate a strong plan and approach to building and
testing the prototype. Many strategies aim to minimize the resources used to maximize the desired
outcome. This was based on the following literature: (Menold 2017; Menold et al., 2017; Menold et
al., 2018; Camburn et al., 2015; Camburn et al., 2017a; Christie et al., 2012; Hamon, 2017; Moe et
al., 2004; Dunlap et al., 2014). On the canvas, this motivates the creation of three categories:
“Building Plan”, “Testing Plan”, and Insights.
Table 1. Exemplars of prototyping literature influence on Canvas three principles
Prototyping Insights
from Exemplar Literature
Lauff, 2018; Lauff
et al., 2018a
Prototypes are tools for communication, learning, and decision making.
Prototypes are active objects that impact social situations. Prototypes need
to have an underlying purpose to test assumptions.
Moe et al., 2004;
Camburn et al.,
Moe et al. proposed a method for prescribing a partitioning strategy that is
tailored to the specific characteristics of a project and is based upon the
three components of requirement flexibility: cost, schedule, and
performance. Camburn et al. identified six techniques for prototyping that
can minimize resources used during development: iteration, parallel
concepts, scaling, subsystem isolation, requirement relaxation, and virtual
Menold 2017;
Menold et al.,
2017; Menold
et al., 2018
The Prototype for X (PFX) framework is a strategy that breaks prototyping
efforts into three key phases: (1) Frame, (2) Build, and (3) test. Through
these phases, PFX helps designers develop a strategy to focus resources and
efforts on building prototypes that test core assumptions and lead to deeper
and richer learning about specific aspects of the design, at the time of
The layout of the canvas was influenced by the layout of the Business Model Canvas (Osterwalder and
Pigneur, 2010). A user can fill out the canvas in any order, with the most structured approach starting with
the Stakeholders and Assumptions & Questions, moving left-to-right, until the Insights are
documented. The contents of the Prototyping Canvas are described next.
Stakeholders. Stakeholders refer to all people who have some stake in the project. This can include
end-users, consumers, clients, project managers, investors, manufacturers, or similar. The
stakeholders need to be considered throughout the building and testing of their prototype, especially in
how they will be communicated with using the prototype.
Assumptions & Questions. This section is meant to identify all the assumptions about the problem or
design, along with all questions that are unanswered. There are three sub-categories related to
feasibility, desirability, and viability to encourage deeper thinking about the problem or solution.
Critical Assumption/Question. This section assesses the assumptions and questions listed prior to
determine which is the most critical to the success of the project. This validates why it is necessary to
prototype. The critical assumption/question should guide the prototype development.
Resources Available. Resources refers to materials, money, people, and time collectively. You must
first consider what resources are readily available, and the sources of those resources, followed by
what resources you must obtain, so that the simplest prototype can be built to test the critical
Testing Plan. This section acts as a guide to create a simple, yet comprehensive testing plan for the
prototype. The guiding questions include: How will you test your assumption/question using a
prototype? How will you assess success or failure? What metrics are needed to assess the
performance? How will the stakeholders be impacted? Where, when, and with whom will you test?
Building Plan. This section is used for sketching the intended prototype and documenting a plan
before building and testing occurs. The previous answers to the resources block will guide material
selection, prototype medium, and construction method for the prototype. The goal is to determine the
simplest way to build and test the critical assumption/question, while keeping the relevant
stakeholders in mind.
Insights. The final section is meant for reflections, insights, and documenting any new assumptions
and questions that arose after testing the prototype. The intent is that prototypes are iterative, meaning
there are more assumptions, questions, and unknowns to test. This section may lead to the next
prototype iteration or development of an entirely new concept to prototype.
2.4 Testing of Prototyping Canvas V1
The first version of the Prototyping Canvas was tested with the SUTD-MIT International Design Centre
(IDC) team working on an industry-client project. The IDC team was tasked with designing a launch
mechanism for a large construction kick-off event. There were four professional designers on the project,
and they each used the Prototyping Canvas to guide their prototyping efforts. Before using the canvas, one
of the researchers gave a 20-minute presentation that covered the importance of prototyping in the design
process and walked the designers through the Prototyping Canvas. The team then spent 15-minutes filling
out the canvas in pairs, followed by a larger 30-minute discussion amongst the team. They then spent two
days developing and testing six different parallel prototypes based on the canvas before filling in the final
“Insights” section.
Figure 2. Completed Prototyping Canvas with call-outs (left) and scaled prototype (right)
One completed V1 Prototyping Canvas is shown in Figure 2, alongside images of the tested prototype
entitled Sandcastle. The designers started with the Sandcastle concept, and then used the canvas to
develop a prototyping plan. They documented eight assumptions and questions about the concept and listed
available resources in the IDC to build the prototype. The engineer chose to create a scaled down version of
the Sandcastle to test appeal to the client, the ease of movement of sand, the overall wow factor, and
structural integrity of the system. They built the scaled Sandcastle prototype in less than one day, using
materials and resources in-house. A digital model was created in CAD, acrylic was laser engraved and cut
to size, sand and LED lights were found in the IDC, and the entire structure was assembled. As shown on
the right of Figure 2, a locking mechanism releases sand from the upper reservoir when the acrylic tabs are
pulled, resulting in the IBEW logo in the lower reservoir being filled with sand. This movement of sand
also displays the engraved futuristic city-scape in the upper reservoir, which is illuminated by the LEDs.
New insights arose after testing the prototype, such as what materials would be used in the final version and
how the scaled-up design would support the weight of the sand. These insights were recorded on the canvas
and influenced further prototype development.
The IDC designers completed a survey after they finished using the Prototyping Canvas. This survey
included four 5-point-scale Likert-type questions (1=low, 5=high) and three open-ended questions. The
survey questions, in an abbreviated form, and the summarized results and feedback from the designers are
displayed in Table 2. In addition to the survey, the designers were provided with a blank Prototyping
Canvas and asked to “mark” the canvas with suggestions, noting elements that were confusing, useful, or
needed improvement. Based on feedback from the IDC designers, as shown in Table 2, the research team
summarized seven benefits of using the Prototyping Canvas: 1) provides utility, 2) saves resources, 3)
prepares a plan to build and test, 4) systematic and objective focused, 5) decreases mental burden, 6)
identifies unforeseen issues, and 7) aids in communication amongst the team. Based on the survey, with an
average survey score of 4 on a 5-point-Likert scale, the designers believed that the Prototyping Canvas
provides utility, saves resources, and prepares a plan to build and test. This validates, even in a small
sample size, that the Prototyping Canvas is an effective design tool for planning intentional prototypes.
Additionally, seven suggestions to improve the canvas were captured from the designers feedback: 1)
improve ability to inspire, 2) show more examples of how to use the canvas, 3) add more specifics, like
prototyping strategies and types of materials listed, 4) create a larger format, including more space to
sketch, 5) include a section for how to communicate the prototype to stakeholders, 6) further emphasize
‘simplest’ prototype possible, and 7) improve aesthetics of the canvas. This important feedback guided the
research team in revising the Prototyping Canvas tool into V2.
Table 2. Prototyping Canvas (PC) quantitative and qualitative survey results
Survey Qs
Quant. Results
Qualitative Feedback
How much utility does
PC provide?
Avg: 4/5
Assumptions/questions and critical assumptions were very
helpful and the breakdown was great to guide through that.
How well does PC aid
in saving resources?
Avg: 4/5
Wanted to start ‘fiddling with things’ when it got time to identify
resources and build and test instead of writing them down…”
How prepared for
Avg: 4/5
Emphasize building and testing the simplest prototype possible
even more throughout the canvas, as this is a key takeaway.
How well does PC
inspire you?
Avg: 2.75/5
The current version works well for distinct separate ideas, but its
cumbersome if I just want variants of the same idea.
List 3 things you love
about PC.
stated 3x
Systematic; Objective focused; ensuring the point” of the prototype;
Decrease mental load, structure thoughts; Identify assumptions and
unforeseen issues; define metrics; determine materials/resources
List 3 surprising
aspects of PC.
Reduce mental
burden stated
Simple yet effective; Reduce mental burden; Worked well
discussing in pairs; Thinking about human resources
List 3 ways to improve
aesthetics 3x
Scale to A3; examples; visual/intuitive interface; less text; more
room to sketch; communicate to stakeholders; hard to remember
2.5 Incorporating feedback into Prototyping Canvas V2
The feedback from the IDC team was used to guide revisions to the Prototyping Canvas. The revised
version is shown in Figure 3. To increase the size and spacing, the revised canvas is scaled from A4 to A3,
the text descriptions for the categories were streamlined, and descriptive icons were added to represent the
main goal of each box. Additionally, changes were made to the font, text size, and colour scheme to
improve the overall aesthetics. The research team also launched a free online Design Innovation (DI)
learning module on the Prototyping Canvas ( On this website,
there are guidelines for how to use the canvas, examples working through the canvas, and a free
downloadable canvas for anyone to use.
The content of the canvas changed to include two new categories: 1) Communication Strategy for
Prototype, which lists four types of communication that are often associated with prototyping: explain,
feedback, negotiate, and persuade, and 2) Prototyping Approaches, which lists thirteen prototyping
strategies, including: parallel prototyping, sequential prototyping, sub-system isolation, scaling,
requirements relaxation, remove unessential features, wizard-of-oz, repurpose existing products, experience
prototyping, paper prototyping, role playing, storyboarding, and mockups. The Communication Strategy
section was added so that teams would be more explicit about how the prototype would be used to explain
the concept, gather feedback, negotiate requirements, or persuade stakeholders (Lauff, 2018). The
Prototyping Approaches section was added to directly link validated prototyping strategies and reduce
cognitive load of participants. This section lists thirteen different prototyping strategies, which were
identified from the literature review on prototyping strategies in engineering design (Menold 2017; Menold
et al., 2017; Camburn et al., 2015; Camburn et al., 2017a; Christie et al., 2012; Hamon, 2017; Moe et al.,
2004; Dunlap et al., 2014). The content of both categories was discussed in the presentation given before
the earlier version of the Prototyping Canvas was tested, but they were not explicitly listed on the canvas in
the previous version. Overall, these changes to the Prototyping Canvas directly address the seven areas of
improvement from the designs feedback.
Figure 3. Revised version 2 of Prototyping Canvas, available for download at
2.6 Validating Prototyping Canvas V2
The revised Prototyping Canvas was tested with three groups of professionals over the course of three
different design innovation sprint workshops. The first group had 12 professionals over 3-days, the second
group had 17 professionals over 3-days, and the third group had 27 professionals over 2-days. In each
session, teams were divided by business unit and had between 3 and 7 team members. This totalled 55
engineering and design professionals that engaged in a multi-day design innovation sprint on their own
company challenge. The professionals were from two large organizations, groups one and two were from
the same engineering and defense company and group three was from a telecommunications company.
These professionals were trained in the Design Innovation process over 2 or 3 days, where they actively
engaged in all 4 stages of the process: Discover, Define, Develop, and Deliver on their own company
Build t he sim ple st pro tot ype p ossible (le ast cost, ti me, a nd ma teri als
requi red) t o te st crit ical assum ptio n an d/o r an swer critic al qu estio n.
Expla in
Feed bac k
Neg otia te
Persu ade
About the user a nd thei r nee ds
About the tec hnica l fea sibilit y & fu nctio nal ity
About the cost a nd b usine ss
Wh at d id yo u lea rn? Di d you answ er t he cr itica l assum pt ion/ quest ion?
Assess abo ve list: w ha t is th e m ost crit ica l to t he suc cess of t he pr oject ?
Wh at a re y ou te sting ?
Wh at m et rics ar e ne eded ? Qua lita tive /Qu ant ita tive assessm ent .
Time, P lace , Peop le, & Ma te rials re quir ed t o test
Mat eria ls rea dily a va ilab le or n eede d
Time, M one y, & Peop le Allo tte d
PROBLE M/OP PORTUNI TY__________________________________________ CONC EPT/SOLUTI ON__________________________________________
Para llel P roto typin g Seque ntia l Pro tot yping
Sub-syst em I solat ion Scalin g
Requir eme nts Re laxa tio n Rem ove Un essent ial Feat ures
Wiz ard- of-Oz Repu rpose Ex isting Prod ucts
Experie nce P roto typin g Pap er Pr otot yping
Role Pla ying Storyb oar ding
Mock ups Oth er:___________________________
design challenges (Camburn et al., 2017b). These challenges ranged from designing for autonomous
vehicles to enhancing safety protocol in the field to planning for the future of 5G networks.
The Prototyping Canvas was introduced on the final day of each workshop at the start of the Deliver phase.
The researchers described the canvas and walked through an example with the group before they were
asked to use it for their own projects. The teams then used the Prototyping Canvas to plan for a prototype,
build and test their solution, and reflect on the experience. At the end of the workshop, the teams each
pitched their final prototyped solution. Finally, the 55 professionals completed a survey at the end of the
workshop, after they finished using the Prototyping Canvas. This survey included four 5-point-scale Likert-
type questions (1=high, 5=low) about using the canvas. The summarized questions and results of the
survey are displayed in Figure 4. The first question asked if they learned new prototyping strategies using
the canvas, and the average response was 1.67. The second question asked if the canvas supported
intentional prototyping practices, and the average score was 1.69. The third question asked if the canvas
enhanced team communication, with average score of 1.62. The fourth question asked if the canvas added
value during the Deliver phase of the design process, with an average score of 1.44. Overall, there was a
very positive response to using the canvas, with only six responses as neutral and one response in
disagreement out of 220 total responses (4 questions x 55 people).
Figure 4. Survey responses from 55 professionals after using Prototyping Canvas V2
The revised Prototyping Canvas (Figure 3) will be validated for its usefulness in immediate future studies
with senior capstone Engineering Product Development students working on industry-sponsored projects
and with professional engineers and designers. This future work will focus on answering the following
research questions: 1) Does using the prototyping canvas improve teams’ strategy for prototyping? 2) Does
using the prototyping canvas aid teams in creating more purposeful prototypes? 3) Does using the
prototyping canvas reduce cognitive load on individuals? For each of the research questions, we will
compare individuals and teams using the Prototyping Canvas against individuals and teams who prototype
freely. Answering these questions will extend our understanding of how the Prototyping Canvas affects
individuals and teams and provide more rigorous validation of the tool.
The Prototyping Canvas is a strategic prototyping tool that guides users to build the simplest prototype
possible to answer critical assumptions or questions about their design. This tool was systematically
developed from surveying prototyping literature and distilling three key principles related to prototyping
purpose, resources, and strategy. The layout and structure of the canvas was also inspired by the highly
successful and widely adopted Business Model Canvas. This Prototyping Canvas acts as a roadmap to
guide designers through identifying their assumptions and questions around the desirability, feasibility, and
viability of aspects related to their opportunity or concept; then, the canvas lists all the “key ingredients”
necessary to plan for building that minimal viable prototype, including the resources, strategies, prototyping
principles, and testing plan. Finally, the canvas prompts users to reflect, listing insights and lessons-learned
from the testing of the prototype. The Prototyping Canvas effectively guides designers through creating a
prototyping plan, and it also facilitates a common prototyping language amongst teams. To encourage
purposeful prototyping, the researchers launched a free online Design Innovation (DI) learning module on
Strongly Agree Agree Neutral Disagree Strongly Disagree
Q1: Learn new prototyping strategies
Q2: Supports intentional prototyping practices
Q3: Enhance team communicartion
Q4: Adds value during Deliver phase
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downloadable canvas (
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The team would like to acknowledge the SUTD-MIT International Design Centre (IDC). The IDC design
engineers were critical to the testing and iterations on the Prototyping Canvas. Additionally, many
conversations with other IDC members influenced the direction and evolution of this tool.
... However, Goudswaard et al. (2021a) suggest that prototyping practice could be improved by improving prototyping method selection to ensure the right tool is used at the right time to generate the right knowledge which is of importance as, in particular, novice designers are found to approach prototyping in an ad hoc manner (Petrakis et al. 2021a). This has led to the creation of prototype selection frameworks to guide designers to appropriate approaches for their given scenario (see, e.g., Filippi & Barattin 2012;Menold et al. 2017;Lauff, Menold & Wood 2019). ...
... As such they identify that a prototype is more than the sum of its parts, and plays a broad and critical role in the learning and understanding processes of designers and across design teams. It is therefore critical for researchers to understand how prototyping methods influence the learning they afford it generates such that better tools and methods may be developed and selected by designers (Menold et al. 2017;Lauff et al. 2019). ...
... Through these models and definitions, it is clear that design, and hence prototyping as an activity within it, can be considered as a knowledge generation processa view echoed by many (see Ulrich & Eppinger 2016;Camburn et al. 2017;Lauff et al. 2019;Goudswaard et al. 2021b). Increasing knowledge of the current design representation and comparison against expectation or some predefined ideal supports the next stage of iteration, with type and quality of knowledge generated then impacting the success of the design process. ...
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Prototyping is a knowledge generation activity facilitating improved understanding of problem and solution spaces. This knowledge can be generated across a range of dimensions, termed knowledge dimensions (KDs) , via a range of methods and media, each with their own inherent properties. This article investigates and characterises the relationships between prototypes and knowledge generated from prototyping activities during the design process, by establishing how different methods and media contribute across KDs. In so doing, it provides insights into prototyping activity, as well as affording a means by which prototyping knowledge generation may be studied in detail. The investigation considers sets of prototypes from eight parallel 16-week design projects, with subsequent investigation of the knowledge contributions that each prototype provides and at what stage of the design process. Results showed statistical significance supporting three inferences: i) teams undertaking the same design brief create similar knowledge profiles; ii) prototyping fidelity impacts KD contribution and iii) KDs align with the different phases of the project. This article demonstrates a means to describe and potentially prescribe knowledge generation activities through prototyping. Correspondingly, the article contends that consideration of KDs offers potential to improve aspects of the design process through better prototyping method selection and sequencing.
... Relevant research has emphasised prototyping's cognitive benefits to students, i.e., the reasoning and understanding of a design problem during the early stages, as well as the advantages offered through learning by reflection, learning by thinking and learning by making during prototypingbased exercises [2], [3]. Nevertheless, although prototyping constitutes a major theme of design education, it is still regarded as an underexplored activity which is inadequately understood and implemented by students [4], [5]. Our previous work is built on the importance of prototypes having pre-defined purposes, as an explicit purpose to be achieved by a prototype can ensure higher quality outcomes and better inform decisionmaking. ...
... Relevant research has focused on the development of several tools for assisting students with their prototyping activities. Such means intend to structure prototyping into systematic step-by-step processes and have been introduced in the form of platforms containing photo-or video-based resources [2] or consist of questions which force conscious decision-making and are included in canvases [5] or planning-based templates [6]. However, the recent shift towards online and blended learning environments due to COVID-19 restrictions and globalisation, has raised the need for additional online design tools that can ensure the successful delivery of distributed design activities [7]. ...
... According to Camburn et al. (2017), prototyping should be applied strategically and in a way that is appropriate for a given context. When prototypes are used without a particular purpose or strategy, resources dedicated to prototyping can be perceived as wasted (Lauff, Menold & Wood 2019). Moreover, inadequate prototyping and stakeholder engagement practices can ultimately lead to project failures if quality stakeholder input is not collected and incorporated effectively (Cooper 2019;Hansen & Özkil 2020). ...
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Engineers must engage project stakeholders effectively if stakeholder needs are to be met, and prototypes are key tools for communicating design form and function. Quality stakeholder engagement in the front end of design processes, in particular, is critical in the success or failure of design projects. As remote stakeholder engagement has become increasingly common as industry trends toward distributed design, there is a need to develop the theory and practices behind effective remote design processes, which have not yet been as well-studied as in-person design. This study explored the prototyping strategies for remote stakeholder engagement during front-end design used by 10 engineering practitioners and 10 senior engineering students through semi-structured interviews. Prototyping strategies were found to overlap with many of the strategies described by prior literature that are not specific to remote engagement modes, though several of these strategies were adapted to the remote context, and three emergent strategies for prototyping in remote engagements were identified. Designers’ perceptions of remote versus in-person prototyping strategies for stakeholder engagement in front-end design, including perceived advantages and limitations, were also explored, and recommendations for educators to better prepare engineering students for hybrid and remote work are provided.
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We are on a design journey. Business, education, society, and community are at the center of this journey. In the words of the Prime Minister of Singapore, ‘Singapore is a nation by design. Nothing we have today is natural, or happened by itself... Now, as a first world country, design thinking will be critical for us to transform Singapore again, and to stay an outstanding city in the world. Actually, there are many other policies which will benefit from your design thinking. If you think about it, healthcare, education, CPF, national service and even our political system.’ The ideas expressed by the Prime Minister focus on the design journey, as a concept, known in the popular vernacular as Design Thinking, or, more broadly, what we refer to as Design Innovation. This journey is a vision for the future, no matter what country or community in which we reside. We are facing the grandest of global and national challenges, such as an ageing population, environmental crises, needs for transformation in transportation, smart and loveable cities, threats of terrorism, ethnic and religious tensions, and economic uncertainty. Design Innovation holds an optimism, an ‘Also Can’, and a promise to confront and overcome these challenges. The Design Innovation Methodology handbook represents a contribution to our design journey. This handbook was developed by a number of contributors from the United States and Singapore. Through a co-creation effort and common interests to innovate together, the intent is to make a difference for all persons in our communities and society. Readers are provided with a meaningful and practical guide, reference booklet, and living document in which to engage Design Innovation at the apex of Design Thinking and Systems Thinking, and beyond. Appreciation is conveyed to all of the contributors in developing this handbook. We sincerely hope that this guide will inspire and embolden all readers and partners to push the boundaries of human-centered systems innovation across one’s entire portfolio and strategic plan. In doing so, the future will be bright, and we will have an impact beyond anything we can imagine or foresee. We wish you the very best as you embrace your personal Design Innovation journey. To Design Innovation, and Beyond!!
Using prototypes to engage stakeholders during front-end design activities is crucial for successful design outcomes that are grounded in real stakeholder needs and priorities. Compared to prototyping that is used for iterative refinement during back-end engineering design activities, prototyping that informs problem definition, requirements and specifications development, concept generation, and other front-end design activities is understudied. To identify patterns in prototyping strategies for engaging stakeholders during the design front-end, we conducted semi-structured interviews with 26 design practitioners across three product design domains: automotive, consumer products, and medical devices. Seventeen strategies evident across the collection of practitioners were used in generally consistent ways, with some variation based on context, e.g., project scope, stakeholders engaged, and the stakeholder interaction situation. Twelve out of the 17 strategies were used by industry practitioners across the three domains, and five of the 17 strategies were used by practitioners from the medical device domain and either the automotive or consumer products domain. The descriptions and examples in context of prototyping strategies used to engage stakeholders during front-end design can guide the design strategies of both experienced and novice designers.
This paper presents a process of development and validation of a methodological tool for supporting the co-design of strategic actions to enhance the digital competencies of educators in higher education. Considering that organisational strategy and change are often imperfectly reflected in structural arrangements in higher education institutions, this work proposes a novel approach to address this difficulty. In a four-iteration process with a design-based approach, a team of experts and stakeholders from six European countries has created and validated a CANVAS to design actions for fostering Digital Teaching Competences based on the DigCompEdu framework. The result is a methodological instrument that facilitates co-design across stakeholder groups within higher education institutions. Its goal is to enhance a strategic vision for participatory action by scaffolding institutional development processes, collaboratively defined, for short, medium- and long-term impacts. This work can also be a reference for other systematised innovation design approaches.
Prototyping in New Product Development (NPD) encompasses a broad selection of methods used to generate knowledge about a product or process. Whilst some methods focus on the creation of a prototype in its intended domain, others centre on its testing and evaluation, contributing to an understanding of the prototype’s performance against a set of design requirements or objective. Where prior works have explored the contributions to design knowledge afforded by methods of creation, methods used to evaluate prototypes lack a similar characterisation.
This paper investigates team psychological safety (N = 34 teams) in a synchronous online engineering design class spanning 4 weeks. While work in this field has suggested that psychological safety in virtual teams can facilitate knowledge-sharing, trust among teams, and overall performance, there have been limited investigations of the longitudinal trajectory of psychological safety, when the construct stabilizes in a virtual environment, and what factors impact the building of psychological safety in virtual teams.
With the increasing prevalence of artificial intelligence (AI) agents, the transparency of agents has become vital in addressing interaction issues (e.g., trust, usefulness, and understandability). However, determining the transparency of AI agents requires a systematic consideration of complex related factors, including stakeholders, algorithms, context, etc. Thus, in our study, we presented an overview of studies on the transparency of AI agents through multiple-stage bibliometric analysis, and identified an ontological framework of the key concepts relevant to transparent AI. We then built a Transparent-AI Blueprint prototype which is a diagram that visualizes the ontological framework of design concepts. In the subsequent pilot test, we updated Blueprint to the final version, and validated it in a workshop. Our work structurally summarized the design concepts related to the transparency of AI agents, and proposed a useful and practical conceptual design tool that effectively guides designers to operationalize the transparency of AI agents.
Conference Paper
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Economic use of early stage prototyping is of paramount importance to companies engaged in the development of innovative products, services and systems because it directly impacts their bottom-line [1, 2]. There is likewise a need to understand the dimensions and lenses that make up an economic profile of prototypes. Yet, there is no reliable understanding of how resources expended and views of dimensionality across prototyping translate into value [3, 4]. To help practitioners, designers, and researchers leverage prototyping most economically, we seek to understand the tradeoff between design information gained and the resource expended into prototyping to gain that information [5]. We investigate this topic by conducting an inductive study on industry projects across disciplines and knowledge domains, while collecting and analyzing empirical data on their physical prototyping process [3]. Our research explores ways of quantifying prototyping value and reinforcing the asymptotic relationship between value and fidelity [6]. Most intriguingly, it reveals insightful heuristics that practitioners can exploit to generate high value from low and high fidelity prototypes alike.
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Design has been called one of the defining characteristics of engineering, and it has been long-argued that design is equally social and technical in practice. The field of Science and Technology Studies (STS) has a research tradition of exploring the interwoven social aspects of technical fields like engineering design. We borrow a concept from STS—the notion of intermediary objects—to better understand first-year engineering design teams and explain how prototypes mediate technical skill development and social relationships. An intermediary object is both a conceptual framework and an analytic tool that enables researchers and educators to identify critical aspects of design coordination. In this paper, we compare two differently organized sections of a first-year engineering design course as a way to highlight the importance of prototypes in mediating these technical and social relations. It is not until these two courses are compared side-by-side that we uncover the critical importance of prototypes as intermediary objects. Based on this comparative case analysis, we argue that prototypes are pivotal intermediary objects that aid in students’ development of their engineering skills and pathways toward becoming an engineer. This paper contributes to the field of engineering education by connecting traditions from STS and exploring how the creation of prototypes impacts design education. In doing so, we provide some immediate recommendations for organizing engineering design courses, and we indicate future research on understanding the role of prototypes in design education and practice.
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Prototypes have been identified as critical artifacts for generating and developing innovative products and thus stimulating economic growth. However, prototyping is also associated with a large sunk cost including the extensive time and resources required to make physical prototypes. While a wide variety of prototyping methods have been proposed to reduce the cost and time of prototype development and increase the likelihood of final product success, the majority of research to date has explored the impact of these methods using simplistic measures of the technical performance of a design. Just as it is not enough to measure the effectiveness of ideation methods only by the quantity of ideas produced, we argue that it is not enough to measure the effectiveness of prototyping frameworks through technical performance alone. Without this fundamental knowledge, we cannot understand the impact of prototyping methods on final design success or failure. Therefore, the purpose in this work is to explore the effects of a structured prototyping framework on a variety of design attributes, including user satisfaction, perceived value, technical quality, and ease of manufacturability. Specifically, the overarching research question this study seeks to answer is: what attributes of a final design are affected by the implementation of a prototyping framework? A partial factorial experimental design was used to collect data from designs produced by 77 student design teams; designs were analyzed using five robust product metrics derived from the literature. Results indicate that a structured prototyping framework can lead to improved overall design quality and that differences in the implementation of such a prototyping framework can affect the achievement of these design attributes. The findings of this work deepen our understanding of the relationship between prototyping methods and design refinement during the product development process.
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Prototyping is an essential part of product development in companies, and yet it is one of the least explored areas of design practice. There are limited ethnographic studies conducted within companies, specifically around the topic of prototyping. This is an empirical and industrial-based study using inductive ethnographic observations to further our understanding of the various roles prototypes play in organizations. This research observed the entire product development cycle within three companies in the fields of consumer electronics (CE), footwear (FW), and medical devices (MD). Our guiding research questions are: What is a prototype? What are the roles of prototypes across these three companies? Through our analysis, we uncovered that prototypes are tools for enhanced communication, increased learning, and informed decision-making. Specifically, we further refine these categories to display the types of communication, learning, and decision-making that occur. These insights are significant because they validate many prior prototyping theories and claims, while also adding new perspectives through further exploiting each role. Finally, we provide newly modified definitions of a prototype and prototyping based on this empirical work, which we hope expands designers' mental models for the terms.
Conference Paper
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Design is a ubiquitous human activity. Design is valued by individuals, teams, organizations, and cultures. There are patterns and recurrent phenomena across the diverse set of approaches to design and also variances. Designers can benefit from leveraging conceptual tools like process models, methods, and design principles to amplify design phenomena. There are many variant process models, methods, and principles for design. Likewise, usage of these conceptual tools differentiates in industrial contexts. We present an integrated process model, with exemplar methods and design principles that is synthesized from a review of several case studies in client based industrial design projects for product, service, and system development, professional education courses, and literature review. Concepts from several branches of design practice: (1) design thinking, (2) business design, (3) systems engineering, and (4) design engineering are integrated. A design process model, method set, and set of abstracted design principles are porposed.
Conference Paper
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Just as design is a fundamental part of engineering work, prototyping is an essential part of the design process. For many engineering design courses, students must develop a final prototype as part of the course requirements. And in industry, engineers build multiple prototypes when creating a product for market. Although prototyping is core to design education, there is a lack of research on understanding the perceptions and usage of prototypes from both students and professionals. Without understanding students’ perceptions of prototypes, we cannot adequately train them. Likewise, without knowing how professionals use prototypes, we cannot translate these practices back to design education. This paper reports on the pilot study comparing the perceptions of prototypes between mechanical engineering students and professional engineers. The findings indicate that the interpretation of the term “prototype” varies between students and professionals. Specifically, these mechanical engineering students have a more narrow perception and identify prototypes as only having a few key elements, namely for building and testing functionality and feasibility of physical elements in a product. Comparatively, professionals have a broad perception of prototypes. They identify a wider range of attributes, including prototypes as a communication tool, an aid in making decisions, and a way to learn about unknowns throughout the design process. Many instructors in design education are cognizant of the importance of prototyping. However, we believe that students require explicit instruction about key concepts. It is not enough to just tell students to “prototype.” As design educators, we must be aware of the various roles of prototypes, and teach these concepts to students. We provide some immediate recommendations for practice, including a list of ten principles of prototypes to create similar mental models between students.
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Prototyping is interwoven with nearly all product, service, and systems development efforts. A prototype is a pre-production representation of some aspect of a concept or final design. Prototyping often predetermines a large portion of resource deployment in development and influences design project success. This review surveys literature sources in engineering, management, design science, and architecture. The study is focused around design prototyping for early stage design. Insights are synthesized from critical review of the literature: key objectives of prototyping, critical review of major techniques, relationships between techniques, and a strategy matrix to connect objectives to techniques. The review is supported with exemplar prototypes provided from industrial design efforts. Techniques are roughly categorized into those that improve the outcomes of prototyping directly, and those that enable prototyping through lowering of cost and time. Compact descriptions of each technique provide a foundation to compare the potential benefits and drawbacks of each. The review concludes with a summary of key observations, highlighted opportunities in the research, and a vision of the future of prototyping. This review aims to provide a resource for designers as well as set a trajectory for continuing innovation in the scientific research of design prototyping.
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Prototypes are essential tools in product design processes, but are often underutilized by novice designers. To help novice designers use prototypes more effectively, we must first determine how they currently use prototypes. In this paper, we describe how novice designers conceptualized prototypes and reported using them throughout a design project, and we compare reported prototyping use to prototyping best practices. We found that some of the reported prototyping practices by novice designers, such as using inexpensive prototypes early and using prototypes to define user requirements, occurred infrequently and lacked intentionality. Participants' initial descriptions of prototypes were less sophisticated than how they later described using them, and only upon prompted reflection did participants recognize more specific benefits of using prototypes.
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Design is a ubiquitous human activity. Design is valued by individuals, teams, organizations, and cultures. There are patterns and recurrent phenomena across the diverse set of approaches to design and also variances. Designers can benefit from leveraging conceptual tools like process models, methods, and design principles to amplify design phenomena. There are many variant process models, methods, and principles for design. Likewise, usage of these conceptual tools differentiates in industrial contexts. We present an integrated process model, with exemplar methods and design principles that is synthesized from a review of several case studies in client based industrial design projects for product, service, and system development, professional education courses, and literature review. Concepts from several branches of design practice: (1) design thinking, (2) business design, (3) systems engineering, and (4) design engineering are integrated. A design process model, method set, and set of abstracted design principles are porposed. OPENING There are patterns and consistent styles to the approach that humans take in design. Patterns of design activity often emerge quite differently according to context, and styles of the designer [4]. In this paper we explore the integration of several extant conceptual tools that support design innovation [5]. Specifically, aspects of design thinking, business design, systems engineering, and design engineering are explored. The distinction and interrelationships between design process model, methods, and principles is also approached The paper is organized according to the following three objectives: 1. Explore professional education workshops 2. Explore industrial case studies 3. Develop an integrated design innovation process model, methods set, and principle set Numerous design studies have explored process models, design methods, and design principles. Yet there is an ongoing need to distinguish these concepts and to build an integrated toolset. These conceptual tools are distinct, yet support each other. Process models guide overall activity flows and trends, methods support shorter term activites and help in planning work tasks, while principles guide designers mentally. Figure 1 provides an abstract illustration of the inter-woven relationship between these conceptual tools and designers.
Do-It-Yourself (DIY) fabrication is the practice where the end user creates a product for personal use rather than commercial production. This paper reviews how DIY practitioners can produce useful artifacts with limited resources. Fabrication principles were extracted from the DIY design repository A set of candidate principles was iteratively refined and converged to five unique principles. Case studies are presented that illustrate approaches for implementing each. A first empirical study verifies the repeatability of the principle classification through crowd-sourced assessment. A hypothesis is that the principles seen in DIY fabrication can support design prototyping. This is validated through an empirical study that shows a positive correlation between exposure to the principles and enhanced design outcome.