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d
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desire designum design, 4
th
european academy of design 2001
ISBN 972 789 024 5
What Inspires Undergraduate Design Students?
Paul Rodgers and Alex Milton
Awarded best paper award
Also published in: The Design Journal, Volume 4, Issue 2, 2001
Abstract
The importance of design inspiration sources and the way designers utilise them during their
designing activities is well-documented [1]. For example the use of nature as a source of inspiration is
widespread in a variety of design disciplines [2], such as the invention of VELCRO in the early 1940’s
[3]. More recently architectural design firms such as Frank Gehry and the Future Systems Group have
received widespread recognition for their creative use of design inspiration sources. Gehry,
responsible for the design of the hugely successful Guggenheim Museum in Bilbao, lists one of his
main sources of design inspiration as “fish” (Figure 1).
Figure 1. Gehry’s Obsession with Fish has led to Stunning Architectural Design
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The Future Systems Group [4], on the other hand, are well known for their extraordinary range of
inspirational sources in their design work such as the use of cross sectional views of racing yachts in
the design of the Lords Media Centre, London (Figure 2).
Figure 2. Future Systems Group’s Lords Media Centre Inspired by Racing Yachts
In the realm of product design, inspirational sources are also viewed as a significant factor in the
development of unique and innovative objects. For example, in the field of product design, the hugely
successful Michael Young includes the work of the American conceptual artist Jeff Koons, old tractors
and milk bottles (Figure 3) in his list of wide ranging inspiration sources [5].
Figure 3. Inspiration behind Michael Young’s MY 068 Wood Chair
Similarly, the British furniture designer Matthew Hilton has used imagery and inspiration sources in his
“Wait” plastic chair from classic furniture pieces of the 1960’s (Figure 4) and 1970’s including Vico
Magistretti’s “Selene” chair and Joe Colombo’s “Universale” chair [6].
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Figure 4. Inspiration for Matthew Hilton’s “Wait” Chair
However studies into what inspires undergraduate design students, to date, have been neglected.
Thus, the goals of this paper are firstly to investigate what inspires undergraduate design students
and secondly explore any correlation between the formal undergraduate coursework performances of
the students and their design inspiration sources.
1. Studying Design Student’s Inspiration Sources
The main objective of this study is to explore the relationship of undergraduate design students’
responses to questions concerning their design inspiration sources from fields including art, cinema,
literature, architecture and so on and use this as a measure of their level of design awareness. From
their design awareness rating one can compare this with their first year undergraduate degree
performance, the key objectives being:
• to explore the potential of quantifying design inspiration sources as an indication of a student’s
level of design awareness;
• to investigate whether this design awareness level will provide an indication as to how well a
student will perform during their undergraduate education.
Preliminary results from this study, presented later in the paper, indicate that there is a correlation
between a student’s first year degree performance (i.e. coursework mean) and their design
awareness score. This appears to indicate that students with a high design awareness rating will
perform significantly better than their counterparts with a lower rating.
2. Methodology
A total of twenty five first year undergraduate design students from the department of design at Napier
University were interviewed independently in a semi-structured manner within a controlled
environment [7]. The investigators (authors) questioned the student interviewees directly as this is far
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less likely to result in misinterpretations than say an open-ended questionnaire approach. A potential
problem with the interview approach, however, is the investigator/respondent effect. The concern here
is that the respondents will fear that the investigator might find their responses “unsuitable” or
“incorrect”. In an attempt to reduce investigator/respondent effects, a number of control questions
were used during each interview. These control questions were not used in the subsequent analyses
of the respondents’ interviews. The students were not allowed to consult with other students before or
after their interview.
Each student was asked a total of eight questions. The questions posed of each student were:
1. What building (past or present day) inspires you the most in your design studies?
2. Which three-dimensional product (of the past or present day) do you feel has had the most impact
on your design work?
3. Which author (living or dead) inspires your work?
4. Which automobile design (past or present) inspires you most?
5. Which film from the past or present day has inspired your work recently?
6. What music inspires you the greatest in your design work?
7. What magazine do you read regularly that inspires and informs your design work?
8. Who is your favourite designer (including architects) living or dead - in terms of the impact they
have on your design studies?
Responses from the students were wide ranging and showed a varying degree of awareness of the
subject area of each question. This is illustrated in Figure 5, with a variety of responses to questions
concerning film, building design, and 3D product design evident. The responses shown here include
Bladrunner and Star Wars to the query “Film”, the Sydney Opera House and the Pompidou Centre to
the query “Building Design”, and Apple’s Ibook and Alessi’s Firebird to the query “3D Product”.
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Figure 5. Some of the Student Responses to Design Inspiration Questions
Every response from each student was then assigned an individual rating and subsequently summed.
The rating scale, based on the “System Usability Scale” [8], used in this study uses ten distinct scale
points between two semantic anchors of “high design awareness” and “low design awareness”. Each
student response was scored by a committee comprising five members of the lecturing staff within the
Design Department of Napier University (including the authors). A rating of 10 was assessed to show
an exceptionally high level of design awareness, whereas a rating of one was considered to show a
very low level of design awareness.
Figure 6. Design Awareness Scale
For instance, in Figure 6, the committee of design staff rated the successful, contemporary designer
Jonathan Ive (head of Apple design) a 9, the radical Australian designer Marc Newson 8, down to
design awareness levels 2 and 1 representing brand name manufacturers involved in design
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(although outside the field of 3-D design) such as Tommy Hilfiger (level 2) and popular design student
misconceptions regarding famous designers such as Marcel Duchamp (level 1).
3. Results and Analysis
From the study carried out, the coursework mean scores of the twenty five students involved are
illustrated, as a percentage range, in Figure 7. From this data, one can observe that the mean score
for the year-long coursework mean is slightly over 50%. The most frequently occurring score (i.e.
mode) in this group is 51% and the median is 51.6%.
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10
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0
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4
6
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10
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< 30 30 - 39 40 - 49 50 - 59 60 - 69 > 70
Coursework Mean %
Frequency
Num bers of Students
Figure 7. Coursework Mean (% scores) Distribution
Furthermore, a distribution graph highlighting the student sample responses relating to their design
awareness percentage scores is shown in Figure 8. From this figure one can see that the majority of
the students in the sample possess a design awareness score between 40 to 49%. The most
frequently occurring score (mode) is 40%. The mean design awareness score is just over 39%, with
the median score of the distribution being 40%. The relatively low design awareness score is not too
surprising when one bears in mind that the students are only in the first year of their four year
undergraduate degree programme. The main pedagogical goal obviously being to increase each
student’s design awareness rating as their studies progress.
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0
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10
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< 20 20 - 29 30 - 39 40 - 49 50 - 59 > 60
Design Awareness %
Frequency
Figure 8. Design Awareness (% scores) Distribution
3.1 Relationships
A scatter diagram shown in Figure 9 was plotted to illustrate diagrammatically the extent of the
relationship between the design students’ coursework mean and their design awareness % score. As
can be seen from Figure 9, the general trend of the points slope upwards from left to right which
indicates that there is a positive, linear relationship between the two variables (coursework mean and
design awareness).
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10
20
30
40
50
60
70
0.00 20.00 40.00 60.00 80.00
Coursework Mean %
Design Awareness %
Series1
Linear (Series1)
Figure 9. Scatter Plot of Students’ Coursework Mean and Design Awareness (% scores)
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The data illustrated above provides some evidence that the higher the student’s coursework mean
score, the higher their level of design awareness score will be. Having illustrated that there is an
association indicated between the two variables in Figure 9, the next section of the paper will try to
discover the degree of correlation between the variables by using Pearson’s correlation coefficient [9].
3.2 Pearson’s Product Moment Correlation Coefficient
Pearson’s product moment correlation coefficient (r), a dimensionless index that ranges from -1.0 to
1.0 inclusive, was used to reveal the extent of any positive or negative linear relationship between the
two variables (i.e. year coursework mean and design awareness percentage score) [10]. Based on
the data collected in this study, and illustrated in Figure 8, Pearson’s product moment correlation
coefficient (r) was calculated as +0.663 which suggests that a strong positive correlation exists.
However, the coefficient of determination is important and relevant here as it measures the proportion
of total variation that can be explained by r. Thus, when r = +0.663, r
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= 0.440118 which means that
one can conclude that just over 44% of the variations in design awareness can be explained by the
regression equation, leaving approximately 56% to be explained by other factors.
3.3 Analysis Summary
Although the analysis of data above indicates that correlation exists there is no justification in
assuming a cause and effect relationship at this point. Occasionally a high correlation is nonsensical.
For example the high correlation between infant mortality and the extent of overcrowding that was
found in Bethnal Green, London between the First and Second World Wars does seem to suggest
that overcrowding causes high infant mortality. In fact, however, both are probably a result of low-
income levels [9]. However, the initial aim of this study was to explore the relationship between a
design student’s responses to a number of questions relating to their design inspiration sources, take
these as a measure of their level of design awareness, and finally compare this awareness with their
first year undergraduate degree performance. From the data gathered during this work, the results
indicate that there may indeed be a correlation between a design student’s level of design awareness
and how they perform in their formal design coursework and, if nothing less, further investigation is
required to expand and develop the study.
4. Conclusions and Future Work
The preliminary results presented here show that there is a correlation between a student’s first year
degree performance (coursework mean %) and their design awareness % score (see Figure 5). For
example from the study, students within the design department averaging a grade A or B overall in
their first year of undergraduate studies (i.e. greater than 60%) have a design awareness mean score
of slightly over 47% (mode 43% and median 45%). Students averaging a C grade (i.e. 50 to 59%)
have a design awareness mean score of just over 40% (with a mode of 28% and median 39%).
Students with a coursework grade score of D or E (i.e. 30 to 49%) have a mean design awareness
score of 36% (mode 40% and median 39%). Students obtaining an average grade F (i.e. lower than
30%) have a design awareness average score of 25% (with a mode of 30% and median of 30%).
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These figures are illustrated in the bar diagram in Figure 10. This indicates that students with a high
design awareness rating perform significantly better than their counterparts with a lower rating.
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10
20
30
40
50
A - B C D - E F
Coursework Grades
Design Awareness % Scores
MEAN
MODE
MEDIAN
Figure 10. Overall Student Coursework Versus Design Awareness Mean, Mode and Median Scores
It is acknowledged that a strong correlation between the two variables (coursework mean and design
awareness) can not be concluded without further investigation. To this end, future work will include
extending the questionnaire/interview study to incorporate further “design aware” criteria such as what
famous chair most influences your design studies? Future work is also planned to include further
analysis of the data that has been gathered to investigate other significant relationships, such as for
example, between an individual’s design awareness score and their gender or age. Moreover, further
studies will be carried out to monitor the development of students (in terms of their design awareness)
as they progress through the four year undergraduate degree programme. It is also planned to carry
out a much larger empirical study both within Napier University and other University design
departments throughout the UK.
5. References
[1] Oxman, R.E., Prior knowledge in design: A dynamic knowledge-based model of design and
creativity, Design Studies, Vol. 11, No. 1, 1990, pp. 17-28.
[2] Petroski, H., The evolution of useful things, Vintage Books, New York, NY, 1994.
[3] Wake, W.K., Design paradigms, John Wiley and Sons, New York, NY, 2000.
[4] Future Systems., More for Inspiration Only, Academy Editions, London, 1999.
[5] Payne, A., We Like This, Black Dog Publishing, London, 1999.
[6] McDermott, C. and Dewing, D., Matthew Hilton: Furniture for Our Time, Lund Humphries (Ashgate
Publishing Limited), London, 2000.
[7] Jordan, P.W., An Introduction to Usability, Taylor and Francis, London, 1998.
[8] Brooke, J., “A Quick and Dirty Usability Scale”, in P.W. Jordan et al (Eds.), Usability Evaluation in
Industry, Taylor and Francis, London, 1996, pp. 189-194.
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[9] Owen, F. and Jones, R., Statistics, Pitman Publishing, London, 1994.
[10] MacRae, S., Describing and Interpreting Data, The British Psychological Society, Leicester, 1994.
