Using personality type differences to form engineering design teams

Abstract

This paper argues for the greater use ofpersonality type instruments such as theMyers-Briggs Type Indicator (MBTI) andthe Keirsey Temperament Sorter II (KTS II),when forming engineering design teams.Considering the importance of teamworkin all aspects of education and industry,it is surprising that few universities in theUK use personality type information whenforming design teams. This has led tomany courses not getting the best out oftheir students, and more importantly thestudents not getting the most out of theteamworking experience. Various teamformation methods are discussed and theirrelative strengths and weaknesses outlined.Normal personality type distributionsin base populations are presented andcompared with data from recent studies ofengineering students, and the link betweenengineering, design and creativity isdiscussed. The results of this study haveshown that the most important of the typepreferences is the Sensing-iNtuitive (S-N)scale, with its proven link to creativityand learning styles. It is concluded thatboth engineers and designers have muchin common, and a methodology of usingpersonality type choice sets to selectand form engineering design teams isproposed.

Full text

54 vol.2 issue 2 2007 engineering education
Using personality type differences
to form engineering design teams
Siu-Tsen Shen, Stephen D. Prior, Anthony S. White and Mehmet Karamanoglu
Abstract
This paper argues for the greater use of
personality type instruments such as the
Myers-Briggs Type Indicator (MBTI) and
the Keirsey Temperament Sorter II (KTS II),
when forming engineering design teams.
Considering the importance of teamwork
in all aspects of education and industry,
it is surprising that few universities in the
UK use personality type information when
forming design teams. This has led to
many courses not getting the best out of
their students, and more importantly the
students not getting the most out of the
teamworking experience. Various team
formation methods are discussed and their
relative strengths and weaknesses outlined.
Normal personality type distributions
in base populations are presented and
compared with data from recent studies of
engineering students, and the link between
engineering, design and creativity is
discussed. The results of this study have
shown that the most important of the type
preferences is the Sensing-iNtuitive (S-N)
scale, with its proven link to creativity
and learning styles. It is concluded that
both engineers and designers have much
in common, and a methodology of using
personality type choice sets to select
and form engineering design teams is
proposed.
Introduction
Placing individuals into productive teams
is one of the most important activities of
any educational or business environment.
However, it is also one of the least considered
components. Much attention has been given to
selection, performance measurement, retention
and progression activities in the literature,
but too little to the most fundamental task of
them all - forming the team. It is little wonder
that educational and business environments
often fail to get the best out of their students
and their employees, leading to frustration,
recriminations, and poor performance. This
failure, coupled with the fact that lecturers
in higher education are finding themselves
under increasing pressure, has resulted in
group formation activities being hit-and-miss
at best, and doomed to fail at worst. ‘University
teachers have accordingly found themselves
working harder and at the same time being
required to be more business-like and more
accountable.’ (Ramsden, 2003).
Research questions
• Whatistherangeofteamformation
methodologies available?
• Which,ifany,teamformationmethodologies
work and why?
• Isthereabetterwayofformingengineering
design teams, than simply using traditional
random selection methods?
• Whereistheproofthattheywork?
Team formation methods
There are many alternative methods available
to the individual lecturer when forming an
engineering design team. Each of these
methods has advantages and disadvantages;
however most are fatally flawed due to the fact
that they do not consider the strengths and
weaknesses of the individuals involved and
how to structure the mix to get the ‘best’ out of
all team players. By ‘best’, we mean performing
at the individual’s maximum output. If each
individual member of the group is given a role
which best suits their skills and knowledge, and
if the team is structured such that each role is
covered, but not duplicated, then we believe
that the team will perform to its maximum
capability. In doing so, the team will produce
the best learning experience for the individuals,
and also produce the best outcome – design,
system or prototype.
In brief, the choices in selecting team-based
groups after Race (2001) are:
(a) Let the students choose their own teams.
(b) Use the alphabetical class order in the
register.

engineering education vol.2 issue 2 2007 55
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(c) Use the university student number code
order.
(d) Select team members based on previous
performance.
(e) Select groups based on a
heterogeneous mixture, i.e. sex, age,
nationality, specialisation, etc.
(f) Select a team leader and let them pick one
additional member in turn.
(g) Select team members based on sitting or
standing position.
(h) Select team members based on astrological
‘star sign’ or month of birth.
(i) Select team members based on their
Personality Type and/or Learning Style.
(j) Issue coded labels to students, who then
form groups based on the codes.
Of these methods, the most commonly used
are (a), (b) and (c).
Allowing students to form their own teams
results in formations based on friendships.
Friends rarely work well in a team situation –
the relationship is too cosy, things don’t get
done and the atmosphere is too relaxed. This
method also tends to alienate people based
on differences in sex, age, nationality, race,
religion, disability and social status (as does
method (f)). Method (d) can be used to place
the best students in the top (alpha) team and
the worst students in the bottom (zeta) team.
This method, whilst stimulating the bottom
team to perform or die, can also have the effect
of giving the top team a feeling of unrealistic
superiority (the Apollo Syndrome) (Belbin,
1981) with its many negative implications. It
is also obvious that you need historical data,
which is not available in Year 1 classes, to
employ this method. Using random selection
methods such as (b), (c), (g), (h) and (j) will
produce average results at best. The only
methods that will guarantee above average
results are (e) and (i). Heterogeneous mixtures
of students usually perform well due to
their blending of expertise, experience and
perspectives. However, even apparently well-
balanced teams such as these sometimes fail
to perform due to no obvious reason.
Clearly it would be helpful to the engineering
lecturer to be able to understand the
personality, motivation, strengths and
weaknesses and learning style of the students
before forming the team. This can best be
achieved by using a questionnaire style
instrument to extract this information. The
two most popular methods are by using
instruments such as the Index of Learning
Styles (ILS) developed by Felder and Soloman
in 1991 and by using the Myers-Briggs Type
Indicator, MBTI® developed by Myers-Briggs
some 50 years earlier. These two models share
many facets and are complimentary in many
respects. This article will concentrate on the
use of the MBTI instrument due to its wide
proliferation and its large user base. For an
overview of Learning Styles please refer to the
excellent article by Felder & Brent (2005).
Belbin Team Roles
As already mentioned, the work of Dr R.
Meredith Belbin and his team of researchers
during the 1970s were influential in terms
of understanding management teams in a
business setting. His work, over nine years at
the Henley Management College, investigating
how teams function, culminated with his theory
of Team Roles. This theory is based on nine
team roles which can be broken down into:
Action oriented roles: Shaper, Implementer,
and Completer Finisher.
People oriented roles: Co-ordinator,
Teamworker and Resource Investigator.
Cerebral roles: Plant, Monitor Evaluator, and
Specialist.
This work has led to a series of business
orientated books and the e-interplace® software
package incorporating the Belbin Self-
Perception Inventory (SPI) – a psychological
profiling tool for the individual team member
(Belbin Team Roles, 2007). There is a lot of
overlap between the work of Belbin and that
of Myers-Briggs, however, in so far as the
Belbin method concentrates on the world of
commerce, we shall concentrate on methods
primarily for the educational setting.
The Myers-Briggs Type Indicator
In its basic form the Myers-Briggs Type
Indicator, MBTI® is a 93-item instrument and
the most widely known psychological typing
tool in use today. It was estimated by Pittenger
(1993) that over 2 million copies were being
sold annually in 1992. This has now risen to an
estimated 3.5 million annual sales worldwide
(OPP, 2007). The MBTI is available in more than
21 languages.
The MBTI has been around in one shape or
another for over 60 years, and has been used
in a number of occupational settings. No other

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psychological testing instrument has been
subjected to as many tests of reliability and
validity (Myers & McCauley, 1985). However,
it is fair to say that it has detractors as well as
supporters (Mathews, 2004).
Douglass Wilde, a Research Professor in
Design at Stanford University, who has used
the principals of psychological type with great
success to form engineering design teams over
the last 20 years, has stated that:
About a hundred million people have used the
MBTI, at least three-quarters of them agreed
strongly with all four results. Just about everyone
agrees with at least three. The other quarter
may find the MBTI preference clarity concept
useful for understanding uncertainty, if not
eliminating it.
(Wilde, 2003)
Historical development
of the MBTI Instrument
The roots of type theory can be traced
back to the turn of the 20th century and
the work of Carl Gustav Jung (1875-1961),
the Swiss psychiatrist and contemporary of
Sigmund Freud and Alfred Adler. Jung and
Adler disagreed with Freud with regards
to the importance of sexuality in causing
psychological problems and therefore split
with him in 1912. Jung’s seminal work,
Psychological Types was published (in German)
in 1921 after almost twenty years of practical
research work (Jung, 1971).
In her excellent book, Gifts Differing, the
co-founder of the MBTI, Isabel Briggs Myers
(1897-1980) describes how, together with her
mother Katherine Cooks Briggs they extended
Jung’s theory of personality types, adding two
important aspects:
[1] The existence and roles of the auxiliary
processes.
[2] The addition of the Judging (J) and
Perceiving (P) preference.
Thus, Jung’s eight pairs (23) became the
Myers-Briggs 16 types (24) (Myers & Myers,
1995). As can be seen from Figure 1, this
consists of four dichotomies, the interaction of
these, giving the 16 individual types, i.e. ISTJ,
ENFP, etc. The abbreviations in Figure 1 are
used throughout the paper.
The development of the MBTI and its
acceptance took many years of hard work
by Isabel Myers, herself, not a qualified
psychologist or statistician. The spur for this
development was World War II, where most
males were called to serve in the US military,
thus forcing many women into industrial jobs
for which they were not familiar or even well
suited. Thus the origin of the MBTI dates from
the summer of 1942, to quote Myers “…to do
something that might help people understand
each other and avoid destructive conflicts.”
(Myers & Myers, 1995)
Throughout the 40s, 50s and 60s, Myers
collected and developed an item pool of
data on personality type, mainly using
students from schools and colleges. The
first MBTI manual was published by the
Educational Testing Service in 1962. In 1975,
the publication of the MBTI was transferred to
Consulting Psychologists Press (CPP), with
the Center for Applications in Psychological
Type (CAPT), organised as a service for MBTI
development, research and training. The
CAPT maintains a research database of MBTI
published works which currently holds over
9,700 records.
The MBTI saw rapid growth and acceptance
throughout the 80s and 90s and has grown
into a multi-million pound industry. The MBTI
was developed specifically as a tool for the
non-psychiatric population, and is therefore
inherently benign. As a founding principle, no
one type is any better or worse than any other
and the testee has the final say as to his or
her type designation.
Figure 1.
The MBTI
dichotomous pairs
Myers-Briggs
Jung
Extraversion EIntroversion I
Sensing SiNtuition N
Thinking TFeeling F
Judging JPerceiving P

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The MBTI Preferences
Isabel Myers determined that the sixteen
personality types could best be shown using a
standard Type Table as shown below:
Myers stated that the interaction of these
orientations, functions and attitudes are what
makes up the personality types. Type theory
describes how, in a normal person, these
functions are developed as we mature, with
mastery of the dominant function, adequate
but not equal development of the auxiliary, and
eventual use of the third and fourth functions to
an acceptable level (Wankat & Oreovicz, 1993).
Further analysis and in-depth understanding
of each of the 16 types can be gained by
reference to the CAPT, CPP and Myers-Briggs
websites (CAPT, 2007; CPP, 2007; Myers-
Briggs, 2007).
The Keirsey Temperament Sorter
II (KTS II)
A contemporary of Isabel Myers, David Keirsey
has been very successful in his own right with
his personality type system which he calls the
Keirsey Temperament Sorter II, this consists of
a 70-item instrument that has only two possible
responses, and is available as an online test.
In his bestselling books Please Understand Me
and Please Understand Me II, Keirsey (1998)
follows the MBTI tradition of using 16 types,
however, this is where he parts company with
Myers. Keirsey regards the S-N scale as the
most important as it relates to the cognitive
perceiving function, and in this respect he has
gained a lot of followers in the area of learning
and teaching styles (Felder & Brent, 2005).
From his analysis, Keirsey orientates the 16
types into a tree-like structure configuring
types into four Temperament groupings, which
he calls Guardians, Artisans, Idealists and
Rationals (see Figure 2).
To each of the 16 types, Keirsey gave an
operational name, i.e. Supervisor, Inspector,
Mastermind, etc. The shading in Table 2 shows
the Temperament groupings (see Fig. 2).
Keirsey argues, with some justification against
the use of the ‘Function Typologies’, i.e. the
grouping of types based on their dominant
function and towards his vision of ‘Intelligence
Typologies’, i.e. Temperament groupings. Both
the MBTI and KTSII have found widespread use
within many fields of education and industry.
Normal type distribution in base
populations
Before looking at particular studies involving
engineering student populations in the UK,
US and Asia, it is important to give the reader
an understanding of how personality types
Table 1. The standard MBTI Type Table and
the UK general population distribution
(%) (OPP, 2007)
ISTJ
13.7%
ISFJ
12.7%
INFJ
1.7%
INTJ
1.4%
ISTP
6.4%
ISFP
6.1%
INFP
3.2%
INTP
2.4%
ESTP
5.8%
ESFP
8.7%
ENFP
6.3%
ENTP
2.8%
ESTJ
10.4%
ESFJ
12.6%
ENFJ
2.8%
ENTJ
2.9%
Note 1. The dominant processes of each type are
underlined in the table above.
Note 2. The sample consisted of 1,634 people living
in the United Kingdom. 748 (46%) were male and
865 (54%) female. 94% of the sample were white and
6% came from other ethnic groups. Ages ranged
from 16 to 65 years with 50% aged between 30 and
50. The sample included people of all educational
levels. 69% were currently employed, with 40% at
supervisory/first level management or above. A wide
range of industry sectors was represented.
The MBTI instrument sets out to gain answers
to the four dichotomies mentioned above, in
broad terms these refer to:
1. Orientation
Extraversion Introversion
(Outer world of people) (Inner world
of ideas and
actions)
2. Cognitive Perceiving Function
Sensing iNtuition
(Practical facts) (Imagination and
creativity)
3. Cognitive Judging Function
Thinking Feeling
(Logical – true or false) (Emotional and
subjective)
4. Attitude of the Functions
(2 & 3 above)
Judgement Perceiving
(Closure and certainty) (Open-ended,
uncertainty)

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Figure 2.
Keirsey’s tree structure
of Temperament groups
STJ SFJ
Guardians
STP SFP
Artisans
NFJ NFP
Idealists
NTJ NTP
Rationals
SJ SP NF NT
S-N
ESTJ, ISTJ
ESFJ, ISFJ
ESTP, ISTP
ESFP, ISFP
ENFP, INFP
ENFJ, INFJ
ENTP, INTP
ENTJ, INTJ
Table 2. Keirsey’s type names and their association with the MBTI type table
ISTJ
Inspector
ISFJ
Protector
INFJ
Counsellor
INTJ
Mastermind
ISTP
Operator
ISFP
Composer
INFP
Healer
INTP
Architect
ESTP
Promoter
ESFP
Performer
ENFP
Champion
ENTP
Inventor
ESTJ
Supervisor
ESFJ
Provider
ENFJ
Teacher
ENTJ
Fieldmarshal
Guardians Artisans Idealists Rationals
Table 3. Distribution of dichotomous population preferences in the UK, US and Korea
(CPP/OPP, 2007; Sim and Kim, 1993)
Guardians Artisans Idealists Rationals
UK 49.4% 27.1% 14.0% 9.5%
1998 E52.6% S76.5% T45.9% J58.3%
N=1,634 I47.4% N23.5% F54.1% P41.7%
Guardians Artisans Idealists Rationals
US 46.4% 27.0% 16.5% 10.4%
2003 E49.3% S73.3% T40.2% J54.1%
N=500,000 I50.7% N26.7% F59.8% P45.9%
Guardians Artisans Idealists Rationals
KR 50% 25% 11% 13%
1993 E41% S75% T63% J63%
N=13,308 I59% N25% F37% P37%

engineering education vol.2 issue 2 2007 59
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are distributed in normal general populations.
Given the length of time that the MBTI
instrument has been available it is somewhat
surprising that the data for the normal general
populations in the US and UK were only
developed in 1986 and 1998 respectively.
Normal population data for many other
countries in the world, including China and
India does not currently exist.
From the data above it is clear that the UK, US
and Korean populations are broadly similar in
terms of the Keirsey temperament distributions.
The UK population is, however, slightly more
Extravert than the US population – this is in
contrast to many earlier studies which reported
that the US population was more Extravert
(75%) (Wankat & Oreovicz, 1993). All three
populations exhibit preferences for Sensing and
Judging, with Korea being the most Judging.
In terms of the T-F dichotomy, Korea is very
different to either the UK or US, with a strong
preference for Thinking.
It should be noted that in terms of the Thinking-
Feeling dichotomy it is well documented that
Men prefer Thinking over Feeling (T = 60%,
F=40%), whereas Women prefer Feeling over
Thinking (F = 75%, T = 25%).
MBTI and the Chinese Market
The Chinese Mandarin version of the MBTI
was first translated in 1994 (Miao, Huangfu,
Chia and Ren, 2000) and only a few studies
have been reported since then (Yao, 1993;
Broer & McCarley, 1999; Osterlind, Miao,
Sheng and Chia, 2004; Sharp, 2004; Hu,
2005). Surprisingly, the CAPT database has
only 16 references to the term ‘Chinese’ and
7 references to ‘Taiwan’. Considering the
importance of the Chinese economy in the next
decade, more research is needed in this area.
According to the latest Engineering UK Report
(2006), China has experienced a 124 per cent
increase in the number of science, technology,
engineering and mathematics degrees over the
past decade to 350,000 per year.
Results from the few Chinese studies (Taiwan,
Hong Kong and China) that have been
published have reported:
• Introversionslightlypreferredover
Extraversion (52-64%).
• Sensingover-represented(60-85%).
• Thinkingover-represented(61-93%).
• Judgingover-represented(70-85%).
Overall this gives the national identity of the
Chinese population as ISTJ – inferring a
group who are “Serious, quiet, earn success
by concentration and thoroughness… make
up their own minds about what should be
accomplished and work towards it steadily,
regardless of protests or distractions.” (Myers et
al., 1998).
ISTJs also make up the highest proportion in
the UK population and the second highest in
the US population. From Myers et al. (1998)
ISTJs make very good leaders, are well
organised and have an entrepreneurial spirit.
Due to their diligence and attention to detail
they also find their way into the engineering
professions in large numbers.
Use of the MBTI in Engineering
Education
Over the years, studies in nearly every area
of engineering have investigated the ubiquity
of using the MBTI and KTS II instruments.
These range from mechanical and electrical
engineering, to chemical engineering and many
others (McCaulley, 1990; Rosati, 1998; Jensen,
Murphy and Wood, 1998; O’Brien, Bernold
and Akroyd, 1998; Stone and McAdams, 2000;
Jensen, Wood and Wood, 2003; Felder, Felder
and Dietz, 2002; Felder and Brent, 2005; Lester,
Schofield and Chapman, 2006).
One of the biggest studies into engineering
students was conducted by a consortium of the
American Society for Engineering Education
(ASEE-MBTI) involving eight engineering
schools and 3,784 students during the period
(1980-87). All subject specialisms were
covered and of special interest to us was
Mechanical Engineering. CAPT is the Center for
Applications in Psychological Type.
Comparing and contrasting the data in Tables 3
and 4 shows that Idealists are slightly over-
represented. Rationals (intuitive types) are
vastly over-represented by a factor of two
or three, and that there is a preference for
Thinking and Judging. This data has been
confirmed by many later studies.
Other studies have investigated personality
typing in Psychology (Chamorro-Premuzic &
Furnham, 2003), Economics (Ziegert, 2000),
Multimedia Engineering Design (McKenna,
Mongia and Agogino, 1998), Software
Engineering (Layman, Cornwell and Williams,
2006), Microelectronics (Pearson, Bell and

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Croley, 2003), Electrical Engineering (Chang &
Chang, 2000), Post-traumatic Stress Disorder
(Otis, 2005), Health Professionals (Hardigan,
Cohen and Janoff, 2005), Pharmacy Students
(Shuck and Phillips, 1999), Dentistry (Baran,
2005) and Career Counselling (Gruber, 2000),
Doctors and Patients (Clack, Allen, Cooper and
Head, 2004).
For an overview of how these disciplines relate
to distributions on the standard MBTI type table
we refer readers to the Atlas of Type Tables
(Macdaid, McCaulley and Kainz, 1986) and
Gifts Differing (Myers & Myers, 1995).
To put the MBTI results into context, it may
be helpful to note extreme values of the
preferences and how they relate to certain
professions:
Almost every reference quoted above refers
to studies conducted in the US or Canada,
very little work has been conducted in the UK
within Higher Education (Lester, Schofield and
Chapman, 2006).
Creativity and the design student
There is a scarcity of MBTI information on
Design students. A study by Stephens (1973),
though dated, provides some interesting data
in terms of the strong relationship between
creativity, introversion and intuition. This
research finding is further supported by earlier
work from Guilford (1966). Other studies have
used the MBTI, KTS II and Gough Creativity
Index (GCI) to further support this correlation
(Wilde, 2004).
A work by Durling (1996) also confirms the link
between creativity and intuition, and goes on
to discuss the problem-solving strategies of
designers. Interestingly, Durling orientated the
standard MBTI Type Table along the lines of
the dominant functions as stated in Table 3. By
plotting data for business managers, engineers,
architects, artists and designers together with
the general population he was able to show
the broad disposition of occupational groups
on the modified Type Table. Again much of
the basis for this data relates to the US base
populations, which have small sample sizes
and are outdated. Durling reported a study
of 71 students from product design, interior
design, graphic design, furniture design and
design marketing, based at two UK universities.
The distribution of type for this sample is shown
in Table 5 (re-orientated for consistency).
Table 4. Comparison of Mechanical Engineering students with Engineering Professionals
(McCaulley, 1990)
Guardians Artisans Idealists Rationals
ASEE-MBTI 40.16% 19.12% 6.94% 33.79%
1980-87 E45.56% S59.27% T80.32% J64.1%
N=518 I54.44% N40.73% F19.68% P35.9%
Guardians Artisans Idealists Rationals
CAPT-ME 44.48% 14.29% 19.48% 22.08%
86 E46.76% S58.44% T70.13% J62.34%
N=77 I53.24% N41.56% F29.87% P37.66%
Guardians Artisans Idealists Rationals
CAPT-Eng 38.25% 14.40% 19.98% 27.38%
1986 E47.67% S52.64% T63.59% J60.45%
N=986 I52.33% N47.36% F36.41% P39.55%
Student Leaders Architects
E - 84% E - 30%
I - 16% I - 70%
School Bus Drivers Fine Artists
S - 97% S - 9%
N - 3% N - 91%
Management Consultants Priests
T - 92% T - 20%
F - 8% F - 80%
Retail Store Management Food Service
J - 92% J – 48%
P - 8% P – 52%

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The sample shows that Design students have
a strong preference for iNtuition (79%) and a
strong preference for Perception (69%). Over
a quarter of the sample were from one type -
ENTP. People with the ENTP preference have
been described as “Warmly enthusiastic, high
spirited, ingenious and imaginative. Able to do
almost anything that interests them. Often rely
on their ability to improvise instead of preparing
in advance.” (Durling, 1996)
Engineers and designers
As can be seen from the data presented
earlier, Engineers and Designers have a certain
amount in common; they both have strong
levels of iNtuition (40-47%) and (79%), when
compared to the normal population (24-27%)
which enables both groups to be able to solve
problems creatively and intuitively. However,
even these groups don’t come close to Fine
Artists (iNtuition, 91%).
Both groups design, develop, validate and
create products and services for use by people.
However, many people would assume that by
their very nature designers are more creative
than engineers – we believe that this is a
common myth. It is true to say that designers
tend to operate on a divergent model theory
– many solutions (possibilities); whereas
engineers tend to operate on a convergent
model theory – one best solution (probabilities).
It is only when we combine these models
together to form the divergent-convergent
model do we get the optimum solution, which
we might call the Engineering Design solution.
Team formation using
personality type
By analysing the standard type table and its
associated type profiles, it has been possible to
group common personality traits into five tiers
(tiers 0 to 4 in Figure 3). From this, we have
concluded that there is a range of types best
suited to both the dual roles of Engineering and
Design.
Table 5. Type table distribution of 71 UK design
students (Durling, 1996))
ISTJ
1.4%
ISFJ
1.4%
INFJ
2.8%
INTJ
5.6%
ISTP
2.8%
ISFP
1.4%
INFP
7%
INTP
5.6%
ESTP
2.8%
ESFP
7%
ENFP
15.5%
ENTP
26.8%
ESTJ
4.2%
ESFJ
0%
ENFJ
5.6%
ENTJ
9.9%
Figure 3.
Exploded type table
showing choice
sets for Engineering
Design
TIER 0
ESTJ
ESFJ
ESTP ESFP ENFP
ENFJ
ENTP
ISTP ISFP INFP
INFJ
INTP
ISFJ
ISTJ
TIER 1 TIER 2 TIER 3 TIER 4
ENTJ
INTJ

SHEN, PRIOR, WHITE
and KARAMANOGLU
62 vol.2 issue 2 2007 engineering education
From analysis of the 16 MBTI personality types
and their dominant features, we suggest that
the following eight types in tiers 0 and 1 would
be the most suitable for Engineering Design
teams. Ideally, the team leader role should be
chosen from either the ISTJ or ESTJ personality
types (tier 0) due to their ability to lead,
organise, control, motivate and coordinate
team activities:
Tier 0 (Team Leadership):
ISTJ – Inspector – Pragmatic, detailed,
organised.
ESTJ – Supervisor – Practical, realistic,
decisive.
Note: we advise not to place ISTJs and ESTJs within
the same team, due to the inherent potential for a
power struggle to develop.
Tier 1 (Development Team):
ISTP – Operator – Hands-on, problem solver,
curious.
ESTP – Promoter – Problem solver, mechanic,
adaptable.
INTJ – Mastermind - Original thinker, creative,
organised. (Possible Leader)
INTP – Architect - Scientist, logical, analytical.
ENTP – Inventor – Ingenious, outspoken,
resourceful.
ENTJ – Fieldmarshal – Frank, decisive.
(Possible Leader)
These choice sets and their relationship to
Keirsey’s temperaments can be seen in Table 6.
Table 6. Choice sets for the selection of Engineering Design teams
Guardians Artisans Idealists Rationals
Tier 0 ISTJ – Inspector
ESTJ – Supervisor
Tier 1 ISTP – Operator
ESTP – Promoter
INTJ – Mastermind
INTP – Architect
ENTP – Inventor
ENTJ – Fieldmarshal
Tier 2 ISFJ – Protector
ESFJ - Provider
INFP – Healer
ENFP - Champion
Tier 3 INFJ – Counsellor
ENFJ - Teacher
Tier 4 ISFP – Composer
ESFP - Performer
Note: The Tier 0 group consists of half the Guardians, and is the grouping from which the Team Leader role
should ideally be selected.
To show how this might work in practice, data
from Durling (1996) and data supplied by the
CAPT databank (Macdaid et al., 1986) has
been combined in Table 7.
Analysis of Table 7 shows that by using only
Tiers 0 and 1 selection sets (eight types)
which encompasses 46% of the general UK
population, it would have been possible to have
selected 60% of the Design students and 70%
of the Mechanical Engineers in this example.
Further selection sets could be employed
when necessary to enlarge the pool or act
as a filtering mechanism for team formation
purposes. We accept that a lot will depend
on the size of the team being formed and the
availability of the personality types in the pool.
However, it is also clear that certain types (ISFP
and ESFP) would make poor Engineering
Designers.
It is common for teams to range from two to
eight students in an educational environment,
and perhaps up to ten in a business context.
Clearly, a balanced team consisting of a range
of personality types is the desired goal.
Discussion and conclusions
For the first time, accurate data on various
aspects of personality type, such as population
preferences, temperament statistics and type
table data, has been brought together within
one source.

engineering education vol.2 issue 2 2007 63
SHEN, PRIOR, WHITE
and KARAMANOGLU
Some recent data on the distribution of
extroversion in the US refutes earlier research
which suggested that the US population was
75% Extroverted, we now know that there
are more extroverts in the UK (53%) than in
the US (49%), and that both populations are
remarkably similar in other respects.
The authors of this paper argue that any of the
methods described (MBTI, Keirsey, Belbin or
Learning Styles) which seeks to group teams
based on an understanding of their underlying
personality traits, skills and knowledge is better
than any of the alternative random selection
methods.
As an example of its success, the work of
Wilde (2003) at Stanford University stands out,
due to his method of adapting both the MBTI
and KTS II, formulating his own method of
team selection. This has proved to be a highly
successful strategy in terms of the annual
National Lincoln Prize awards in the US:
1. No selection strategy (27% of awards won).
2. Preference information guidance (57% of
awards won).
3. Creative roles used (73% of all awards won).
Further work is ongoing at Stanford to develop
this system into an even more effective tool.
Table 7. Comparison of Mechanical Engineers and Design Student type selection using only Tiers 0 & 1
Rank Mechanical Engineers % Cumulative Rank Design Students % Cumulative
1
2
3
4
4
4
7
8
8
8
8
8
8
14
14
16
ISTJ (19.5%)
ESTJ (18.2%)
ENTP (9.1%)
ISTP (6.5%)
INFP (6.5%)
INTJ (6.5%)
ENFJ (5.2%)
INTP (3.9%)
INFJ (3.9%)
ESTP (3.9%)
ENFP (3.9%)
ESFJ (3.9%)
ISFP (3.9%)
ENTJ (2.6%)
ISFJ (2.6%)
ESFP (0%)
19.5
37.7
46.8
53.3
-
59.8
-
63.7
-
67.6
-
-
-
70.2
-
-
1
2
3
4
4
6
6
6
9
10
10
10
13
13
13
16
ENTP (26.8%)
ENFP (15.5%)
ENTJ (9.9%)
INFP (7%)
ESFP (7%)
INTP (5.6%)
INTJ (5.6%)
ENFJ (5.6%)
ESTJ (4.2%)
ISTP (2.8%)
ESTP (2.8%)
INFJ (2.8%)
ISTJ (1.4%)
ISFJ (1.4%)
ISFP (1.4%)
ESFJ (0%)
26.8
-
36.7
-
-
42.3
47.9
-
52.1
54.9
57.7
-
59.1
-
-
-
For the average lecturer, the use of any of
these methods will come down to how much
time they have to prepare, and how much
money is available to spend. The answer
to both these questions is usually little or
none. Therefore, there either needs to be a
fundamental change in the philosophy of team
selection and its importance to the learning
environment or cheaper alternatives need to
be found.
In the search for a solution to this problem
we have been experimenting with freely
available pseudo-MBTI questionnaires which
are available over the internet. One of the best
that we have found so far is from Similarminds
(2007). Of course, going down this path
provides a solution to the problems of time
and money, but, this is at the cost of reliability
and validity, which are largely unknown.
More empirical studies in this area are clearly
needed.
Much of the original research into personality
type was conducted in the 50s, 60s and 70s
and therefore can be regarded as somewhat
out of date. However, ongoing work by various
agencies such as the CAPT, CPP Inc and the
OPP Ltd has rejuvenated some of these data
sets with information not available to earlier
research studies.

SHEN, PRIOR, WHITE
and KARAMANOGLU
64 vol.2 issue 2 2007 engineering education
The Chinese (South East Asian) economy
is clearly set to rapidly expand over the
next decade, and as such MBTI data, not
currently available, will be extremely useful
for both education and business purposes
alike. From our research it is clear that the
Chinese populations are different in several
respects when compared to western nations.
The Chinese have stronger preferences for
Introverted, Sensing, Thinking and Judgment.
This makes them good in organisation, detailed
thinking and control, but not so good in terms
of creativity, openness, warmth and perception.
Having analysed the sixteen MBTI personality
types for their relevance to the fields of
engineering and design, we can conclude that
there are eight types which are best suited
to the area of engineering design. By ranking
these in order of selection preference (Tiers
0-5) we have effectively provided the educator
or business leader with the tools to select a
successful engineering design team, consisting
of a complimentary set of skills, and managed
by a strong leader type (ISTJ or ESTJ).
There is clearly much work to be done in
understanding engineering designers, and the
way that they think, however, there are a lot of
associations to be found between creativity,
intuition, learning styles and personality types.
In conclusion, the authors would like to
encourage all engineering educators to make
greater use of type theory when selecting
and forming engineering design teams and
delegating leadership roles. The benefits
of this, we hope, will be recognised by the
mainstream engineering education community,
and just as importantly by our industrial
colleagues (Dym et al., 2005).
n
Acknowledgements
The authors would like to thank Ms. Jamelyn R. Johnson, Coordinator of Research Services at the
Center for Applications of Psychological Type for preparing the Selection Ratio Type Tables (SRTT)
used in this research.
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About the authors
Siu-Tsen Shen MDRes, PhD. Assistant Professor, Multimedia Design, National Formosa
University, Hu-Wei, Taiwan
Stephen D. Prior BEng (Mech), PhD, CEng, MIMechE, PGCertHE, FHEA
Principal Lecturer, Product Design and Engineering, Middlesex University, London, UK
(Corresponding author.) Tel: 020 8411 5275 Fax: 020 8411 5683 Email address: s.prior@mdx.ac.uk
Anthony S. White BSc (Eng), MSc, MSc, PhD, PhD, FRAS, FIMechE, MRAeS
Research Professor, Computing Science, Middlesex University, London, UK
Mehmet Karamanoglu BEng (Mech), PhD, MIEEE, FRSA, FHEA
Principal Lecturer, Product Design and Engineering, Middlesex University, London, UK