Journal of Small Business Strategy Vol. 25 ● No. 2 ● 2015

SBI 2015 Conference
Distinguished Teaching Paper

Awarded by the Small Business Institute®

WHAT PEDAGOGICAL METHODS IMPACT STUDENTS’
ENTREPRENEURIAL PROPENSITY?

Bonnie Canziani
University of North Carolina, Greensboro

bonnie_canziani@uncg.edu

Dianne H. B. Welsh*
University of North Carolina, Greensboro

dhwelsh@uncg.edu

Yuchin (Jerrie) Hsieh
Rochester Institute of Technology

yhsieh@rit.edu

William Tullar
University of North Carolina, Greensboro

wltullar@uncg.edu

ABSTRACT
There is a dearth of research that investigates the effectiveness of different pedagogical
methods for teaching entrepreneurship. This paper focuses on three learning design choices:
experiential learning, use of teamwork, and focus on quantitative methods. The paper
examines pedagogical variables that could contribute to raising student scores on constructs
of change, risk taking, goal setting, feedback, and achievement as measured by our
customized entrepreneurial propensity survey. Results offer moderate evidence to confirm
effects of experiential learning designs for goal-setting and weak evidence for feedback.
Additional findings suggest the need for rethinking the role of teamwork in entrepreneurship
courses.

Keywords: entrepreneurship pedagogy, experiential learning, entrepreneurial propensity

Journal of Small Business Strategy Vol. 25 ● No. 2 ● 2015

INTRODUCTION

The enormous economic, social, and
educational benefits resulting from
entrepreneurship have caused the proliferation
of entrepreneurship education programs in
colleges and universities around the world. In
the U.S. alone, more than 1,500 colleges and
universities offer entrepreneurship-related
training in different formats (Charney &
Libecap, 2000). The exponential growth of
entrepreneurship education is a challenge to
educators, and prompts more thinking and
research on what to teach and how to teach
entrepreneurship in a classroom setting. The
entrepreneurship education literature
highlights two dimensions relating to the
outcomes of entrepreneurship education. One
is the development of an individual’s skill set
(e.g., the skill to identify opportunity and to set
up a business and manage its growth), the
other is to build an “entrepreneurial mindset”,
meaning to mold an individual’s
entrepreneurial personalities or attributes
(e.g., an individual’s creativity, innovation,
and risk-taking) (Fayolle, Gailly, & Lassas-
Clerc, 2006; Garavan & O’Cinneide, 1994;
Weber, 2011).

Some scholars (Müller & Gappisch, 2005;
Roberts, 1998; Stormer, Kline, & Goldenberg,
1999) emphasized the second dimension and
argued that entrepreneurship is a personality
trait: a combination of personality and talent
that can be cultivated and trained.cognitive
declarative knowledge, individuals who are
goal-setters, who need achievement, and who
are risk takers, tend to become successful
entrepreneurs (Welsh & Tullar, 2014).
Entrepreneurship education can strengthen
individual’s entrepreneurial attitudes (Harris,

Gibson, & Taylor, 2007/2008). To train
and cultivate entrepreneurial traits requires an
integrated learning and teaching strategy that
aligns intended learning outcomes with the
effective selection of pedagogy. There is a
strong belief that the most effective
pedagogical approach to teaching
entrepreneurship is action-oriented and
experientially based learning that embeds
hands-on project-based activities (Minniti &
Bygrave, 2001; Sherman, Sebora, & Digman,
2008).

Although researchers and educators have
extolled the alleged benefits of
entrepreneurship education, there has been
little rigorous research on its effects (Gorman,
Hanlon, & King, 1997; McMullan, Chrisman,
& Vesper, 2002). Specifically, how effective is
such an experiential approach in enhancing
students’ entrepreneurial propensity? Do
experientially based activities have an impact
on students’ intent to become entrepreneurs?
And is the extent of the impact positive or
negative? To date, there is a dearth of research
that investigates the impact or effectiveness of
different pedagogical methods for teaching
entrepreneurship (Honig, 2004; Winslow,
Solomon, & Tarabishy, 1999). This paper
focuses on the impacts on critical measures
associated with entrepreneurial propensity of
three learning design choices: experiential
learning, use of teamwork, and focus on
quantitative methods. The paper aims to
unlock the pedagogical variables that could
contribute to student scores on constructs of
change, risk taking, goal setting, feedback,
and achievement as measured by our
customized entrepreneurial propensity survey
(Welsh & Tullar, 2014).

Journal of Small Business Strategy Vol. 25 ● No. 2 ● 2015

BACKGROUND LITERATURE

Entrepreneurial Propensity/Intention for
Entrepreneurship

The basis for our Entrepreneurial Propensity
survey (Welsh & Tullar, 2014) is to measure
student task motivation in entrepreneurship
courses. The constructs measured are:
Change, Risk Taking, Goal Setting, Feedback,
and Achievement. We follow the Task
Motivation Theory (Miner, Smith, & Bracker,
1989) in designing the survey. Task
Motivation Theory is largely synonymous
with McClelland’s (1961) work on the need
for achievement which has been widely
recognized as one of the first good predictors
of entrepreneurial success. Miner and
colleagues recast McClelland’s (1961)
concepts into Task Motivation Theory (Miner
et al., 1989). Task Motivation Theory (Miner
et al., 1989) follows a more holistic approach
to the entrepreneurial role. While it measures
achievement motivation, it also measures risk
taking, feedback of results, personal
innovation, and planning for the future.

Task Motivation Theory (Miner et al., 1989)
holds that the pushes and pulls of sanctions are
built into the entrepreneurial task itself.
Control over a person’s behavior does not
proceed from superiors, or professional norms,
or peer group members, but rather it comes
from the work itself and the way it is
structured. Entrepreneurs expect financial
rewards, status in their communities, and
personal satisfaction. At the same time they
experience the threats of business failure,
personal ruin, and bankruptcy.

Five constructs essential to entrepreneurial
propensity were drawn from the above
theories. The first of the five constructs is

Change. The pull of individual achievement
works only to the extent that the individual can
attribute change to something the individual
has done him/herself. Original or creative
changes have a distinctive quality that makes
it easier to identify them as one’s own and to
take personal credit for them. A desire to
introduce such changes is more likely to make
task inducement function as it should.

The next construct is Risk Taking. The
successful entrepreneur must face considerable
challenge and the prospect of being
overextended. To accept this, an individual
must have a desire to take risks; tasks that the
individual already knows well don’t exert any
pull because there is no sense of achievement in
accomplishing them. In addition, the desire to
take risks where personal effort cannot
ultimately reduce the risk is not part of the
entrepreneurial mindset. In neither case can a
person anticipate a sense of individual
achievement with any reasonable probability.
Entrepreneurs desire to take risks where they
can have an influence on the outcome.

Goal Setting is a hallmark of the
entrepreneurial mindset. The entrepreneur is
pulled by the prospect of anticipated future
rewards. S/he must approach life with a strong
future orientation. Such a person must have a
desire to plan and to set personal goals that will
signify achievement. Having set the goal, the
entrepreneur must plot ways to attain the goal.
The entrepreneurial mindset is future oriented
without inordinate fear of failure.

Feedback is generally a need of entrepreneurs.
Feedback on the amount and results of one’s
performance are the only way to attribute any
degree of success to one’s efforts.

Journal of Small Business Strategy Vol. 25 ● No. 2 ● 2015

Entrepreneurs need to know whether they
have succeeded or failed. Consequently, the
individual must be motivated to seek out
results-oriented feedback in measures such as
profitability, productivity, waste, course
grades, etc.

The last and most recognizable of the
constructs is Achievement. Based on
McClelland’s seminal work, Achievement has
been shown related to entrepreneurial success
in a wide variety of contexts (cf. McClelland,
1961). The major source of this motivation is
an intrinsic desire to achieve through one’s
own efforts and ability and to experience the
enhanced feelings of self-esteem and self-
worth that achievement affords. Individuals
high in this motive typically look for situations
where the risks that they take and their hard
work can produce tangible results that they can
tell themselves they have caused.

These five separate motives may substitute for
one another in producing an overall index of
task motivation (Locke & Henne, 1986). The
Thematic Apperception Test (TAT) was
developed by Henry A. Murray and Christiana
D. Morgan at the Harvard Clinic at Harvard
University during the 1930s (For a history, see
Morgan, 2002). Although McClelland’s work
was based on a single construct, the need for
achievement (McClelland & Winter, 1969),
the scoring of TAT stories for need for
achievement included some risk taking,
feedback, and innovation, but these factors
were not measured separately. Task
Motivation Theory (Miner, Smith, & Bracker,
1989) is based on the notion that it is necessary
to measure each of these five features of the
entrepreneurial role separately which is the
approach used in this paper.

Experiential Learning
The concept of experiential learning is not a
recent phenomenon. There is a long history of
ideas regarding the importance of experiential
learning, rooted in the early work of John
Dewey (1910, 1938). Dewey believed
learning and democracy would be advanced if
people were engaged in “active, real world
problem-solving” combined with “reflective
thought and action” (Harkavy & Benson, 1998,
p.16). Dewey integrated the idea of experiential
learning into traditional higher education,
believing that experiential learning could be
used as a bridge between the academic and the
practical. Scholars such as Kurt Lewin, Jean
Piaget, William James, Carl Jung, Paulo Freire,
and Carl Rogers helped to model the theory of
experiential learning (Kolb & Kolb, 2005). Carl
Rogers differentiated between two types of
learning: cognitive and experiential; and
indicated that experiential learning focuses on
the needs of the learner, and is conducive to
personal change and growth (Rogers, 1969).
These scholars believed that learning is a
holistic process of adaptation to the world,
resulting from synergetic transactions between
the person and the environment, and it is the
responsibility of education to connect student
learning to the real world.

Kolb’s Experiential Learning Theory. Kolb’s
experiential learning theory is one of the best
known educational theories in higher
education, and defines learning as "the process
whereby knowledge is created through the
transformation of experience. Knowledge
results from the combination of grasping and
transforming experience" (Kolb, 1984, p. 41).
The theory presents a cyclical model of
learning, consisting of four stages. The first
stage, concrete experience, is where the learner
actively experiences an activity. The second

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stage, reflective observation, is where the
learner consciously reflects back on that
experience. The third stage, abstract
conceptualization, is where the learner attempts
to conceptualize a theory or model of what is
observed. The fourth stage, active
experimentation, is where the learner tries to
plan how to test a model, theory or plan for a
forthcoming experience. A person passes
through these modes repeatedly in a way that
helps them learn from the past and take new
information into future learning situations
(Kolb, 1984).

Benefits of Experiential Learning.
Experiential learning focuses on learning by
doing, which is regarded as one of the best
instructional techniques to provide students
with opportunities to internalize material, and
is understood by a great number of students
(Meyers & Jones, 1993). Experiential learning
is student-centered instruction, rather than
teacher-centered instruction, since the
student’s progress through the four
experiential learning stages facilitates and
drives the education process (Kolb, 1984).
Active participation of the learners in the
learning process often results in deeper and
more robust learning than is gained from just
reading or listening to lectures. In the
experiential learning classroom, even students
who are passive in learning are provided with
opportunities to facilitate their own learning
by actively applying the material at hand
(Krueger, 2007). The experiential learning
classroom also provides the opportunity for
students to receive immediate feedback in
classroom discussions, and to realize the
importance of participation in group activities,
which helps eliminate the competitive
atmosphere that occurs when students are not

given opportunities to work together to
achieve a common goal (Meyers & Jones,
1993). It is also found that real-life
experiences have a lasting effect on students
(Okudan & Rzasa, 2006).

Experiential Learning in
Entrepreneurship
Scholars have argued that for an
entrepreneurship education program to be
effective, it must teach in entrepreneurial ways
(i.e., Honig, 2004; Kuratko, 2003; Politis,
2005; Welsh & Tullar, 2014). Although class-
based knowledge input is a vital component of
learning, the traditional lecture-based didactic
pedagogy alone is not sufficient (Cooper,
Bottomley, & Gordon, 2004). Sherman,
Sebora, and Digman (2008) pointed out that
traditional approaches such as reading the text
have little impact on a student’s decision to
choose entrepreneurship as a career, while
activities that are more experiential in nature, or
with more hands-on activities, pique students’
interest in becoming entrepreneurs.

To achieve real understanding of the meaning
of entrepreneurship, new pedagogical
approaches that embrace active and
experiential learning, such as student business
start-ups, live cases and simulations, should be
incorporated into teaching (Honig, 2004;
Kuratko, 2005; Ronstadt, 1987). Studies
reviewing entrepreneurship programs around
the world found experiential activities have
been widely utilized to increase the depth of
the program, including guest speakers focused
on entrepreneurship/small businesses; business
plan competitions; student club/organizations
focused on entrepreneurship/small businesses;
internships focused on
entrepreneurship/small businesses; on-site
visits focused on entrepreneurship/small

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businesses; and feasibility studies (Wilbanks,
2013; Winkel, Vanevenhoven, Drago, &
Clements, 2013. Research also has
demonstrated that experiential learning
opportunities increase students’ desire and
intention to become an entrepreneur (Fiet,
2000; Peterman & Kennedy, 2003); enhance
their self-awareness and recognition of their
entrepreneurial abilities and weaknesses
(Fuchs, Werner, & Wallau, 2008, Harris &
Gibson, 2008; Matlay, 2006); increase their
skills in identifying opportunities (Corbett,
2005); and develop their social skills
(Dhliwayo, 2008).

An experiential learning approach can be
delivered in different forms to expose students
to concrete experience. The most common
approach used by college educators is the
creation of business plans (Ronstadt, 1987).
Many entrepreneurship courses include
activities such as visiting small businesses,
guest speakers, case studies and projects
related to the development of a business that
give students the opportunities to grasp the real
work of entrepreneurship (Gorman et al., 1997;
Vesper & McMullan, 1988). Business ventures
on campus, entrepreneurship internships, or
co-operative education, also allow students to
develop their skills and knowledge in
entrepreneurship. For the purpose of this paper,
three core instructional design factors were
hypothesized to have effects on the
entrepreneurial propensity of students studying
entrepreneurship at the university:
Experiential Learning (EL), Teamwork, and
Quantitative focus. These have been
hypothesized to have independent effects on
the five task motivation constructs outlined in
this paper. The following hypotheses were
tested:

Hypothesis 1
There are statistically significant
differences in entrepreneurial
propensity between students exposed to
courses adopting experiential learning
and those exposed only to traditional
learning designs. Specifically,
Achievement, Change, Feedback, Goal
Setting, and Risk Taking scores will be
higher for experiential learning
courses than for traditional learning
designs.

Hypothesis 2
There are statistically significant
differences in entrepreneurial
propensity between students exposed to
courses with team-work and those
without team-work learning designs.
Specifically, Achievement, Change,
Feedback, Goal Setting, and Risk
Taking scores will be higher for
teamwork-based courses than for non-
teamwork based learning designs.

Hypothesis 3
There are statistically significant
differences in entrepreneurial
propensity between students exposed to
quantitative courses and those exposed
only to non-quantitative courses.
Specifically, Achievement, Change,
Feedback, Goal Setting, and Risk
Taking scores will be higher for
quantitative courses than for non-
quantitative courses.

METHODOLOGY

Sampling
The setting of the data collection was the
experiential Learning Pilot at the University of

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North Carolina at Greensboro. The B.S. in
Entrepreneurship launched in the fall of 2009
and the reconfigured minor for business and
non-business students launched the fall of
2008. The purpose of the Entrepreneurship
program is to produce graduates that are
globally ready by equipping them with
Entrepreneurship skills for the 21st Century
(Welsh, 2014). An innovative curriculum was
built on existing faculty strengths in the
business school and across the University.
Students have the opportunity to choose a
profile based on one of seven entrepreneurship
areas based on research by one of the authors
on where careers are headed for the next
twenty years: Creative Industries
Entrepreneurship, Family Business,
Franchising, Health Care Entrepreneurship,
International Entrepreneurship, Science,
Innovation, and Technology, and Social
Entrepreneurship.

As of fall 2014, there are 46 undergraduate and
graduate courses available in 26 departments
with three more being proposed for 2015,
which will bring the total to 49 courses in 26
departments. Majors, minors, and graduate
students have the opportunity to take elective
courses in the above areas. To our knowledge,
this is the second largest number of cross-
disciplinary courses developed at a school of
our size and stature in the United States;
Washington University in St. Louis, Missouri
has the most courses available. It is the largest
cross-disciplinary program in the State of
North Carolina. As of fall 2014, there are
approximately 130 majors and 90 minors,
business and non-business students, in the
program.

Sample Design. As noted, student scores for
five constructs, Change, Risk, Goal-setting,
Feedback, and Achievement, were obtained
from students at the end of their
entrepreneurship courses. For the purpose of
this study, the initial dataset was refined in
multiple ways to ensure the usability of the
input data for analysis. The final dataset
resulted in the following proportions by
course:

• ENT 200 Intro to ENT Finance
(n=13)

• ENT 201 Creativity, Innovation
(n=13)

• ENT 240 Intro to the ENT
Experience (n= 7)

• ENT 300 Feasibility Analysis
(n=55)

• ENT 337 Family Business (n=16)

• ENT 342 International
Entrepreneurship (n=15)

Three major learning designs emerged from a
manual content review of the sample course
syllabi: experiential learning, teamwork-
oriented learning, and quantitative-focus
learning (see Table 1). The determination of
where to place each course on these
instructional design factors was made based on
manual content analysis of the course syllabi
by two researcher faculty with follow up expert
validation with course instructors. The seven
courses were assigned systematically a value
of either 1 or 0 for each instructional design
factor; for example. ENT 300 and ENT 337
were assigned a 1 for experiential learning and
all other courses were assigned a value of 0.

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In projecting which of the courses followed
an experiential based design, we evaluated the
percentage of graded work falling into
experiential activity versus traditional
assessment (tests, quizzes). Two courses,
ENT 300 and ENT 337, had respectively only
32 and 35 percent of course grades attributed
to tests and quizzes, reflecting a strong use of
experiential activities for teaching and

assessment purposes. The other courses each
has 70 percent or more of course grade being
based on tests and quizzes. Teamwork and
quantitative methods were determined by
verifying the teaching methods and stated
learning outcomes, again reviewing syllabi to
assign courses to each category on these two
variables.

Table 1
Classification of Entrepreneurship Courses on Learning Designs

Course # Course Topic EXPERIENTIAL TEAM QUANTITATIVE

ENT
200

ENT Finance X

ENT
201

Creativity/Innovation X

ENT
240

The ENT Experience X

ENT
300

Feasibility Analysis X X

ENT
337

Family Business X X

ENT
342

International ENT

Instrument Development for Collection of
Dependent Variable Student Scores
The constructs measured are: Change, Risk
Taking, Goal Setting, Feedback, and
Achievement. Our constructs are based partly
on McClelland’s Need for Achievement
(1962) scoring system and partly on the Miner
Sentence Completion Scale Form T. Task
Motivation Theory (Miner et al., 1989)
usually deals with the fit between a person’s
motivation and the organization. In this case,
it is more appropriate to examine the fit
between the person’s motivation in class and
the entrepreneurial role (Miner et al., 1989).

While we believe that Task Motivation Theory
(Miner et al., 1989) is a good approach, we
argue that Miner and colleagues’ measure is
not entirely suitable for the measurement of
students. The sentence stems include items
such as, “When I fill out my tax return . . .” and
“Profit and loss statements . . .” Obviously,
these are things that traditional students have
little or no experience with. In order to follow
this approach, we found it necessary to change
many of the sentence stems. We converted the
sentence completion feature of the revised
Miner et al. (1989) measure to a multiple
choice format. This was done to make our
measure more readily usable across curricula.

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The sentence completion format takes a
considerable amount of training to score, and
scoring, even after training, is always a
laborious process. We revised the dimensions
by Miner et al. (1989) somewhat to make the
test more “student friendly.”

We made up sentence stems to fit the
constructs using some of Miner’s wording and
some of the wording from McClelland’s TAT
scoring instructions. We gave these sentence
stems to a sample of 80 MBA students. The
students were instructed to complete the
sentences with the ending that first occurred to
them. Then we took the most common student
completions and had a group of 12 different
MBA students scale the completions on a five
point scale from most positive to most
negative.

From the scale scores, we were able to find the
two most positive statements to go with each
sentence stem, the two most negative
statements to go with each stem, and two
statements that showed no affect at all but
were merely statements of fact. In doing this,
we had a 40 item multiple choice assessment
which yielded scores on the five constructs
mentioned above. Each construct is measured
with eight different sentence stems, so a
construct score could range from -8 to +8. We
attempted to get the negative and positive
statements to be approximately equal in
deviation from zero.

Validity and Reliability.

The validity of the Task Motivation Theory
Scales relies on the work of Miner &
colleagues and McClelland. Our items are
directly derivative of Miner’s MSCS form T

constructs. We argue that they are content
valid in that they include most of the same
verbal content as Miner’s scales.

We also had six MBA students sort the items
from our Entrepreneurial Propensity Scale
into the various scale categories. They sorted
the items with a 91% success rate into each of
the nine scale categories. We have had two I/O
psychologists sort the items into the scale
categories. They had an 86% success rate of
classifying the items as we have. On the basis
of where the items derived from and the ability
of students and professionals to recognize
where the items fit, we argue that the scales
are content valid.The descriptive statistics for
the constructs are shown in Table 2. The Alphas
are somewhat low, but we argue that given this
method of measurement, it is difficult to
produce higher alphas. This is so because the
participant taking the assessment would have a
hard time understanding what is being
measured. We also tried to make the social
desirability of the choices approximately the
same even though some of them are undesirable
as entrepreneurial answers. For instance, in
answer to the stem “Inventing something new .
. .” the possible answers are a. is very difficult,
b. is something I excel at, c. is good for the
market, d. is fun and exciting, e. is something
I’m not interested in, and f. is important for
economic growth. Choices a and e are scored -
1. Clearly, people who choose these two
options are not interested in inventing a new
product. Choices c and f, while positive, are just
statements of fact and are therefore scored zero.
Choices b and d show positive affect toward
inventing something new and are therefore
scored as +1. Each construct is measured with
eight different sentence stems, so a construct
score could range from -8 to +8. We attempted
to get the negative and positive statements to

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produce approximately equal in deviation from
zero. However, as may be seen in Table 2, we
have a positive bias in our scales. This may be
due to the fact that all our participants are

entrepreneurship students. We might expect
students with other majors to score lower on
these scales, closer to zero.

Table 2
Descriptive Statistics of Entrepreneurial Propensity Constructs (n = 1076)

Construct Mean
Standard
Deviation

Cronbach’s
Alpha

Change 1.45 2.46 0.627
Risk Taking -0.09 2.13 0.680
Goal Setting 2.43 2.22 0.560
Feedback 3.77 2.52 0.589
Achievement 2.52 2.51 0.652

Table 3 shows the correlations among the
constructs. The strongest correlation is
between Feedback and Achievement. The fact
that these two scales are moderately correlated
is not surprising given the emphasis on
feedback in most of the literature on n
Achievement. With a sample this large,

significance is not much of an issue since even
small correlations are significant, but Risk
Taking is only related to Change significantly.
That correlation is very small at just .08 and
the other three correlations are very close to
zero.

Table 3
Intercorrelations among the Entrepreneurial Propensity Constructs (N= 1076)

Construct Risk Taking Goal Setting Feedback Achievement

Change .080* .152* .223* .284*
Risk Taking .030 -.036 .052
Goal Setting .336* .289*
Feedback .402*

* p < .05

RESULTS AND DISCUSSION
T-tests were utilized to determine whether
any statistically significant differences exist
in terms of students’ entrepreneurial
propensity scores among the three learning

designs. Considering Table 4, we find
moderate evidence to confirm Hypothesis 1
effects of experiential learning designs for
goal-setting and weak evidence for
feedback, but not for the change, risk, or
achievement scores.

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We found very slight evidence (see Table 5)
for Hypothesis 2, i.e., that teamwork affected
achievement in a negative direction. We found

no evidence (see Table 6) for Hypothesis 3,
i.e., that a heavy quantitative focus of a course
impacted any of the five entrepreneurial
propensity measures in any significant way.

Table 4
Experiential Learning versus Non Experiential Learning courses

ENT
Propensity

Measure
Experiential

Learning

Non Experiential

Learning

value

× SD N × SD N

Change 1.79 2.376 66 1.98 2.881 44 -.376 .708

Risk -.18 2.246 66 -.39 2.212 44 .471 .639

Goal-setting 3.17 2.116 66 2.27 2.039 44 2.202* .030

Feedback 4.35 2.587 66 3.41 2.433 44 1.910** .059

Achievement 2.52 2.362 66 2.70 2.673 44 -.391 .697

*p<.05; **p<.1

It is notable that experiential learning produces greater goal setting motivation. Apparently, the
more tangible aspects of experiential courses boosts a student’s need to set goals. In addition, it
appears that Feedback needs are considerably higher in experiential learning courses.

Table 5
Team-based versus Non Team-based courses

ENT
Propensity
Measure

Team-based
Learning

Non Team-based
Learning

t
value

p
value

× SD N × SD N

Change 1.73 2.485 83 2.26 2.863 27 -.917 .361

Risk -.24 2.223 83 -.33 2.270 27 .187 .852

Goal-setting 2.89 2.130 83 2.56 2.118 27 .713 .477

Feedback 4.10 2.658 83 3.59 2.223 27 .888 .376

Achievement 2.36 2.518 83 3.30 2.267 27 -1.716** .089

**p <.1

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The only significant, albeit weak, result in
Table 4 is that of Achievement. It is not
surprising that Achievement motivation is
higher in courses where students are not

assigned to teams. Individual Achievement is
what is measured by our Achievement scale,
and such a motive cannot be taught well in a
course that emphasizes group work.

Table 6
Quantitative versus Non Quantitative courses

ENT
Propensity
Measure

Quantitative
Learning

Non Quantitative
Learning

t
value

p
value

× SD N × SD N

Change 2.23 3.492 13 1.81 2.451 97 .545 .587

Risk -.38 1.938 13 -.25 2.269 97 -.208 .836

Goal-setting 2.62 1.557 13 2.84 2.192 97 -.349 .728

Feedback 3.92 1.553 13 3.98 2.669 97 -.111 .913

Achievement 3.23 2.166 13 2.51 2.517 97 .990 .324

In the comparison of quantitative with non-
quantitative courses, we find no significant
differences. This is not unexpected.
Whether or not a course is quantitative has
little to do with the motivations of our five
constructs. In the distinction between
quantitative and non-quantitative, we are
focusing on cognitive knowledge acquisition
rather than motive strength. We argue that
courses that create affect are more likely to
show differences in our motives.

The present results provide limited evidence
for the proposition that experiential learning
produces greater levels of entrepreneurial
motivation. This makes logical sense and
reinforces a trend that has been growing in
recent years. Cognitive declarative
knowledge may well improve an
entrepreneur’s chances of succeeding, but it
does only a little to help him/her to want to

succeed in his/her own business. Experiential
learning is more motivationally directed, so
we should not be surprised that it has an effect
on student motivation.

On the other hand, team-based courses may
actually inhibit the Achievement motive. This
is a finding that needs further investigation. If
it is true, and if it is also true that Achievement
motivation is a good predictor of success in
entrepreneurial activity, then we may need to
rethink our pedagogical strategies for teaching
entrepreneurship courses. Assigned group
work may dampen the Achievement motive
because the student doesn’t have the
opportunity to produce results that are
identifiably his/her own—and thus the pull of
Achievement cannot be found. The literature
also indicates that entrepreneurs view
interpersonal relationships largely as ways to
assemble needed skill and funding resources

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and tend to prioritize competence of others
over other social traits (Stuart & Sorenson,
2007). Thus, when teams are created without
careful communication of the added value of
teammates on a project, students may view
teams as hindrances rather than helpful.

We should not be at all surprised that cognitive
declarative knowledge in the form of
quantitative vs non-quantitative courses
shows no difference in terms of motives.
Cognitive declarative knowledge and
motivation are different things.

IMPLICATIONS FOR ACADEMIC
FACULTY AND BUSINESS

PRACTITIONERS

Experiential learning has been a growing idea
in entrepreneurship education in recent years.
These data provide good reasons to think this
trend is good for students in entrepreneurship
courses. Though very preliminary, it does
appear that experiential learning courses in
our sample foster entrepreneurial motivation
better than other styles of pedagogy. Two
ways in which one commonly assesses or
monitors student’s development of
entrepreneurial propensity in courses have
been noted in the academic field: rubric-driven
instructor feedback and self-reported student
profile instruments. This paper sought to
validate the latter as a tool to compare
different pedagogical techniques.

Such forms of assessment keep students/teams
aware of their academic mission and remind
them that course experiential activities have
academic learning goals beyond the resume
worthy experience and networking
opportunities. Since the instructor cannot
completely control the learning environment

during some experiential activities, the type
and quantity of instructor monitoring of
results become vitally important. The goal is
to promote systematic feedback to students on
constructs relevant to entrepreneurship by
specifically addressing the five relevant
constructs of change, risk, goal-setting,
feedback, and achievement. In our case, this
set of constructs has been converted into sets
of behavioral and attitudinal scale items that
students can use to self-report on their
propensity for entrepreneurial thinking and
motivation. The implications for faculty are
that these scores can be used to examine
instructional pedagogies and refine them in
order to promote increased entrepreneurial
propensity in students.

The onus on academic programs in
entrepreneurship is to prepare students for
future careers and innovative activity leading to
the creation of new businesses. With this in
mind, we believe that the careful examination
and continuous improvement of academic
pedagogies in entrepreneurship will yield more
and better entrepreneurs and intrapreneurs for
the variety of business fields that our students
will enter. We also believe that by linking
entrepreneurial propensity improvements to
experiential learning activities involving
entrepreneurship experts and partner
businesses, we strengthen the potential for
strategic partnerships between the academe
and the field of practice.

CONCLUSIONS AND
RECOMMENDATIONS

As noted, there is a dearth of research that
investigates the impact or effectiveness of
different pedagogical methods for teaching
entrepreneurship. This paper focused on

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closing that gap by studying the impacts on
critical measures associated with
entrepreneurial propensity of three learning
design choices: experiential learning, use of
teamwork, and focus on quantitative methods.
Experiential learning was defined as student-
centered instruction through the use of active
participation of students, rather than teacher-
centered instruction via lectures and testing.
The constructs measured comprised Change,
Risk Taking, Goal Setting, Feedback, and
Achievement following the tenets of Task
Motivation Theory.

As discussed, we found moderate evidence to
confirm effects of experiential learning
designs for goal-setting and weak evidence for
feedback. While an interesting finding, this
study represents a relatively small sample due
to the difficulties of managing instructor and
student engagement with the entrepreneurial
propensity survey. The authors plan to
continue collecting data from students to
increase the sample size and provide insight
that will support the impact of pedagogical
methods on enhancing students’
entrepreneurial propensity. Further research is
clearly needed to clarify the relationship and
answer additional questions of interest: What
kinds of activities instill the most motivation?
Can we design experiential learning that will
increase the Change, Risk, and Achievement
motives? Should all entrepreneurship
courses include some experiential instruction
and what is the proper weight to assign to this
critical activity? Further research and
consistent results along these lines could make
entrepreneurship education stronger and more
efficacious than it now is.

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Dr. Bonnie Farber Canziani holds a Ph.D.
from Cornell University in Hotel
Administration. Her teaching and research
spans services management and marketing,
revenue management, and wine industry
strategy and marketing. She has held
numerous positions relevant to academic
assessment and the furtherance of teaching
and learning excellence in higher education.
Additional research areas include assessment
of complex competencies such as critical
thinking in student consulting projects,
entrepreneurial propensity, sustainability,
and global competence.

Dr. Dianne H.B. Welsh is the Hayes
Distinguished Professor of Entrepreneurship
and Founding Director of the Entrepreneurship
Programs at The University of North Carolina
Greensboro. She is the 2015 Fulbright-Hall
Distinguished Chair for Entrepreneurship for
Central Europe. Dianne is a recognized scholar
in family business, international
entrepreneurship, women-owned businesses,
and franchising and has seven books and over
150 publications. Her books include Creative
Cross-Disciplinary Entrepreneurship,
published by Palgrave-Macmillan, and the 2nd
edition of Global Entrepreneurship and Case
Studies in Global Entrepreneurship.

Dr. Yuchin (Jerrie) Hsieh received her Ph.D.
in Hospitality and Tourism Management from
Purdue University in 2004. Prior to joining
academia, she worked for five-star hotels in
Taiwan and the Netherlands. Her research
interests include hospitality-related human
resources, and hotel employees’ occupational
health.

Dr. William Tullar is a Professor of
Management at the University of North
Carolina Greensboro where he has taught for
40 years. He obtained his Ph. D. in
Industrial/Organizational Psychology from the
University of Rochester. Professor Tullar has
been a Fulbright Scholar to Germany, and a
visiting Scholar in Moscow, Russia, Worms,
Germany, Ludwigshafen, Germany, and
Chisinau, Moldova. He has consulted widely
both in the U. S. and in Europe. He has
published numerous articles and book chapters
on various aspects of management, most
principally on human resource management
and development.

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