Constructivistic Entrepreneurship Education

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4 The microfoundations of entrepreneurial learning
and . . . education: the experiential essence
of entrepreneurial cognition
Norris F. Krueger, Jr

Experience is not what happens to you, experience is what you do with what happens to you.
Epictetus

Introduction
Knowing a lot about entrepreneurship is hardly sufficient to make one a successful entre-
preneur, ‘knowing a lot’ can even be dangerous. Knowledge is not just an accumulation
of data; knowledge requires both the information content and the structure by which we
organize it. All too often in our haste to transfer large amounts of important content to
students, we lose sight that the knowledge structures are even more important and our
ability to influence how students’ mental models evolve is the essence of education.
Perhaps nowhere is this as visible as in entrepreneurship education, where we must
go beyond teaching facts and teach students how to think like an entrepreneur, to help
them toward a more expert entrepreneurial mindset. One way to do that is to situate
entrepreneurship education in settings where mental models are not shared, where there
is cognitive diversity, that is, a significant diversity of knowledge structures. The success
of cross-campus entrepreneurship programs may derive in large part from the inherent
cognitive diversity of its students and teachers.
As entrepreneurship educators, we are not training memories, we are training minds.
Education changes students; entrepreneurial education is no different. Here, more than
anywhere, we can assess that change and we can use that assessment to nurture our
students’ education. Many of our best teaching and training methods visibly affect how
students think about entrepreneurship. Of any business discipline, can one readily envi-
sion classes where experiential learning does not dominate in the way it typically does in
entrepreneurship teaching?
The rise of cross-campus programs in entrepreneurship now offers a golden opportu-
nity to explore this, given the greater cognitive diversity of students who come from dif-
ferent majors, different academic levels and even different physical locations. However,
we first need to step back and look at the microfoundations of entrepreneurial learning.
We offer here a primer of how the constructivistic paradigm of education applies to entre-
preneurial learning; we also hope that it provokes significant discussion about what are,
and how we might test, the drivers of cognitive change in entrepreneurship learners.

Constructivistic, not behavioristic
Genuine experiential education changes what learners know but even more importantly
how they know it. Teaching content is often behaviorist in nature, but to change how we
think requires a more constructivistic mode of education. Constructivistic approaches

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36 Handbook of university-wide entrepreneurship education

change more than what students know, they change how they structure that knowledge. If
entrepreneurial education often includes highly constructivistic methods, we can thus make
the case that entrepreneurial education can have significant, positive impacts on learning.
However, this then requires us to consider some new questions as we design, imple-
ment and assess entrepreneurship education. What is the change we are attempting to
induce? We argue here that it is logical to assume that we want to help learners move
from a more novice mindset toward a more expert mindset as entrepreneurs. To be spe-
cific, we want to help learners move from being novice to expert thinkers!
Considerable research has explored how experts become expert (Ericsson and
Charness, 1994), studying chess grandmasters to musicians to pole vaulters. What do
all experts share? They may know different things, but what really differs is how they
structure their knowledge. Also, there are consistent cognitive processes that develop
those deep knowledge structures, processes that we need to take explicit advantage of in
our teaching and training.
Thus, we need a better understanding of what course (and curricular) activities influ-
ence what cognitive changes. We must also understand what cognitive changes are
most desired (and it would not hurt to have a better understanding of what cognitive
mechanisms are involved in moving learners toward being more expert entrepreneurial
thinkers).

Entrepreneurship education is inherently constructivistic
Entrepreneurship faculty members all want to believe that there is something ‘special’
about what they do in the entrepreneurship classroom (Fayolle and Servais, 2000). The
expectation is that the applied, hands-on nature of class assignments helps students
to think entrepreneurially, to see themselves truly as entrepreneurs. State-of-the-art
educational theory suggests that the bias toward experiential, action learning found in
entrepreneurship training reflects how humans actually learn complex, ill-structured
knowledge (Krueger, 2007; Gustafson, Chapter 5, this volume). In fact, these methods
reflect the cutting-edge educational theory of ‘constructivism’ – which is coming to domi-
nate the more familiar and traditional behavioral methods.

Genuine education changes how we think
Perkins (1994) argues that education needs to be ‘thinking-centered’ – reflecting the
reality that education truly involves changing how students think. Truly changing
students’ entrepreneurial thinking requires more than mere transfer and acquisition of
information and skills – students need to move toward a more expert way of structuring
that content. To do that, students must take ownership of these new skills and knowl-
edge. This requires significant change in deeper cognitive structures, not just changes in
knowledge content but also changes in how individuals structure knowledge.
Krueger (Krueger and Brazeal, 1994; Krueger, 2000) argues that an organization
seeking a more entrepreneurial climate requires more entrepreneurial thinking in its
members. Classrooms are no different. As with organizations, educators must seek to
develop a fertile seedbed that supports entrepreneurial thinking. This cognitive infra-
structure supports entrepreneurial thinking and the changes in cognitive structures such
as intentions and attitudes, and even deeper cognitive structures such as students’ per-
sonal mental models of ‘what is an entrepreneur? Am I an entrepreneur?’.

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The microfoundations of entrepreneurial learning and education 37

We must care about these deeper structures. If we are to truly stimulate entrepreneur-
ial thinking in a fundamental way, then it is likely that there will be important changes
in students’ thinking, including deeper cognitive structures that reflect how humans
represent and process information. Mere transfer of information is insufficient to fun-
damentally alter behavior. This has important implications for learning how to think
entrepreneurially.
Despite a very extensive – and largely descriptive – literature of entrepreneurship
education, academics have been less successful at researching how entrepreneurs actu-
ally learn (for example, Alberti et al., 2004). The descriptive work done in entrepreneur-
ship education has, of course, proven of great benefit. The next step for researchers
is – as is now being done with intentions – to be much better grounded in educational
theory.

Learning and constructivistic education
There are two dominant paradigms in education. The traditional ‘behaviorist’ approach
focuses on fact-based learning (including rote memorization, repetitive drilling and
similar mechanisms that focus on transferring content knowledge). Instructors typically
provide the models and the framework for knowledge being transferred to students.
In contrast, the constructivist approach argues for situated learning where students
must develop their own ways of organizing the knowledge (building and changing their
own mental models to represent knowledge) as they acquire it. The labels ‘learning the
answers’ versus ‘finding the questions’ are one way to think about the difference; the
author prefers the words of W.B. Yeats about learning. Entrepreneurship educators, it
seems, much prefer ‘lighting a fire’ to ‘filling a vessel’. And this makes perfect sense in
terms of cutting-edge educational psychology.
Traditional methods provide greater control to the instructor and can appear as more
efficient for large groups of students. Constructivistic methods tend to be much more
student centered, but this reflects how humans actually learn in daily life: by trial and
error in a social setting. Moreover, if one wishes to change deeper cognitive structures
such as scripts, then more student-centered learning is imperative. Albert Bandura’s
social learning theory (for example, 1994) posits learning as an iterative change process
by which deeply held beliefs and attitudes co-evolve as learners actively acquire, process
and organize new knowledge. That is, students and teachers alike learn from each other
– not just facts, but from each other’s mental models. The more cognitive diversity, the
more opportunities there are to learn from one another.
The number one objective of constructivistic education is deep understanding, the
more surface-level skills will follow naturally. Obviously, the more complex the skills
required, the more advantageous it is to be constructivistic. Constructivism thus appears
essential to nurturing an expert. Moving toward becoming a more expert entrepre-
neurial thinker is not easy, nor is teaching this. How do we provide critical development
experiences for students that accelerate change toward more expert deep knowledge
structures?

How knowledge evolves
Again, knowledge is not just an accumulation of data; knowledge requires both the
information content and the structure by which we organize it. But, this raises one critical

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issue: to advance a learner’s knowledge almost always requires confronting significant
discrepancies and contradictions. Prior knowledge, assumptions and beliefs may prove
problematic, even dysfunctional. Constructivistic education offers mechanisms for
helping learners confront and learn from challenges and resolve contradictions in their
constructed knowledge base. In fact, progress generally requires an ongoing, iterative
process of construction and re-construction of knowledge. Consider Thomas Kuhn’s
The Structure of Scientific Revolutions (1962) where he describes a parallel phenomenon
of how a strongly held shared mental model (the ‘paradigm’) evolves in a scientific field.
Another parallel lies in the difference between transactional and transformational leader-
ship; too much of education is transactional, despite recognizing that true learning is sig-
nificantly transformational. A final useful parallel is the process of participatory action
research where research subjects become co-investigators.
A big part of being an expert is knowing what you do not know; a big part of staying
an expert is continuing to reassess how one structures knowledge and the deep beliefs
that anchor those structures. While teachers may intend to assist students toward more
expert thinking, they need to model the same learning and openness to cognitive change
that they desire in students. In constructivistic classrooms, the teacher–student distinc-
tion is thus blurred mindfully; both are learners, both are teachers.
The net result is that we are providing learners with the opportunity and environment
to change not just what they think, but how they think (see Figure 4.1). This is important.
We need to help students change how they structure what they know about entrepre-
neurship. This requires giving them opportunities for critical developmental experiences
that help them to re-shape their mental models.

Change in what we know (content)

Entrepreneurial
No vice Mindset Expert

Change in how we know it
(knowledge structures)

Critical Developmental Experiences

Source: Adapted from Krueger, (2007).

Figure 4.1 What we really do in entrepreneurship education

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Thinking-centered learning
Learning is a process by which we construct meaning jointly from our context and from
informational cues. Construction of meaning occurs within the learner rather than
simply a process of assimilating information from the environment. Learning is situ-
ated, though. That is, learning is independent of neither the context nor the learner. The
landmark research of Jean Piaget and his successors demonstrates clearly that learning is
not a literal transfer of knowledge from teacher to student. Learners of any age construct
new knowledge by integrating the new data into relationships with prior knowledge,
connecting new information in more than one way. Knowledge is thus constructed as
an interrelated whole, not as a set of isolated brute facts. Thus, master educator David
Perkins’s (1994) felicitous phrase ‘thinking-centered learning’ proves most appropriate.

Constructivism and the learning cycle
Research has clearly identified a natural learning cycle: first, we discover an issue (and
its seeming implications), next we identify critical concepts that may help us explain the
phenomenon in question, and finally we seek to apply our newly constructed knowledge
and test it against reality (ibid.).
The natural learning cycle assumes that ‘big ideas’ and ‘big questions’ are inherently
complex. Perhaps oddly, we need complexity to accelerate learning. Oversimplification
can actually confuse us when we first confront a ‘big idea’. Only after we have immersed
ourselves in the problem is it useful to move to a more reductionist approach to isolate
key principles. Then, as we struggle to apply the key principles that we have extracted, we
return to more complexity. Finally, we must evaluate our resolution to the problem and
re-think the process anew, actively seeking contradictions and counter-examples. Note
we use the word ‘resolution’ instead of ‘solution’. The word ‘resolution’ captures both
the iterative nature of the learning process and the recognition that few perfect solutions
exist. It also illustrates the dialogic nature of learning a concept. However, as Prawat
(1992) notes, students’ exploration still requires some sort of ‘road map’. Instructors
need to provide focus and coherence to prevent the breadth of inquiry from degenerating
into unproductive wandering through trivia.

Key principles of constructivistic education
Constructivism’s five key principles follow the learning cycle (Brooks and Brooks,
1993):

1. ‘Authentic’ (and ‘important’) questions Learners need to ‘own’ their knowledge,
thus they need to find their ‘own’ problems in a given subject area. Educators can
assist by posing ‘authentic’ problems of emerging relevance to learners. This has the
further advantage of engaging learner emotions productively. For example: plan-
ning a desired new business takes on extra meaning when it is potentially ‘for real’
even though it often complicates our efforts.
2. ‘Big ideas’ We should structure learning around primary concepts, not minutiae. If
we light a fire with one or more primary concepts with which learners relate directly,
they will identify and adopt details as needed. We want students to grasp the essence
of a given phenomenon. For example: entrepreneurship is more than identifying an
opportunity, it is about understanding how we learn to see the opportunities that we

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do (and those we do not). A colleague of the author has introductory entrepreneur-
ship students (many with zero business courses) identify a small business innovation
research topic for a feasibility study – and students learn what personally they see as
opportunities, often in quite surprising fashion. This is a particularly welcome model
for classes including students from science, social science and/or engineering. (Arts
and humanities students might also be able to identify grant-based opportunities.)
Social entrepreneurship is thus a fast-growing topic in any entrepreneurship course
and is often the centerpiece for cross-campus entrepreneurship, as this Handbook
demonstrates. Where better to connect learners with big, authentic ideas?
3. Constructing meaning requires triangulation We should focus on and value learn-
ers’ different points of view; accommodating multiple perspectives often entails
team teaching. (This takes advantage of multiple types of intelligence in the class.)
For example: team projects that are designed to be truly interdependent force stu-
dents to bring their differing perspectives to bear in productive fashion. An even
better example is the action-learning model that allows students to see how ‘book’
knowledge squares with practice in hands-on situations (Leitch and Harrison, 1999).
Consider how the cognitive diversity in a cross-campus course requires negotiation
of often radically different mindsets.
4. Coaching, not lecturing The curriculum should follow students’ inquiries (their
process of constructing knowledge) not the instructor’s own process. (This does not
imply an ‘anything goes’ approach, however.) For example: informal interaction
between students and the instructor is critical; but so too is allowing (or requiring)
students to coach one another.
5. Assessment and evaluation techniques should reflect these processes They should not
reflect the ability to merely ‘regurgitate’. Also, different majors are accustomed to
often quite different modes of assessment and evaluation (for example, the portfolios
used in art). Why not ask students to negotiate the most efficacious metrics? For
example: assessment and evaluation processes themselves need to be assessed and
evaluated with student involvement.

Re-read the above list and consider how these are reflected in a well-done analysis of a
case study or in a hands-on small business institute-type project. (The SBI approach uses
real businesses as a ‘live-ammo’ case.) We begin with a focus on ‘big ideas’ and authentic
questions in an environment that offers a ‘safety net’ (for example, it is acceptable to try
to fail). Learners will accept almost any challenge if they frame the learning situation
as an opportunity, but to perceive an opportunity requires perceptions of control and
competence that are very much in the eye of the beholder. How do we help them to frame
it as an opportunity? The instructor can foster and reinforce those perceptions, but a
student’s peers are equally important in promoting a sense of safety and of challenge.
Making it safe for students to explore is more difficult than we realize and requires con-
stant vigilance. For example, too much visible knowledge can actually impede knowl-
edge; if students see one possible answer, they can see it as ‘the’ answer. Similarly, if they
see the instructor as having ‘the’ answer, learners may focus on extracting that answer.
The author can attest that instructor ego can be problematic. As such, the constructivists
suggest emphasizing questions that clearly have no one single answer. Sound familiar?
The human mind comprises an ever-evolving set of cognitive structures that help us

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Table 4.1 A simplified view of how modern pedagogy has evolved

(more behavioristic)
Key theory Core assumption Key activity Sample tool
Teacher-centered Expert teacher; passive student Memorization Fact-based lectures
Teaching-centered Expert teacher; active student Skill development Pro formas; business
plans
Learner-centered Learners need to control Teacher–student Case studies
learning process (student as interaction
customer)
Learning-centered Metacognitive understanding Problem-based Self-managed field
of learning (from what we learning projects
know to how we know it)
(more constructivistic)

Source: Adapted from Krueger (2007).

make sense of our environment and our place in that environment. This includes per-
ceptions of opportunity; we increase the potential for entrepreneurial behaviors if we
increase the perceived range of possible opportunities (Krueger and Brazeal, 1994). If we
accept this cognitive framework, we must, however, abandon much of the behavioristic
tradition that still dominates educational theory and practice (for example, Table 4.1).
Learning is not just a stimulus-response phenomenon (Langer, 1994). Memorizing facts
or other mimetic activity is not learning; brute facts without context offer little meaning
beyond ‘We need to know this for the next test!’.

Entrepreneurial learning in practice
The literatures on entrepreneurship, small business, family business and so on all offer
considerable evidence that supports the constructivistic paradigm. Bouchhiki argues
explicitly that entrepreneurs appear to construct their environments (1993) while Jelinek
and Litterer (1995) describe in great detail how a truly entrepreneurial organization
encourages its members to construct an opportunity-friendly cognitive infrastructure.
Perceptions of self-efficacy, something that constructivistic learning is better at develop-
ing, are already closely linked to entrepreneurial intentions (Krueger et al., 2000), oppor-
tunity perceptions (Krueger and Dickson, 1994), venture performance (Chandler and
Jansen, 1992), and entrepreneurial career choice (Scherer et al., 1989). We also see evi-
dence that entrepreneurial performance is associated strongly with ability in self-directed
learning (Guglielmino and Klatt, 1993). Finally, recall that entrepreneurs appear to be
motivated far more by intrinsic (for example, autonomy, mastery) than extrinsic (for
example, money) considerations (Brockhaus, 1987). These all suggest that if the entre-
preneurship-friendly cognitive infrastructure is constructed, then it makes a lot of sense
to emphasize learning that is consonant with the constructivist model. If entrepreneur-
ship education works in theory, then it should also work in practice.
Consider the range of best practices that the field of entrepreneurship has developed.
While beyond the scope of this chapter, it would be relatively easy to examine, for
example, award-winning pedagogies and see the inherently constructivistic principles

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at work. Many awardees place novice learners in learning situations where they do not
answer questions; they must first identify the proper questions. Rather than fulfill a
relatively well-structured task such as ‘write a business plan for your client’, the students
must first assess what tasks would solve the client’s seeming problem (and may need to
assess whether the apparent problem is a root cause or merely a symptom).
True problem-based learning (PBL) is much more than ‘learning by doing’, as power-
ful as that may be. Students are forced to structure the problem and the knowledge and
skills required (again, as we see prevalent in medical and legal training). Consider, too,
the very nature of PBL. We know that genuine PBL enhances students’ entrepreneurial
thinking to a remarkable degree, even showing evidence of changing knowledge struc-
tures in a few months (for example, Krueger, 2001; Hanke et al., 2005; Souitaris, 2005;
Cooper and Lucas, 2007; Post et al., 2007; Tegtmeier, 2007; Chapters 11 and 15, this
volume). However, the particular value of PBL in entrepreneurship pedagogy is that
PBL requires learners to move from answer finding to question creating, to take personal
(cognitive) ownership of their projects. Faced with very high uncertainty, extreme time
pressures and competing demands on their time and effort, PBL mirrors what an entre-
preneur faces on a daily basis. As students proceed, their reflections invariably lead them
to that realization: the necessity for further improving their personal role identity as an
entrepreneur. (It would be difficult for me to sustain any mental prototype of ‘entrepre-
neur’ that does not include ‘me’.)
If we are therefore to assist novice entrepreneurial thinkers to become more expert, we
need to apply some of the latest research on entrepreneurial cognition to address central
questions of how expert entrepreneurs differ, not just in terms of surface knowledge and
skills, but in how deep structures affect how they think.
How I think this discussion might apply in the entrepreneurship classroom centers on
what we are trying to achieve: we seek to develop more individuals with the entrepreneur-
ial mindset and, more importantly, to develop them better at being entrepreneurial. In
the language of cognitive science, we are helping novice entrepreneurs to become expert
entrepreneurs. Observers such as former Inc. editor George Gendron1 have argued that
entrepreneurship has grown increasingly professionalized and, in turn, that entrepre-
neurs increasingly require assistance to help them grow as professionals. Whether or not
one considers entrepreneurship to be a profession, we now know that there are expert
entrepreneurs. As we improve our understanding of what differentiates the expert entre-
preneur, we also need to focus our pedagogy in directions that help students and trainees
to grow in that direction.
Along those lines, Jack and Anderson (1999) suggest that we should be creating
‘reflective practitioners’ with higher-level skills, both practical and cognitive. Creating
reflective practitioners requires more than the mere acquisition of information and skills.
Again, genuine knowledge is both the raw information and the structures by which we
organize that information. If we are to truly change our students’ entrepreneurial think-
ing, we must also help them develop new cognitive structures at a much deeper level. In
turn, this requires creating a cognitive infrastructure in the classroom that mindfully
facilitates such changes.
Tom Monroy was perhaps the first to articulate that traditional classroom methods
were not only less frequently used in entrepreneurship classes but they are less effec-
tive than more experiential approaches (Monroy, 1995). Rather we tend to emphasize

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‘problem-based learning’ where learners focus on real-world issues, a focus that is a
staple of most entrepreneurship courses. Indeed, the most popular and successful train-
ing techniques used in entrepreneurship tend to strongly reflect the constructivistic
model: living cases (for example, small business institute), business plans, shadowing and
so on (Krueger and Hamilton, 1996).
Garavan and O’Cinneide (1994; see also Alberti et al., 2004) published an interesting
overview of different entrepreneurship training programs as to key approaches used, key
constraints and so on and it illuminates the strong bias we have for hands-on, experien-
tial learning. In particular, action learning represents a model of education that seems
particularly applicable to entrepreneurship training (Leitch and Harrison, 1999). Action
learning is perhaps the most prominent incarnation of the constructivist model.
Much of constructivist pedagogy focuses more on cognitive phenomena, while action
learning focuses more on a set of techniques to facilitate that change. Creating Jack
and Anderson’s (1999) ‘reflective practitioners’ with both practical and cognitive skills
requires action learning’s iterative combination of both classroom and hands-on learn-
ing in synergistic fashion. Action learning is typically most efficacious in a team setting,
as befits the situated nature of the learning, especially a team setting that reflects consid-
erable cognitive diversity (for example, Chapter 11, this volume). Think Senge’s (1990)
cross-functional high-performance work teams.

‘Informed’ intent
Who would you bet on? An experienced, successful entrepreneur with a moderate intent
or a complete novice with an intense, even passionate intent? What can it possibly benefit
us if we increase students’ attitudes and intentions toward entrepreneurship, if we fail to
prepare them (or, worse, encourage them unrealistically). Increasing intent is one thing,
nurturing an informed intent is far more important (Krueger et al., 2007).
We have recently seen exciting research expanding the richness of our understand-
ing of entrepreneurial intentions and, in particular, the relevance to pedagogy and the
critical importance of expertise. As entrepreneurial expertise is increasingly important to
scholars and educators alike, why not ask about ‘entrepreneurial intent among novices
versus entrepreneurial intent among experts? If entrepreneurship is not fully recognized
as a profession, it certainly has become more and more professionalized. What does it
mean to be “expert” in the entrepreneurial domain? How can we help people get there?’
As entrepreneurship researchers and educators, we do not want to turn out entrepre-
neurs per se, rather we are attempting to help them become as expert as possible in the
skills and processes entrepreneurs need to exhibit. As educators we can assist them in this
journey from novice to expert and that is exactly what we need to be doing. But, that begs
the question of content – what should they be working to become expert at? The growing
body of work in entrepreneurial cognition argues persuasively that what differentiates
entrepreneurs is not necessarily knowledge content and even surface-level skills.
What differentiates entrepreneurs is entrepreneurial thinking; our job is to nurture stu-
dents into thinking like an expert entrepreneurial thinker. That requires changing some
very deep beliefs, deep assumptions that anchor our mental prototypes. To do that requires
giving students opportunities for critical developmental experiences (again see Figure 4.1).
Current research has focused on how entrepreneurial education changes intentions and
attitudes. Formal training/teaching does seem to matter in the emergence and evolution

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of entrepreneurial thinking. Nicole Peterman’s thesis work found that an entrepreneurial
training program significantly influenced the various antecedents of entrepreneurial atti-
tudes and intentions (Peterman, 2000). Even formal coursework (Cox, 1996; Krueger,
2001; Lucas and Cooper, 2004; Post et al., 2007; Tegtmeier, 2007) appears to have a
small but measurable impact on critical beliefs (for example, self-efficacy) and attitudes
(including intent).
Again, however, developing entrepreneurial thinking requires changes in deeper
cognitive structures. This offers us many opportunities to research the specific impacts
of different training activities and other experiences to further improve our learning
(Duckworth, 1986). Prior experience certainly influences perception of future opportuni-
ties (for example, Krueger and Brazeal, 1994). For example, we have some evidence that
growing up in a family business influences attitudes and intentions toward entrepreneur-
ship (Krueger, 1993; Delmar and Davidsson, 2000). Exposure to competitive sports
seems particularly potent in more collective-minded cultures (Neergaard and Krueger,
2005); one might even make the case that children’s fairy tales might affect deep beliefs
(Neergard and Smith, 2007). While it may be unrealistic to place students in their own
family business, what are the ‘lessons learned’ that we might replicate? (And that we are
likely doing already.)

Skills and self-efficacy
What are some critical developmental experiences that we can fruitfully offer? What spe-
cific kinds of skills, what specific kinds of training and what specific kinds of experiences
are truly transformative in terms of enhancing entrepreneurial thinking? For example,
Robert Baum and colleagues (Baum et al., 2001) found that a venture’s growth depended
on both specific motivations and specific skills of the founder. However, education
researchers argue that skills acquisition is necessary but not sufficient, whether acquired
via hands-on mastery or vicarious learning through behavioral modeling.
Learning a skill changes knowledge content, learning that one can use that skill suc-
cessfully can change how you structure knowledge. Learners must internalize knowledge
and skills to the point where they feel comfortable enough to apply them to new, even
highly risky situations. Self-efficacy theory (Eden, 1992; Bandura, 1993) suggests that
just acquiring skills is not enough to fundamentally change how we think, it also requires
believing in those skills (perceived efficacy versus actual efficacy). No self-efficacy, no
long-term skills acquisition – or skill usage.
However, self-efficacy without the actual skills hardly reflects an informed intent.
Bandura himself would also argue that acquiring the correct skills is also imperative for
long-term, sustained change in our thought processes as we move from a more novice
mindset toward a more expert mindset. In the entrepreneurship domain, we are begin-
ning to focus on identifying those skills that appear to make the most impact on sub-
sequent entrepreneurial behavior. These tend to also reflect changes in entrepreneurial
thinking. For example, opportunity identification often reflects relatively sophisticated
skills of counterfactual thinking. Based on this, Gaglio trains her students in advanced
counterfactual thinking techniques to increase their abilities to identify opportunities
(Gaglio, 2004). How better to expand students’ ‘what-if’ thinking than to have a broader
range of life, work and school experiences in the classroom, as you would find in a
cross-campus course.

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The entrepreneurship program at the University of Victoria (Victoria, BC) focuses
most of their activities explicitly on moving students from a novice entrepreneurial script
toward an expert script; the expert script serves as a guide to accelerate student progress
(for example, Morse and Mitchell, 2005). Baron’s (2006) argument that expert entre-
preneurs are better at ‘connecting the dots’ suggests that we find ways to train students
in related skills; and deliberate practice seems to be one such method (for example, see
Mitchell, 2005; Baron and Henry, 2006). However, this is a process that requires fairly
intense reflection, something that other majors are far more comfortable with – and can
assist business students.
For yet another example, Fiet and Barney (2002) show that certain key skills related
to identifying highly credible opportunities can be identified and taught, thereby raising
students’ self-efficacy at opportunity identification in a broader, more diverse range of
possibilities. This permits instructors to tailor experiential exercises to develop and assess
those skills. However, the more diverse the existing base of knowledge and beliefs that
the student have, the easier that task will be.

Deep beliefs
Finally, what is the essence of being successfully ‘entrepreneurial’? Expert entrepreneur-
ial thinking seems a critical perspective. Successful entrepreneurs should be character-
ized by an expert mindset. Evidence indicates that the content of an expert’s knowledge
base need not differ from that of a novice, but experts typically organize or structure the
content differently. This begs the question concerning how expert entrepreneurs struc-
ture their knowledge. Ericsson (for example, Ericsson and Charness, 1994) has shown
that while some individuals move from novice to expert, yet others do not. And, that
change manifests itself in significant changes in deep cognitive structures. One key impli-
cation of Ericsson’s work is that experts, including entrepreneurs, are definitely made,
not born. There may be some innate ‘hard wiring’ but expertise appears to be learned.
Some deep beliefs may coalesce at a very early age (for example, Neergaard and Smith,
2007) but they evolve over time (for example, Erikson, 1980).
The research also indicates that experts consistently and reliably follow recognizable
cognitive behaviors and processes (for example, Mitchell, 2005; Baron and Henry, 2006).
Consequently, if we want to understand entrepreneurship, then it is vital for the field of
entrepreneurship to learn as much as we can about what differs in the deep cognitive
structures of expert entrepreneurs (maps, scripts, schemas and so on and the deep beliefs
and assumptions driving them). When we gain a better understanding of how such deep
structures evolve, our ability to help entrepreneurs grows in parallel.

Cognitive diversity
In recent years, we have found remarkable new insights into how we learn to think
entrepreneurially. We have found constructs that fully moderate the intentions model.
For a striking example, differences in cognitive style can yield dramatically different
pathways in the formation of intent. That is, the intentions model for learners who
score as preferring intuitive thinking differs significantly from the model for those
scoring as preferring an analytic cognitive style (Krueger and Kickul, 2006). That
implies explicit consideration of differing cognitive styles among our students and,
given the constructivist paradigm, to encourage a broad range of cognitive style and

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other learning styles in our students. If the differences in something as simple as cog-
nitive style matters that much, then how about all the other ways that students may
differ cognitively?
What better way to do that than to have students from every imaginable major.
Barring that, we need to surface the unique mental models that all of us possess.
However, consider how business students can influence how non-business students
think; consider even further how non-business students can influence business students.
But first we must surface as much cognitive diversity as we can, then use that to
everyone’s advantage.

Building a constructivistic classroom

What teaching tools are constructivistic?
How do we actually implement a constructivistic curriculum? Again, let us turn to
Brooks and Brooks (1993):

A constructivist framework challenges teachers to create environments in which they and their
students are encouraged to think and explore. To do otherwise is to perpetuate the ever-present
behavioralist approach to teaching and learning. (p. 30)

[C]onstructivistic teachers seek to ask one big question, to give students time to think about it,
and to lead them to the resources to answer it. (p. 39)

In short, we need to focus much more on the learning process going on inside the
heads of the learners and less on filling those heads with details. If we improve the stu-
dents’ abilities to learn, the details will follow. Straight lecturing is far from optimal. A
charismatic instructor may ‘light a fire’ in students even in straight lecture mode, but be
assured the learning comes from the motivation not the details. Even testing should be a
significant learning experience. What do students learn from parroting the text or lecture
notes? From multiple-choice, true–false, or matching types of tests? They may even learn
that they do not do these kinds of test very well, reducing both their interest level and
their self-efficacy perceptions.

Operationalizing constructivism
Brooks and Brooks also offer 12 concrete steps to operationalize these principles. Let us
look at them in the context of the entrepreneurship classroom, where students engage in
hands-on projects that offer the potential for critical developmental experiences:

1. Explicitly encourage, accept, and honor students’ autonomy and initiative Self-
managed, self-organized work teams require that students take considerable
initiative.
2. Try to use raw data and primary sources as fodder for student inquiry Requiring
student initiative and responsibility also requires that the instructor give them the
authority to guide the direction of their own projects after launching.
3. Students’ tasks are to classify, analyze, predict, and create (not simply memo-
rize) Real-world projects inevitably involve both primary and secondary data
collection as grist for the students’ mill.

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4. Student responses on a topic should direct strategy and content of teaching The
projects (and essay exams) force the students to think critically, to integrate and
apply what they are learning with projects (and with past life, work and school
experiences).
5. Ask for students’ understanding before we give them our perspective They also
require that class discussions be centered around the students’ authentic questions,
often about how to apply a concept to their project.
6. Encourage dialogues between students and teacher, each other, family, even outsid-
ers The projects require students to discuss their efforts with each other, clients
and others in the community with the knowledge and expertise needed for the
project.
7. Ask open-ended questions; encourage students to also do so The exam takes this
approach, while experiential projects themselves naturally induce open-ended
questions (often to a harrowing degree). Moreover, students feel free to ask tough
questions of each other.
8. Ask for elaborations of initial responses Similarly, students in self-managed team
projects rarely let their peers give evasive answers (but are coached to be supportive
as well.)
9. Don’t accept quick answers; encourage reflection Similarly, giving the students two
months for the essay exam affords them an opportunity to elaborate and reflect,
even argue with one another.
10. Actively seek contradictions Interestingly, hands-on projects under high cognitive
diversity appear to naturally encourage the students increasingly toward initiating
dialogues that are more Socratic in nature, as they struggle to make sense of ill-
structured projects in ill-structured domains.
11. Actively seek metaphors Metaphorical reasoning is not inherent in these projects
(nor in the exam) although students have a propensity toward analogical reason-
ing, even where spurious, affording teaching moments for the instructor. Here
again, cognitive diversity becomes a true ally.
12. Take advantage of the natural learning cycle (from discovery to concept introduction
to application), balancing both challenge and safety For example, the extended
time afforded by take-home exams with deep, ‘stretch’ questions allows students
to work through this cycle. Extremely challenging team projects work best when
students realize that there is a safety net in the form of both the instructor and their
fellow students.

Impediments to constructivistic curricula
Another aspect of that is how educators’ prior expectations can cloud their perceptions
of what is happening in the classroom. A trap we are all familiar with: it is very easy in
case-study discussions to assume that the discussion will eventually end up taking the
same general directions and end up with the same general conclusions. Prawat (1992)
notes the existence of four critical cognitive impediments to implementing a more
constructivistic curriculum:

1. dichotomous view of teaching and learning;
2. student interest and involvement is necessary and sufficient for deep learning;

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3. dichotomous view of comprehension and application; and
4. the curriculum is a fixed agenda (dichotomous view of content and process).

These erroneous assumptions reflect instructors’ own role identity as a teacher. We can
test ourselves – are we guilty of these assumptions? Assumptions may be hard to change,
but we can raise our awareness of them. Prawat suggests that these assumptions reflect
dichotomous, ‘either/or’ thinking about learning, though experienced educators are fully
aware of the sizable ‘grey areas’. Let us consider this in terms of cross-campus entrepre-
neurship education.
Teaching and learning as distinct implies the folk wisdom that education is a transfer
of knowledge from teacher to student. An entrepreneurial setting often requires the
student to bring considerable information to the class and, in many cases, a distinctly dif-
ferent mental model of the problem at hand. The latter is particularly powerful in helping
students (and teachers) to construct newer, more apt mental models.
A classroom where many different majors are present (and not just different business
majors) forces these differing mental models to the surface immediately. It is this itera-
tive, reflective process of constructing and re-constructing deep knowledge structures
that makes for deep learning. All the student and teacher passion in the world will not
help if we ignore the constructivistic nature of deep human learning.
Prawat’s third impediment is that we often think of learning as a sequential process:
we learn, then we apply our learning. Action learning models (for example, Leitch and
Harrison, 1999) have long argued that deep learning is accelerated when we act, then
seek to understand. Entrepreneurs need to act and learn essentially in tandem, making it
difficult to arbitrarily separate even classroom learning from action. Our classroom exer-
cises must reflect that, rarely being mere transfers of knowledge without the context of
action. It is easier to get students to routinely ask ‘Why?’ and ‘How?’ when their mental
models differ as much as they do in a cross-disciplinary setting.
Prawat’s final impediment is really the culmination of the first three. How do we over-
come the first three impediments, while following a rigid syllabus? Even with students
with a shared mental model (for example, accountants) one never quite knows when
important teaching (and learning) moments can occur. The more cognitive diversity in
the classroom, the more likely it is that any key learning moment can occur at almost any
time and the instructor (and the students) need to be prepared. If entrepreneurs thrive on
serendipity, then so too should entrepreneurship education.
Let us look briefly at how one might grow a constructivistic learning partnership.

Exemplars of constructivistic classrooms
Providing learners with authentic questions (or helping surface them) that engage them
at a deep level and letting them take ownership of how they address those questions
(and how that changes how they think) is key. Doing so requires that the instructor truly
understand the entrepreneurial mindset, but the payoff is significant. Not only does the
engagement benefit the community, but the constructivistic process enables learners to
change how they think about entrepreneurial thinking. You simply cannot change the
entrepreneurial mindset through ‘memorize and regurgitate’ training
Appendix 4A offers two examples that the author is closely familiar with and
most readers will find them well within their comfort zones. Again, much of what

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entrepreneurship educators do routinely leans heavily toward the constructivistic; these
examples lean even further, including an intensive engagement with the community.
Both examples also lend themselves quite readily to university-wide programs.
What other kinds of exercise are congruent with the constructivistic learning
approach? Case studies seem an obvious approach. Case-study analysis compels stu-
dents to construct working models and to re-construct them as they work through the
ramifications. The iterative process is immensely valuable as it enhances students’ ability
to ‘learn how to learn’ in new directions. (When we learn to do mathematics, we engage
in the same ‘patterning’ process.) Cases can surface students’ most stubbornly held
assumptions, but only if we encourage reflective thinking and we encourage ‘out-of-the-
box’ thinking. For example, some case instructors insist that students not invoke outside
knowledge, but we are rarely dealing with legal cases where precedent is paramount. If
you are teaching case studies and students ‘go the extra mile’ to find additional data,
why punish them?
One useful approach in this domain is the semi-structured ‘living cases’ such as those
used by many schools. The reality of a living case compels action learning and a construc-
tivistic approach. The good news is that most entrepreneurship educators have embraced
the reality aspect and many focus heavily on experiential learning. However, a deeper
understanding of the key principles of constructivism and of methods that embrace them
(for example, action learning) will enhance learners’ experience even further.
Once again, a caution: experiential exercises need to be truly experiential exercises. Not
all such named exercises are really so. ‘Hands-on’ does not necessarily equal ‘experien-
tial’. Truly experiential exercises give careful consideration to process and content – and
give students room to make mistakes. An example of this would be a business simulation
game that in the long run rewards early mistakes, rather than a game that overly rewards
early success, even if it results purely from chance. In short, truly experiential exercises
change how students think – not just changing the content of knowledge but also chang-
ing deeper cognitive structures.
Consider examples from this Handbook. Entrepreneurship in the sciences requires
an entrepreneurial approach. Biologist Daniel Johnson asked his students to write a
chapter for an authentic biology text, while biophysicist Jed Macosko engaged students
in computer graphics, both with a truly entrepreneurial spin and genuine problem-based
learning (Chapter 9, this volume)
A remarkable example from this Handbook is Lynnette Claire’s entrepreneurship film
project (Chapter 12, this volume) where students with little or no exposure to entrepre-
neurship or to film-making were tasked with studying a local entrepreneur and creating
a compelling short film on their subject. This required bringing in resources from across
the University of Puget Sound (Tacoma, WA) and engaging the community at a deep
level, all the while helping students reflect on their experiences and the impact on their
own entrepreneurial self-efficacy.
Community engagement in general is a potent way to get learners to identify truly
authentic questions. We have already noted that social and sustainable entrepreneur-
ship is often at the heart of cross-campus entrepreneurship programs. What better than
projects that allow learners to learn at a very deep level and channel their passion in
ways that enhance their cognitive development toward more expert entrepreneurial
thinking?

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Getting started
Business students are often well-schooled in the traditional learning approaches. True
collaboration is likely to seem threatening to students who assume that education is
a competitive process. Perkins and others argue that we can begin the process with
deceptively simple exercises such as ‘Fermi’ problems. (A Fermi problem asks a simple
question with no simple answer, such as ‘How many pencils are there in Chicago?’.) The
pursuit of a Fermi problem forces students to be creative and to use multiple perspec-
tives and approaches. In turn, this leads them toward collaboration and toward the
realization of the world’s inherent messiness and noisiness. We observe other simple
approaches such as using metaphors (‘firm as a machine’ or ‘firm as a tree’ and so on as
suggested by Morgan, 1986) or debates or even a mock ‘town meeting’.
‘Students as true co-investigators’ is another powerful model (Yager, 1991). Consider
John Bunch at Benedictine (Atchison, KS) who lets students do ‘How-To’ papers that
show the reader how to handle some useful task such as how to arrange a letter of
credit for exporting to France. The student identifies the topic area (thus an ‘authentic’
problem), negotiates its scope with instructor as essentially co-learner, then delivers a
report that is available to classmates, present and future. We are developing a program
where students will co-write white papers with local technology clients; this may even
become a profit center to help support student activities.
Not all group projects offer such benefits; poorly structured group projects can impede
learning. True group projects involve pervasive collaboration and exhibit many char-
acteristics of cooperative learning (true interdependence in goals, in the means to those
goals, and in rewards). Some instructors have found success in journal writing and other
tangible supports to students’ ability to think reflectively on the learning process in that
class – how their thoughts have changed and how their ways of thinking have changed.
One tangible output might be writing a case study, especially now with formal case-
writing competitions that are welcoming student efforts.
Any such approach lends itself to a cooperative learning environment where stu-
dents are wholly interdependent on each other for their goals, their strategies, and their
rewards. Many business school programs use such teams exclusively with great success.
A low-risk approach is the group outside presentation where the team must present to
some real-world group on a topic of value and interest. This pushes students to select an
‘authentic’ problem and grants them the freedom to pursue it autonomously. As might
be expected, team teaching is often useful, offering multiple perspectives to the students.
A prominent example is the Experiential Classroom Program at Syracuse (NY) that
teams entrepreneurs with academics.
We need to provide a safe environment where failure is clearly and emphatically a
learning experience. Some entrepreneurship classes even insist that students must ‘push
the envelope’ until they actually fail, learning that adversity really is a learning experience.
One popular model is to assign students a project to induce some actual, visible change
in some organization that involves more than one person (who must be persuaded, not
ordered). Setbacks on an ‘impossible’ task are often much less ego-threatening.
Daryl Mitton (1994) offered a series of experiential exercises to build what he calls
entrepreneurial ‘clout’ (essentially tacit knowledge and self-efficacy). Exercises many
use include the ‘dollar’ exercise (create a profitable, legal business for $1) and the ‘five
strangers’ (go ask five strangers about your business idea). Learning experiences such as

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these are generally done outside of class at the student’s choice of time and place. The
exercises encourage breadth of thinking and, more important, increase student percep-
tions of self-efficacy at the task or skill in question. They allow students to change their
mental models with a minimum of risk to ego or self-image.

How do we evaluate progress?
One key advantage of the behaviorist, content-oriented model is that it is relatively easy
to assess whether the content knowledge has been transferred. It is considerably more
challenging to assess whether knowledge structures have changed (and in positive direc-
tions). What we can do is focus on the constructivistic process and to keep firmly in mind
that our goal is to help students move toward more expert entrepreneurial thinking.
Let us return to the issue of how learning processes can change deep mental models in
the direction of better entrepreneurial thinking, whether in terms of learning to see more/
better opportunities or to see oneself as an entrepreneur (or, as we have noted, both).
Both Baron (2006) and Gaglio (2004) demonstrate how the cognitive mechanism of
counterfactual reasoning is a potent lever for stimulating students to question their exist-
ing mental models. And, again, at the University of Victoria, Ron Mitchell, Brock Smith
and Kristie Seawright and Eric Morse have developed a pedagogy that heavily empha-
sizes helping students acquire expert scripts (2000). This clearly suggests that measures of
deep structures, whether scripts or maps or other possibilities, can be usefully deployed
to research how entrepreneurial thinking changes across a training program (Mitchell et
al., 2000; Krueger, 2001).
How do we best evaluate student performance formally? We have suggested above
that in constructivistic learning, it can be powerful indeed to engage the students in
designing assessment and evaluation metrics. An excellent starting-point is something
that students, especially non-business majors, often suggest: the ‘portfolio’ concept that
collects a wide variety of student outputs. Perkins (1994) argues for ‘process-olios’ which
also include throughputs to vividly demonstrate student progress. (That is, the process-
olio includes interim and draft reports.) Requiring multiple projects in the portfolio/
process-olio taps into more than one kind of intelligence and more than one type of skill,
showing how students take advantage of their strengths and how they remediate their
weaknesses. In short, they show how the students learn how to think more entrepreneuri-
ally. SBI reports are ideal candidates. However, we would be remiss if we neglected the
growing use of portfolios in entrepreneurship education with at least three Academy of
Management pedagogy awards going to portfolio-based programs, two of which are
explicitly script focused (San Francisco State and Victoria.) Never lose sight that the
metrics and the evaluation process itself should have visible connection to the change in
deep beliefs and knowledge structures that we are seeking.

Where next?
More important questions remain. As models and methods continue to evolve, espe-
cially those suggested by recent breakthroughs in neuroscience, we will be able to take
closer and closer looks at how specific educational experiences affect specific changes
in how we structure knowledge. However, we still have relatively limited evidence even
at the surface level. Unlike the education field (for example, Hamilton and Hitz, 1994)
we have not studied how students’ reflections change over time (for example, through

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even simple mechanisms such as reflective journals). Would it not be amazing to track
the changes of business majors versus non-business majors? Even if they converge at
the same points, the paths will likely differ. (Even if they start at similar spots, the
paths may differ!) We already know in social entrepreneurship (a frequent theme in
cross-campus programs) that someone with the role identity of an ‘entrepreneur’ starts
with very different knowledge structures from someone with the role identity of ‘social
activist’, even if they too end at the same point (Simms and Robinson, 2006). Cross-
campus courses represent a powerful venue for cutting-edge research in entrepreneurial
cognition.
It is also imperative that entrepreneurship educators do more assessment of the
impact of their teaching. As noted, we consistently see that our classrooms do change
students’ thinking. From the constructivistic perspective, it is almost unthinkable that we
would not. However, that begs two questions. First, why are we not doing more of this
research? Why are we not doing research that addresses directly the legitimacy of what
we do? With accrediting bodies nudging schools to use practitioners less in the classroom
and administrators trying to shoehorn entrepreneurship into the mainstream, why then
are we not providing the very evidence that demonstrates that what we do matters? That
how we do it matters?
Second is a more troubling question: are we always changing minds in the right direc-
tions? Are we actually moving them in the general direction of expert thinking? If the
constructivist model has a large drawback, it is that the instructor needs to fully under-
stand (and likely share) the expert entrepreneurial mindset. What if the people teaching
entrepreneurship have serious misconceptions about the entrepreneurial mindset? Even
a talented, passionate amateur may be painfully hostage to the novice mindset to the
detriment of students.

Entrepreneurship is not linear; entrepreneurial thinking must not be linear
Considering that entrepreneurial processes are rarely linear, becoming an entrepreneur
comprises a set of ill-structured, even wicked tasks. We know that planning a venture
requires effectual, not causal logic (Sarasvathy, 2004). However, what about instructors
who teach entrepreneurship as essentially a linear process? There is growing evidence that
simply teaching someone to write a business plan is dysfunctional at best, educational
malpractice at worst. Meanwhile, leading educators have grown increasingly contemptu-
ous of ‘cookbook’ business plan classes – and contests (for example, Meyer, 2001).
On the other hand, we are seeing the rise of cross-campus competitions such as the
University of Texas’s ‘Idea To Product’ (www.ideatoproduct.org) global contest where
multidisciplinary student teams turn raw intellectual property into plausible products.
Helping students learn to turn ideas into reality is powerfully constructivistic in itself;
adding the cognitive diversity of multiple disciplines makes it work.

The political context? (‘Anyone can teach entrepreneurship!’)
Yet, little of this has seen print. Why? Business plans are essentially the ‘killer app’
that brought entrepreneurship into wider acceptance in business schools. Business
plan contests are great theater and potentially great fund-raisers for schools, even if we
cannot identify measurable impacts on entrepreneurial thinking. What administrator
wants to hear that business plans are too often mediocre pedagogy? We have seen how

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problem-based learning is far more powerful and more productive, yet if it requires an
expert thinker to do it properly, then that constrains administrators who would prefer
to believe that ‘anyone can teach entrepreneurship’ (Fernandes, 2006). However, do we
really know what the impacts are, positives as well as negatives, of using the business
plan ‘cookbook’ as the centerpiece of entrepreneurship education? Would we not be
better off if we took a constructivist approach to teaching business plans (Honig, 2004)?
That is one nettle we need to grasp; we now have the tools to do so. How does this linear
approach actually change deep knowledge structures?

Instructor effects?
Case studies are a middle ground that can also be fruitfully explored. An inexperienced
case teacher may be too prone to follow the ‘recipe’ suggested by the teaching notes, both
the intended conclusions and the paths to get there. Meanwhile, an experienced (expert?)
case teacher can operate in a much more nonlinear fashion, yet providing linearity where
needed. As such, we could hypothesize that instructor differences might play a significant
role. In much of the foregoing, we have argued that the key instructor difference lies in
him/her having or knowing the expert entrepreneurial mindset. Here we may find that
the key difference is being an expert in case teaching. Hanke et al. (2005) seem to argue
that having expertise in true problem-based learning is the critical leverage point, not
necessarily having the expert entrepreneurial mindset. Finally, we would also be remiss
in not arguing that we need to study student effects. (Might not cross-campus courses
provide fertile ground for studying that?) Our research needs to tease out the differential
impacts of instruction, instructor and student.
In sum, it should be obvious that not only does the constructivist model offer us a
powerful, productive way to understand and improve entrepreneurship education, but
there is also a rich, deep array of theoretically interesting – and practically useful – topics
for future research.

Constructivism: major conclusions

1. The number one objective of constructivistic education is: deep understanding, not just
superficial skills. Even complex skills necessary for success are acquired more quickly
and thoroughly through this kind of approach. Being a successful entrepreneur
requires this. And, as we have seen, the cognitive diversity offered by a cross-campus
program can accelerate this process measurably.
2. Gaining a deep understanding requires ‘learning how to learn’ from multiple
perspectives. How better to do this than in settings where the multiple perspectives
define the setting (as in cross-campus classes)?
3. The constructivistic model of education confirms conceptually much of what we
already know to be efficacious educational practice.
4. The constructivistic model affirms the criticality of context: the situation and co-
learners are vital to students gaining a deep understanding of the subject area.
5. Constructivistic teaching works (but it is not easy!).

‘Education is not the filling of a vessel but the lighting of a fire’ (William Butler Yeats).
To borrow an old adage, our goal as entrepreneurship educators is not human resource

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development, rather the goal is developing resourceful humans. Where better than in
entrepreneurship to light – and fan – the fire?

Appendix 4A Two examples of constructivistic classrooms

Example 1 The virtual accelerator course for nascent gazelles
The University of California at Los Angeles (UCLA) pioneered a model program (GAP)
where MBA capstone (all majors) students were matched as teams with nascent gazelle
entrepreneurs with high potential for explosive growth and figured out ways to help them
toward meeting their promise. (UCLA was not the only pioneer, in fact, many schools
now follow this general model such as Georgia Tech’s TiGER program, the multi-school
program developed by N2TEC (www.n2tec.org, led by USC and Fresno State, CA).
However, UCLA’s Alan Carsrud was first to market with this model.)

Basic GAP model Student teams are matched with nascent tech entrepreneurs (firm
already started but not yet launched). Team goal is to help accelerate the business’s
development, ideally resulting in major external funding, acquisition and/or major
customer acquired.

● Step 1: Recruitment Obviously, the client businesses are carefully vetted, but so
too are the instructors required to support this process (comfort with and skills
with regard to problem-based learning is imperative).
● Step 2: Launching Students (and faculty) and entrepreneurs come together for a
‘kickoff’ weekend where the teams and their entrepreneurs can bond and develop
the initial action plan for the semester. This includes a 21 day entrepreneurship
boot camp that gets students and others up to speed on the task ahead. This crash
course can also be shared with a broader audience. The event closes with brief
student presentations on their proposed ‘battle plan’ (including benchmarks and
milestones), pitched to a ‘murder board’ of experts in new ventures and the firm’s
industry.
● Step 3: The work Student teams go home to begin work on their plan, revising as
need be. They identify an advisory board for their project using members of their
community (wherever possible), even national experts. It really is up to the team;
however, at regular intervals, additional course material is presented to students
and other material is provided to faculty and team advisors to use.
● Step 4: The celebration/competition Student teams return at the term’s end
for a celebration of what all the teams have been able to do and a final formal
presentation to an extremely high-powered, experienced ‘murder board’ selected
specifically for each team. (This can obviously be structured as a competition,
of course.) The celebration combines this with a second boot camp that can be
shared with the public, this time focusing on later-stage issues such as presenta-
tion skills.

From a constructivist perspective, note how the GAP program lives up to the key
criteria for constructivistic learning, using the criteria provided by Brooks and Brooks
(1993).

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1. ‘Authentic’ (and ‘important’) questions
2. ‘Big ideas’
3. Constructing meaning requires triangulation
4. Coaching, not lecturing
5. Assessment and evaluation techniques should reflect these processes

● Authentic questions and big ideas: GAP offers projects with genuine, significant real-
world consequences, where both success and failure will be highly visible. Students
realize immediately that they will play a significant role in what happens.
● Triangulation: Nascent entrepreneurs operate in an environment where informa-
tion is problematic, requiring students to work with all manner of information
sources, including human sources whose intel requires triangulation, but also teach
them about the mental models of industry insiders and outside experts.
● Coaching: The instructors provide key information in the initial boot camp and
are available for consultation (and intervention, if need be) throughout the term.
However, it is common that student teams must teach themselves key skills.
● Evaluation: Students are evaluated by the ‘murder board’ expert panels and by
their peers.

Example 2: Technology commercialization and economic development

A ‘TEAMS’ approach? TEAMS was at the heart of a complex partnership between
Boise State University (Boise, ID) (later other schools), the Idaho National Lab (www.
inl.gov) and the Inland Northwest Research Alliance (Idaho Falls, ID) (www.inra.org)
and the universities in the INRA region, supported by these partners and the Ewing
Marion Kauffman Foundation (Kansas, City, MO). Student project teams work on a
diverse set of entrepreneurial projects that provide a rich, ill-structured learning environ-
ment while helping their communities via commercializing novel cutting-edge technolo-
gies and economic development (including social ventures).

The TEAMS process Each team works with external clients to negotiate project scope.
Teams working with a community negotiate their project with local contacts and the
instructor. During the semester teams share their progress (and their hurdles) with other
teams, including a midterm formal progress report and presentation. At the end of the
semester the team presents formally to their clients, usually on-site, with a final formal
presentation with guests from the local business and technology communities.

Technology commercialization projects Most of a wide range of technology projects
were recruited from the large federal research lab here in Idaho, the Idaho National Lab
(INL). Commercialization assessments begin with a thorough industry analysis followed
by a market analysis (à la QuickLook). Student teams develop a strategic plan for imple-
menting commercialization, presented to the inventors and tech transfer professionals.
Students primarily worked with new technologies developed that INL wants to
license, such as software (data warehousing, computer security monitoring), biotech,
and environmental remediation, plus the local high-tech community (for example, www.
kickstand.org).

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Economic development Similarly, INL’s economic development group and others
offered projects where student teams can help local communities. With the technology
projects the successful student work attracted interest from other development entities
in the region.

● Community assessments, such as developing opportunity-capacity matrices to
guide future projects. (For these, students present to development professionals
and local leaders.)
● Feasibility studies for new industries One project proved the high potential for a
new industry cluster based on hydroponics, while another team prepared a feasibil-
ity study for the Sacajawea Interpretive Center in Salmon, Idaho.
● Designing new development efforts Past projects include designing a next-
generation producers’ co-op for rural Idaho and designing a distance learning
center in northeast Idaho.
● Specialized projects Teams from three different Idaho universities inventoried
telecommunications resources in several Idaho cities, presenting their findings to
the Governor and other top officials from government and industry at a major
conference to ramp up rural connectivity.

Key student lessons learned TEAMS projects gave an opportunity for hands-on experi-
ence at creating true entrepreneurial value in constructivistic problem-based learning
where they applied process skills such as:

● ill-structured problem solving (and project management under such
conditions);
● building and maintaining a self-managed high-performance cross-functional work
team;
● integrating and applying a wide range of business skills in an entrepreneurial
setting; and
● an inside look at how large real-world projects get designed and implemented.

Tangible outcomes

1. Student excitement: Students now maneuver to be in these capstone sections.
2. Tangible impact on high-stakes technology commercialization decisions.
3. Tangible impact on local communities, often rural (but could easily be urban).
4. Improved student skills at team building, problem-solving and written/oral
presentation skills.
5. Projects provide real-world context to illustrate key concepts such as business
models, competitive intelligence, industry analysis, benchmarking and, of course,
business plans.

TEAMS as constructivistic learning How does the TEAMS program live up to the
key criteria for constructivistic learning? Let us return to the useful criteria provided by
Brooks and Brooks (1993):

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● Authentic questions & big ideas: Projects have genuine, significant real-world con-
sequences, something that catches the students’ attention – and keeps it. Student
projects have provided INL with information used directly in patenting and licens-
ing decisions. Economic developers have used student projects to advance their
communities (for example, the producers co-op for eastern Idaho relies heavily on
the students’ research and analysis).
● Triangulation: Projects also require using multiple sources of information, often
conflicting, and sometimes working with key contacts who themselves have very
different agendas. Students get multiple perspectives on their projects directly and
en route gain multiple perspectives on critical course concepts. Working in a true
self-managed work team adds additional triangulation (for example, Senge 1990).
With the addition of other universities to the TEAMS effort, students also triangu-
late with the experiences of others.
● Coaching: The bulk of the instructor’s time is spent working with the teams and
clients. To further move away from lecturing, each student team is charged with
teaching a text chapter, explicitly linking that chapter’s key concepts to their own
project. Students also coach each other on peer teaching presentations.
● Evaluation: Students are evaluated on their projects by their peers, clients and
outside experts.

Note
1. See www.pioneerentrepreneurs.net/bigidea_gendron.php.

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