Post on 21-Apr-2023
Jonathan D. Moizer
Jonathan Lean
Gordon Smith
Mike Towler
Plymouth Business School
University of Plymouth
Plymouth
PL4 8AA
Tel: 01752 232824
Email: j.moizer@plymouth.ac.uk
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Experiences of Using a Business Strategy Simulation: Lessons For Promoting Effective
Learning
Abstract
This paper presents the findings of a study in to the use of a
computer-based business strategy simulation game as an instructional
tool for undergraduate students. The factors driving the dynamics
of learning are identified, and their interactions explored. Kolb’s
model of experiential learning is used to describe and analyse the
learning that takes place in the gaming environment. The results
indicate that whilst business simulations provide a useful vehicle
for experiential learning they do not automatically facilitate a
high level of reflective observation. Therefore, appropriate
interventions are required on the part of the educator.
Implications relating to module design are outlined, relating to the
choice of game, the role of briefing and debriefing, the importance
of effective integration of games with other aspects of teaching,
the role of assessment and appropriate instruction in the effective
use of business analysis methods.
Keywords: business simulation game; experiential learning; Kolb, business strategy
Introduction
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A common approach in higher education to the delivery of business
strategy courses has involved the use of case studies. Such a
method can aid the development of both analytical rigor and the
ability to synthesise disparate information. However, static case
studies have a limited capacity to demonstrate time evolutionary
behaviour. Perhaps more importantly, many academics have witnessed
how students can become partially disengaged from the learning
process when using case studies, as it is not possible to observe
the outcomes of ones recommendations or decisions. In recognition
of this, many Business Schools have sought alternative modes of
teaching delivery.
This article evaluates the use of a business strategy simulation as
a platform for learning. The paper is divided in to six sections.
The first section of the paper considers the justification for using
simulations to encourage learning. Following this, the choice of
business simulation used within this study is outlined with respect
to the broad learning objectives. Thirdly, integration of the
simulation in to the curricula design is discussed. Next, the
methodology for the evaluation is described, followed by an
exposition of the study results. The results are discussed with
reference to Kolb’s experiential learning cycle (Kolb and Fry,
1975). The article finishes with a summary of pedagogic lessons
that emerge from the study.
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Why use strategy simulation games?
A computer-based business strategy simulation game is a laboratory
where experimentation with, and exploration of strategic decisions
can be achieved. This is facilitated through examination of the
simulation game’s time based behaviour. Such dynamics are driven by
both the underlying structural design of the simulation, and any
subsequent numerical modifications of its parameters. For a
sufficiently complex simulation a high level of verisimilitude can
be achieved.
Lane (1995) describes simulation games as a ‘learning from
experience’ approach to managerial education. The high level of
realism enables this type of learning to be achieved. The
participants see the effects of their decisions traced out by the
simulation. They can then reflect on their gaming experiences, re-
conceptualise and make fresh decisions. Thus, learning is achieved
through numerous iterations of decisions being played out, the
consequences providing feedback. Analysis and discussion of case
studies often fails to capture these dynamic aspects of strategic
decision making. In effect, participants engaged in case study
learning are less likely to pass through all four phases of Kolb’s
(Kolb and Fry, 1975) experiential learning cycle. Therefore, a
number of authors (Raia, 1966; Wolfe and Guth, 1975; Keys and Wolfe,
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1990; Knotts and Keys, 1997; Tompson and Dass, 2000) conclude that
simulations result in significantly higher efficacy on the part of
students than do case studies. Parks and Lindstrom (1995) agree
with the proposition that business strategy simulations can enable
students to achieve higher levels of learning than case led teaching
but warn that with little emphasis on strategic planning and
implementation, the learning value of the simulation is probably no
better than using cases.
Learning objectives and choice of simulation
Final year undergraduate students at Plymouth Business School are
taught business strategy as a capstone subject. The mode of
teaching delivery had previously followed the traditional model of
formal lectures with accompanying student-led case study orientated
seminars. The authors were of the opinion that case studies might
have been leading students towards a view that the practice of
strategy was simply mechanistic and that it could be successfully
delivered through the application of a range of two-dimensional
frameworks. Instead, the objective was to emphasise in the teaching
the possible outcomes arising from alternative streams of strategic
decisions. Simulation was proposed as an option to be considered
for supporting the teaching of strategy.
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After a review of various commercially available games, the
simulation chosen was the BUSINESS STRATEGY GAME (BSG). This
appeared to meet most requirements; it is PC based, textbook
integrated, contains verisimilitude and complexity, is group based
and should therefore stimulate ‘experiential learning’.
Simulation adoption and integration
The BSG is based upon a global business engaged in the manufacture
and sale of athletic footwear. Student teams (or companies) compete
against each other for a predetermined pattern of market demand. An
administrator is responsible for overseeing the running of the game
and sets up the externalities which will shape the decision making
at the company level (e.g. currency exchange rates, material prices
and shipping costs). The simulation requires the input of yearly
business decisions, these decisions are collectively processed on an
administrator’s spreadsheet, and the game then rolls on to another
year’s play. A score based on a number of performance metrics
(profit, market share, capitalisation, sales volume, etc.) is
determined, resulting in the teams moving up or down a league table.
The BSG was run over eight weekly decision periods (simulated
years).
The BSG is accompanied by fairly comprehensive playing guidelines
but also has scope for a high degree of flexibility with regard to
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the pedagogic approach. Table 1 illustrates the approach adopted by
the authors.
TABLE 1: Pedagogic approach adopted
The Stage One student briefing is a critical aspect of running such
a simulation game. Low (1980) argues that an explanation of the
detailed mechanics enables students to concentrate on learning how
to develop strategies and to make decisions. Knotts and Keys (1997)
note that until students understand the game background, its rules,
and the meaning of data outputs, no significant conceptual or
strategic management learning can occur. The briefing took place
some weeks in to the lecture series in order for the students to
assimilate some basic knowledge of strategy prior to playing the
game.
The first task for each group was to name their company. This was a
useful exercise in encouraging participants to take ownership of
their companies from the outset. Next, students familiarised
themselves with the game’s parameters and rules through reading the
accompanying literature. Ramnarayan and Strohschneider (1997)
suggest that teams are often inclined to start making decisions
immediately with insufficient analysis of their business’s
situation. The researchers therefore emphasised to students the
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importance of early orientation. Participants were then free to
input their decisions using a PC. This consisted of the numerical
parameterisation of finance and investment, human resources,
production and operations, logistics and distribution, and sales and
promotion attributes of the game. Knotts and Keys (1997) argue that
most frequently, learning occurs when participants are forced to
reflect on their experiences. Therefore, the debriefing Stage was
regarded as a critical final aspect of the learning experience.
Debriefing and data collection
At module commencement, students were briefed on the nature and
application of the BSG, and were informed that there would be post-
simulation debriefing sessions. The debriefing sessions took the
form of group discussions with each of twelve playing teams. These
meetings served as the source of primary data for this research
study. Each consisted of the four team players and two academics.
The aim of the meetings was to stimulate a student lead discussion
focusing on the learning achieved as a result of the simulation
experience. Specifically, the objectives were to:
1. identify if and how the use of the BSG facilitated
student learning;
2. identify those factors governing the effectiveness of
the simulation as a learning tool;
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3. inform the development of recommendations for enhancing
the efficacy of simulations in the context of teaching
business strategy.
The data collection framework used drew upon interview approaches
recommended by Thorpe et al. (2002) and Saunders et al. (2000). The
format was of the semi-structured type. This permitted the general
direction of the interview to be guided whilst allowing a rich
picture about the use of the simulation game to emerge. All
participating students agreed to have the interviews recorded for
later full verbatim transcription. Wolfe (1997) identifies the
possible limitations of student opinions or attitudes about a game,
in that they cannot always be relied upon as indicators of the
game’s success or failure. Other authors (Gunz, 1995: Wellington
and Faria, 1996; Ramnarayan and Strohschneider, 1997) found that the
attitudes of poorly performing students towards aspects of the
design and administration of games tended to be unfavourable with
such teams frequently displaying a propensity to blame exogenous
factors for their problems. In designing the debriefing
discussions, the researchers sought to avoid these problems by
encouraging a relaxed, open exchange of views. Furthermore, it was
felt that the lack of summative assessment attached to playing the
BSG would reduce any student anxieties about being forthright in
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describing their expectations and experiences of the game. Each
discussion lasted for approximately thirty minutes.
The approach adopted for data analysis broadly followed the
guidelines of Marshall and Rossman (1989). To reduce and summarise
the collected data, a number of ‘partially ordered meta-matrices’
(Miles and Huberman, 1994) of differing levels of complexity were
developed. These enabled summary descriptions from each group
meeting to be presented in a tabular form (a substantially reduced
and simplified table representing the outputs from the meta-matrix
analysis is presented later in Table 2). The meta-matrix
facilitated the identification of common themes and patterns within
the collected data. Patterns and contradictions within and between
the interview groups could be elicited through comparing and
contrasting the different group summaries contained within the meta-
matrix tables. Having reduced the transcript data and identified
significant themes and issues, supporting evidence from student
statements was extracted from the original transcripts to form part
of the discussion of results.
Key findings of the inquiry
The process of learning experienced by students is described with
reference to the work of Kolb (Kolb and Fry, 1975) as shown in
Figure 1.
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FIGURE 1: Kolb’s experiential learning model
Table 2 presents a reduced summary of the results emerging from the
study. Although much of the rich insight contained within the
original data is lost through this process (Marshall and Rossman,
1989) and the data presented is far from complete, it captures some
of the important patterns evident within the original transcripts.
The table is structured to show the experiences and perceptions of
each of the 12 groups as they relate to the different aspects Kolb’s
learning cycle. Coded responses represent: High (H), Moderate (M)
and Low (L) or Yes (Y) and No (N).
TABLE 2: Summary of debriefing interviews
The primary question to consider from the results is ‘did students
learn as a result of playing the BSG simulation’? Evidence from the
student discussions is mixed with regard to the extent to which
students passed through the different phases of the Kolb learning
cycle.
Concrete Experience
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In gaming terms ‘concrete experience’ this might be represented by the
experiential aspects of taking part in the simulation and the
feelings associated with it. Relevant data collected through the
interviews concerned the level of engagement in the gaming
experience reported by players (e.g. excitement about the competitive
element, motivation to play), their level of enjoyment, evidence of
conflict within the team and perceptions of the game’s realism and
its level of integration with other module inputs. As indicated in
Table 2, the concrete experiences of different teams varied
considerably. Some felt a high level of engagement and enjoyment,
typically alongside a degree of conflict within their group and
positive perceptions of the game’s realism. Others appear to have
been somewhat disengaged from the experience, deriving little
enjoyment from the simulation and seeking a path of least resistance
when interacting with other team members. These groups also tended
to have less positive views of the game’s realism. For instance, a
member of Team 11 commented “I didn’t feel involved…I didn’t think it was something
where I was doing anything really” indicating a high level of detachment from
the game. A team mate added “..if we didn’t come to an agreement…we just tried to
compromise.” This comment reflects the tendency amongst some teams to
follow the least confrontational route to decision making. The
following student comment, from Team 7, perhaps best captures the
reasoning behind this common tactic: “…to do the game in a group of friends
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that you all know…it means that you very much don’t want to…upset but…you want to go
along with each other.” Team 7 was also rather dismissive of the game’s
level of realism stating “If you are in the real world you have much better access
to information and you can see what other people [competitors] are doing.” Whilst
somewhat misinformed, this view does reveal a perception that the
gaming environment did not wholly reflect the real business
environment. This indicates that some students did not involve
themselves “fully, openly and without bias in new experiences” (Kolb and Fry,
1975, p.36). Indeed Gunz (1995) suggests that students using more
complex management simulation games often find it easier to
criticise the simulation itself or the people controlling it than
address the groups own inability to perform. Some students were
finding it difficult to accept that the game was a simplification of
reality and it was this reduced complexity that enabled learning.
Their criticisms suggest that they did not possess the type of
‘concrete experience abilities’ that Kolb and Fry argue are
important for learning.
The experiences of the less engaged teams are significant in that,
as Walters et. al. (1997) report, dissatisfaction with a business game
can greatly diminish its potential as a learning tool. It can also
lead to satisficing behaviour. For instance Team 5 stated “…none of
us came up with a brilliant business idea…we just stuck with like an average price and an
average spec[ification].” A major reason why some teams did not fully
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engage in it appeared to be the lack of summative assessment linked
to the exercise. A typical comment came from a Team 9 member, “I
thought it [the BSG] could have been more worthwhile…if we were given some sort of mark
for it.” There has indeed been a debate in the literature about the
value of summative assessment of gaming participation. Some authors
argue that a summative assessment is an important aspect of module
design (Base et. al., 1986; Herz and Merz, 1998). Others suggest that
there is little or no value in using graded assessment as a
motivating device (Wolfe and Roberts, 1986; Faria, 1986). Most
research studies concerning the delivery of simulation games
incorporate grading systems. This indicates that implementers of
business simulation games are either led by the expectations of
their students or have designed their games’ delivery such that
summative assessment plays a significant motivating role. What is
clear from this study is that decisions relating to assessment can
have a significant impact upon the concrete experience of game
participants and so this aspect of module design must be a key
consideration for academic staff.
The results relating to team conflict in part reflect Hunger and
Wheelen’s (1975) work, concluding that socially orientated teams
perform less well than teams with a high task orientation. Walters
et. al. (1997) intimate that structured cognitive conflict can produce
superior decisions, although they argue that it can also reduce
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satisfaction with decisions and willingness to contribute to the
work of the group. Further, in student teams it is difficult to
ensure that cognitive conflict remains structured, and therefore
conflict tends to become personalised causing polarisation and
dysfunction. Interestingly, in the present study such negative team
behaviours were not very evident. This might be attributed to the
fact that there was no summative assessment attached to the playing
of the game. It appears that anxiety about grade performance was
removed, lessening the likelihood of personal animosity between
participants. This outcome provides an additional perspective to
consider in the debate concerning assessment and module design.
Perceptions of the level of integration between the game and other
module elements were favourable for most groups, even for some
expressing negative views on other aspects of the game. For example
a member of Team 12 commented “It [the BSG] did give us an idea of the things we’ve
been taught in the lectures, seeing what effect they had in a kind of real world situation, just
being able to apply it.” This suggests that students recognised the
efforts made by staff to highlight the broader strategic lessons
emerging from the game and the relevance of strategic analysis
tools. However, as the next section shows a failing was that some
students did not appear to be motivated towards using the
information they had gleaned from lectures and other module inputs
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to enable them to conduct a full strategic analysis of their
position before developing strategic responses.
Reflective Observation
Activities associated with ‘reflective observation’ might include strategic
analysis using a range of formal frameworks and the identification
of ‘decision-outcome’ links. Parks and Lindstrom (1995) identify
that integrating theories and concepts into the simulation and
developing students’ ability to link decisions and outcomes are key
to learning. Where groups were clearly able to identify links
between decisions that they made and outcomes (data outputs), this
was taken as evidence that reflective observation had taken place.
Results suggest that the level of reflective observation was not
high for most groups. For example, one team seemed to indicate that
they had no time to reflect on available information stating that
“We couldn’t analyse how that [the BSG] was going because we were still in the process of
doing it.” The observed tendency towards limited analysis has also
been recognised by Ramnarayan and Strohschneider (1997). These
authors found that the students they studied were more inclined to
make decisions than seek information to inform decisions. They also
noted a tendency to rely on performance figures, distracting many
students from undertaking broader forms of contextual analysis.
This behaviour was apparent in this study and suggests that
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simulation games do not automatically encourage a high level of
reflective observation.
Abstract Conceptualisation and Active Experimentation
It appears that many teams were able to articulate a clear vision
and strategy for their company, thereby demonstrating their
abilities of ‘abstract conceptualisation’. In most cases, the
strategies conceived were not developed as a formal plan. They did
nevertheless represent a shared conceptualisation or ‘theory’ of how
the team concerned should compete within the game’s business
environment. Most conceptualisations were based around well
established frameworks such as Porter’s (1980) Generic Strategies. For
example, Team 12 stated “We went for really high quality trainers and we kept it at a
slightly higher price than everybody else.” Whereas, a member of Team 3
revealed “We tried to have good quality shoes and we tried to have a low price.” These
examples describe how the companies sought to set themselves apart
from their competitors through their ‘business model’.
The role of conceptualisation as a learning aid within business
simulations can be considered in the context of the construction of
mental models. Schaub and Strohschneider (1992) contend that
complex simulations require careful knowledge acquisition and the
construction of a coherent and sufficiently correct mental model as
a prerequisite for action. What is apparent from this study is that
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where a clear vision and strategy had been developed by a team, most
subsequently went on to base their gaming decisions upon this
conceptualisation. This is shown by the data relating to Kolb’s
fourth phase of ‘active experimentation’. Perhaps due to the
prevalence of a theoretically based approach to undergraduate
business teaching, most students appeared able to build abstract
conceptualisations with relative ease and act upon them. However,
what formed the basis of the teams’ conceptualisations or mental
models is less clear because, as already discussed, limited evidence
exists of reflective observation amongst the playing groups. It
could be the case that the analysis undertaken by students was very
informal in nature and that the student interviews did not capture
accurately the extent of this activity. Alternatively, the activity
based nature of the simulation may have led students to focus more
upon their concrete experiences in developing and implementing their
strategies, leading to an emphasis upon experience-based
experimentation above detailed analysis. This type of behaviour
would mirror to some extent that noted by Wellington and Faria
(1996) who highlight the important interactions between strategic
planning and implementation in a gaming context. They find that
plans or conceptualisations often emerge from actions already
occurring i.e. the experience of running a simulated company often
appears to provide the basis for the development and subsequent
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change in ‘mental models’ of that company. The findings from this
study support the view that without intervention, there appears to
be a tendency amongst students to by-pass the phase of ‘reflective
observation’ within Kolb’s learning cycle, thereby limiting the
effectiveness of the simulation approach.
Implications and lessons for gaming pedagogy
In a business simulation game, a range of processes are at work
which influence the extent of learning over a prolonged period of
playing time.
Overall, the evidence from this study presents a picture showing
that most teams were able to develop abstract conceptualisations
describing their company’s strategy and that many subsequently based
their decisions upon these conceptualisations. However, even where
decisions were based upon abstract conceptualisation, it appears
that in a number of cases, the basis for this conceptualisation was
not reflective observation. Thus it is possible that neither the
students’ conceptualisations nor their decisions were particularly
sound. The fact that those groups where abstract conceptualisation
was evident also showed positive results for measures of concrete
experience (e.g. Moderate to High engagement and enjoyment) indicates
that the simulation experience was, in the case of these teams,
successful in engaging and motivating students towards developing
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conceptual models of their companies strategic direction. However,
a significant failing appears to be that the simulation game, as
presented to students in this study, did not facilitate the amount
of reflective observation that might be required to develop sound
conceptualisations and hence make appropriate strategic decisions.
Ultimately therefore, the ability of students to learn from the
experience of playing the BSG simulation was constrained.
How then can educators ensure that the maximum learning benefit is
derived from the playing of business simulation games? First, the
choice of game is critical. Will it stimulate the interest of your
particular student cohort? Will it help to achieve the desired
learning outcomes? Does it lend itself to successful integration
with the other taught elements of your module?
Secondly, briefing can be used to both motivate your students, and
supply technical and cognitive guidance to provide a foundation for
students’ understanding of how to operate their simulated company.
The majority of ready-to-use business simulation games do not reveal
a great deal of information about their structure to the user, i.e.
the models are opaque (see Langley and Larsen, 1995). It is the
structure of the game, i.e. its parameters and variables that is
driving the simulation’s dynamics. In briefing the students,
educators have the choice to reveal, or not to reveal any of the
underlying structure of the simulation. In other words whether to
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make the models more transparent. One of the findings of the study
was that students often failed to recognise the links between
decision making and the emergent outcomes. This supports the case
for introducing some of the underlying structure of the simulated
business to the students in order to aid reflective observation. It
is likely that this would increase both the rate and overall extent
of learning, not least because if students could more readily
understand game outcomes, this would boost confidence and lead to
sustained team engagement in the game.
Beyond the use of briefing, consideration must also be given to how
lectures, tutorials, surgery sessions and guided readings might be
used to highlight pertinent strategy lessons emerging from the use
of a business simulation game. Clearly it is not possible to
achieve total concurrency in the linkages between these taught
inputs and the experiential learning through the gaming. Therefore,
there is an important role for some form of debriefing exercise in
order to draw together and reinforce the learning points emerging
from the whole of the taught module. It has been noted that a lack
of reflective observation by students playing the BSG constrained
learning and the ability to improve strategic decision making during
the playing phases of a simulation. However, reflective learning
that takes place after the game has been completed can help to
remedy this problem. Indeed, research indicates that it is often
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those firms that fail to improve and learn during a game and
consequently perform badly that ultimately learn the most from
reflecting upon their experience. For example, Teach (1990)
contends that business simulation participants who perform poorly in
terms of overall profit performance may well learn more from the
experience than those who win a simulation competition. Similarly,
Wolfe (1990) asserts that it is quite possible that the greatest
learning takes place when a team makes mistakes, and learns from
them. Thus the role of debriefing is critical in that it affords
the opportunity for all teams, whether they have performed well or
poorly, to reflect upon their experience. In a sense, a team’s lack
of reflective observation during the playing period can be
compensated for through well considered debriefing interventions.
A third issue relates to assessment. In this study there was no
summative assessment attached to participation in the simulation
game. Evidence from student interviews suggested that participants
might have been more highly motivated to learn had there been some
form of summative assessment. However, one advantage of not
assessing the students was that this allowed them to fully engage in
useful, sometimes critical team debate in a constructive, rather
than destructive manner. The lack of assessment diffused any
anxieties about the implications of decisions made, enabling the
students to fully explore possibilities in a ‘risk free’ situation.
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Overall however the formative nature of the exercise appeared to be
a strong negative influence over team engagement. Given that
reflective observation was limited, perhaps this should form the
focus of any assessment used.
Achieving higher levels of reflective observation is perhaps the
most important challenge for educators. How might the analytical
methods used by business strategists be more effectively introduced
to students? The findings from the study clearly show that the
range of analytical tools employed by students and the depth of
analysis undertaken were both limited. This contrasts with what
typically occurs when using case studies which appear more conducive
to the application of analytical tools. It appears evident that
analysis, if conducted in an appropriate way, is likely to increase
the extent of learning within a gaming context as Kolb’s model
identifies reflective observation as an integral part of the
learning cycle. In integrating the game with other taught elements
it is therefore important to consider how students are instructed in
the appropriate use of such methods. In particular, the teaching
approach must demonstrate how analytical tools might be applied
suitably in a dynamic business environment. This is critical
because when considering the three remaining phases of Kolb’s cycle,
the results of this study suggest that simulation games provide a
sound mechanism for learning. The technique allows students to
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build upon their concrete experiences to develop theoretical
conceptualisations and apply them in practice, thereby facilitating
active experimentation. Such learning is far more challenging to
achieve through using a static case study approach. These benefits
are however, not automatic and a number of factors have the
potential to block students passage through Kolb’s cycle.
Considerations of the findings of this study may help educators to
overcome such obstacles.
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Figure 1
25
Concreteexperience
Reflectiveobservation
Abstractconceptualization
Activeexperim entation
Table 1
Key Stages in Using the Simulation Game
Outline of Activities
Stage One: Briefing Initial lecture introducing the BSG and its links to the strategy module
Stage Two: Company formation Groups of four students selected per company
Stage Three: Familiarisation Reading of the supplementary BSG literature
Stage Four: Gaming Playing out company decisionsover the gaming period
Stage Five: Debriefing Reflective meetings between the individual companies and the administrator
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Table 2Kolb Phases & Associated Factors
Teams Concrete Experience Reflective Observation
Abstract Conceptualisation
Active experimentation
1 Level of engagement: LLevel of enjoyment: LConflict: NPerceived:-Game realism: LIntegration: L
Extent of:-analysis: MID of decision-outcomes: M
Understanding of Vision & Strategy: L
Decisions implemented: YDecisions based on AC: N
2 Level of engagement: HLevel of enjoyment: MConflict: NPerceived:-Game realism: MIntegration: M
Extent of:-analysis: MID of decision-outcomes: H
Understanding of Vision & Strategy: H
Decisions implemented: YDecisions based on AC: Y
3 Level of engagement: MLevel of enjoyment: HConflict: NPerceived:-Game realism: MIntegration: M
Extent of:-analysis: LID of decision-outcomes: L
Understanding of Vision & Strategy: M
Decisions implemented: YDecisions based on AC: N
4 Level of engagement: HLevel of enjoyment: MConflict: N/APerceived:-Game realism: HIntegration: M
Extent of:-analysis: HID of decision-outcomes: N/A
Understanding of Vision & Strategy: M
Decisions implemented: YDecisions based on AC: Y
5 Level of engagement: LLevel of enjoyment: LConflict: NPerceived:-Game realism: N/AIntegration: N/A
Extent of:-analysis: LID of decision-outcomes: L
Understanding of Vision & Strategy: L
Decisions implemented: YDecisions based on AC: N
6 Level of engagement: MLevel of enjoyment: MConflict: YPerceived:-Game realism: HIntegration: H
Extent of:-analysis: LID of decision-outcomes: M
Understanding of Vision & Strategy: L
Decisions implemented: YDecisions based on AC: N
7 Level of engagement: LLevel of enjoyment: MConflict: NPerceived:-Game realism: LIntegration: H
Extent of:-analysis: LID of decision-outcomes: L
Understanding of Vision & Strategy: M
Decisions implemented: YDecisions based on AC: N
8 Level of engagement: HLevel of enjoyment: HConflict: YPerceived:-Game realism: HIntegration: H
Extent of:-analysis: HID of decision-outcomes: M
Understanding of Vision & Strategy: H
Decisions implemented: YDecisions based on AC: Y
9 Level of engagement: HLevel of enjoyment: MConflict: YPerceived:-Game realism: HIntegration: H
Extent of:-analysis: MID of decision-outcomes: M
Understanding of Vision & Strategy: H
Decisions implemented: YDecisions based on AC: Y
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10 Level of engagement: MLevel of enjoyment: HConflict: NPerceived:-Game realism: HIntegration: L
Extent of:-analysis: LID of decision-outcomes: L
Understanding of Vision & Strategy: H
Decisions implemented: YDecisions based on AC: Y
11 Level of engagement: LLevel of enjoyment: MConflict: NPerceived:-Game realism: LIntegration: H
Extent of:-analysis: LID of decision-outcomes: L
Understanding of Vision & Strategy: L
Decisions implemented: YDecisions based on AC: N
12 Level of engagement: HLevel of enjoyment: HConflict: YPerceived:-Game realism: N/AIntegration: H
Extent of:-analysis: MID of decision-outcomes: M
Understanding of Vision & Strategy: H
Decisions implemented: YDecisions based on AC: Y
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