'Experiences of Using a Business Strategy Simulation: Lessons for Promoting Effective Learning'...

Jonathan D. Moizer

Jonathan Lean

Gordon Smith

Mike Towler

Plymouth Business School

University of Plymouth

Plymouth

PL4 8AA

Tel: 01752 232824

Email: [email protected]

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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

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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


4 Level of engagement: HLevel of enjoyment: MConflict: N/APerceived:-Game realism: HIntegration: M

Extent of:-analysis: HID of decision-outcomes: N/A



5 Level of engagement: LLevel of enjoyment: LConflict: NPerceived:-Game realism: N/AIntegration: N/A




6 Level of engagement: MLevel of enjoyment: MConflict: YPerceived:-Game realism: HIntegration: H

Extent of:-analysis: LID of decision-outcomes: M



7 Level of engagement: LLevel of enjoyment: MConflict: NPerceived:-Game realism: LIntegration: H




8 Level of engagement: HLevel of enjoyment: HConflict: YPerceived:-Game realism: HIntegration: H

Extent of:-analysis: HID of decision-outcomes: M



9 Level of engagement: HLevel of enjoyment: MConflict: YPerceived:-Game realism: HIntegration: H




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10 Level of engagement: MLevel of enjoyment: HConflict: NPerceived:-Game realism: HIntegration: L




11 Level of engagement: LLevel of enjoyment: MConflict: NPerceived:-Game realism: LIntegration: H




12 Level of engagement: HLevel of enjoyment: HConflict: YPerceived:-Game realism: N/AIntegration: H




28

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Word count (excld. Abstract, references and figures):4552

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