Paper Number: P1082 · 1. Introduction Simulation games have been incorporated into both...

Paper Number: P1082

Using Integrative Simulation in Enhancing and Assessing Learning: An Application of Computer Simulation Exercise

Yu-Jen Chen Lingnan University

Hong Kong

T S Chan Lingnan University

Hong Kong

Lai-Cheung Leung Lingnan University

Hong Kong

Ling-Yee Li Lingnan University

Hong Kong

Paper Number: P1082

Using Integrative Simulation in Enhancing and Assessing Learning: An Application of Computer Simulation Exercise

ABSTRACT

We examine how simulation game as a learning tool of learning marketing subject enhances

student learning. A total of 144 undergraduate students from a major public university in

Hong Kong registered in a core marketing course were involved in this research. Students’

learning effectiveness was assessed by using cognitive and affective approaches. The main

project objective is to use the experiences gained to further enhance and improve student

learning. The findings showed that the computer simulation exercise (CSE) could enhance

student learning in both the cognitive and affective learning domains.

Keywords: Computer Simulation Exercise, Simulation Games, Learning Effectiveness of

Simulation Games, Simulation Games as Learning Tools.

1. Introduction

Simulation games have been incorporated into both undergraduate and postgraduate programs

as a pedagogic tool to enhance student learning. A variety of games are available to serve

different pedagogical purposes in various study areas. Prior literature has identified a number

of reasons why using simulation game is a better leaning tool than other methods, including

case discussions or industry studies. One common reason is that simulations motivate

students’ participation and create a low risk environment. However, there were mixed results

regarding the use of simulation and future career success (e.g. Wolfe and Roberts, 1993;

Cronan and Douglas, 2012). Similarly, research in the past decades have reached mixed

conclusions on whether games could deliver the desired learning outcomes, particularly at the

higher levels of learning (Anderson and Lawton, 2009; Vos, 2014). In other words, the long

term learning outcomes from a simulation game has yet to come to a conclusion. In this

research, we aim to examine the pedagogical benefits delivered by simulation games and the

roles of simulation games in in fulfilling various learning assessment goals. Specifically, we

hope that the experiences and knowledge gained in this computer simulation exercise (CSE)

project could help improve the learning effectiveness for students.

2. Literature Review

Education today is characterized and envisioned by a student centered and outcome based

approach where student learning outcomes and active learning are emphasized (Allan, 1996;

Miles and Wilson, 2004). In parallel to this recent development is the emergence of using

simulation games as an educational tool where students are involved in an active learning

process (Auman, 2011). Given a real world scenario, students are required to apply the

theories and concepts learnt to decision making in a dynamic and interactive, but low risk

game environment. Since its introduction in 1950s to 1960s, simulation games have been

Paper no. P1082 Page 1 of 20

2015 AIBSEAR Penang Conference December 3-5, 2015

widely used as pedagogical tools in both undergraduate and postgraduate programs to assist

student learning (Faria and Wellington, 2004; Tao et al., 2015). A variety of games are now

available to serve different pedagogical purposes in various study areas such as strategic

management, strategic marketing, negotiation, international business etc. In the next section,

we introduce simulation game and the methodology used in examining its effect on students

learning.

2.1 Simulation Game Exercise

A simulation game typically consists of two important design elements: structure and agency

(Chin et al., 2009). Structure refers to the make-ups of the game environment in which the

game participants operate. The elements and constraints in the environment resemble the real

world situation that the participants face and make decisions. Some elements are relatively

stable, e.g. consumer needs and wants, and will only change over long periods. Others are

volatile and might even be influenced by the actions taken by the game participants, e.g.

pricing strategy. Agency refers to the choices that a game participant has to make according to

the opportunities and threats defined by the elements and constraints in the game environment

and the actions taken by the other participants. In most games, students are divided into

different teams and are sharing the same business scenario. Then, each team needs to make

certain business decisions in each round before the game is concluded after a given number of

rounds. The decisions in each period are contingent upon the business information available

and the decisions made by all the teams in previous periods. For instance, the decision of

raising the price or not may depend on how the price is set in the previous rounds, how other

teams set their prices before, and the estimated market demand in the current round. As such,

a wrong decision could be very costly because it seriously affects all the future business

performance and may require the team to invest in more resources to catch up with other



teams. The length of the game typically is determined by the instructor after considering the

nature of the course schedule. Some games may be conducted for up to 12 rounds, but most

instructors stop by the eighth round because effective learning seems to deteriorate thereafter

(Vos and Brennan, 2010). Redmond (1989) found that 5 to 6 rounds of games is sufficient for

generating effective learning. The build-in iterative process makes most game environments

highly interactive for the participants who have to be actively involved in the decision making

process (Vos, 2014). The dynamic nature, the interactions and the immediate rewards and

feedbacks explain why many instructors prefer to use games over other learning tools such as

case discussions, term projects, research papers or industry studies.

There are a number of pedagogical benefits identified in the literature why simulation games

have been popularly used by the instructors (e.g. Brennan and Vos, 2013; Faria and

Wellington, 2004; Faria and Whiteley, 1990; Vos and Brennan, 2010; Vos, 2014; See Table 1

for a summary of the benefits). Some studies found that there might be a causal link between

simulation participation and future career success (e.g. Wolfe and Roberts, 1993; Cronan and

Douglas, 2012). However, the causality was questioned by other studies as a number of

additional factors could contribute to the game participants’ higher salaries achieved and

quicker career advancement (Vos, 2014). It is therefore important to assess what specific

learning outcomes could be achieved by using simulation games.

Research in the past decades has reached mixed conclusions on whether games could deliver

the desired learning outcomes, particularly at the higher levels of learning (Anderson and

Lawton, 2009; Vos, 2014). The purposes of this paper are to examine the pedagogical benefits

delivered by simulation games and the roles of simulation games in in fulfilling various

learning assessment goals.



Table 1. Benefits of Simulation Games

Specific Benefits

To engage in experiential learning by making decisions in a complex, dynamic

and interactive environment.

To work with numeric and financial data, and market information available so as to assess performance and to plan and make decisions;

To understand the competitive landscape in real world businesses under a fairly low risk environment;

To get quick and immediate feedback on the consequences of the decisions submitted and to learn from the mistakes made;

To apply and integrate the concepts and theories learnt in the class in making decisions so that they can gain a better understanding of the concepts and theories taught;

To learn how the various business functional areas are integrated in making decisions;

To develop skills such as team building, leadership and time management that help them to prepare for their careers after graduation; and

To take part in enjoyable activities with satisfying rewards (e.g. to become the market leader in an industry) that foster student interest in learning.

2.2 Methodology

To examine the learning outcomes of computer simulation exercise (CSE), undergraduates

from a major university in Hong Kong participated the game as part of the course assessment

in a required marketing course for business students. The project supervisors conducted

several meetings to discuss the implementation of the CSE prior to the start of first semester.

The issues included the recruitment of a game administrator, the choice of the simulation

game, the timeline for the game, the learning assessment tools adopted and preparatory works

for conducting the game. We finally decided to adopt the computer simulation software in The

Marketing Game! (TMG) developed by Charlotte H. Mason and William D. Perreault, Jr. in

2000s to deliver the pedagogical benefits outlined above. We made this decision because the

introductory nature of the game in marketing decision making was suitable for our

undergraduate students who were taking this course as their first marketing course.

Meanwhile, the game was complex and challenging enough for the students to think for an

appropriate strategy and to make marketing decisions.



The game was set in a dynamic marketing environment where four teams (firms) from the

same class session were competing against each other in a voice recognition product industry.

Each team needed to make a list of managerial decisions based on both qualitative and

quantitative analysis of the information given in each decision period. These decisions

included pricing, product specification, promotion, advertising, channels selection, production,

and personnel, etc. Each team was given a budget where all financial relevant decisions had to

be made within the budget. We conducted a total of four decision periods given the time and

resources constraints. The timeline for carrying out the game each term is shown in Table 2.

As could be observed in the table, the time schedule was tight and the game had to be

introduced to the students early in the term when most students might not have a clear idea of

what marketing was at that time. Lectures were re-scheduled to let students learn the theories

and concepts needed to make decisions in the game environment.

Table 2. Timeline for the Marketing Game in Each Term

Week Activities

2 Team formation for The Marketing Game 3 Selection of CEO for each team and assignment of responsibilities to each team member 4 Introduction to the Marketing Game (class lecture supplemented with handouts)

5 First executive Meeting – Preparation for the initial marketing plan and first input decisions D1

(in class) First online survey

6

First executive briefing to the Chairman of the Board of Directors Submit inputs for Decision 1 (D1) and minutes of the first executive meeting Return D1 results and second executive meeting (in class) Interviews with students after class

7 Second executive briefing Submit inputs for D2

8 Return the D2 results Third executive briefing Submit inputs for D3

9 Return the D3 results Fourth executive briefing Submit inputs for D4

10 Return the D4 results Interviews with students after class

11 Preparation for the boardroom reporting Submit pp materials for boardroom reporting Second online survey

12 Boardroom Reporting (Presentation of The Marketing Game)



In order to ensure the role assignment in each team, each student team was required to report

in a business manner their input decisions of each game period to the Chairman of the Board

of Director (i.e. the project supervisor or the game administrator) after holding a meeting

among themselves. The chairman took the role as a coach to help students identify the

strengths and weaknesses of their strategy. The purpose of executive briefing was to allow

students to rectify their inputs. However, the chairman did not provide solutions or directions,

but rather to challenge the students’ analysis and inputs so that the students could rethink

carefully the rationale behind their decisions. The purpose of executive briefing was to allow

the project supervisor to keep track and monitor student performance over the entire game

period and to better understand the team dynamics and conflicts that took place.

Also, at the end of the CSE, each student team had to present in the class their strategy and

results for all the decision periods and the presentation was expected to include the following

items:

A brief overview of the initial target market, marketing objectives and marketing plan.

The modification of the target market, marketing objectives and marketing plan during the

four game periods and the rationales behind the changes.

The marketing mix decisions and the reasons for these decisions during the four game

periods.

Evaluation of the results achieved against the marketing objectives set.

The improvements that students would like to make if you continue to play the game

again for another three periods.

The objectives and planning that students would like to pursue if the game continue for

another three periods.



The students thus had an opportunity to review what they had learnt throughout the game. The

project supervisor also made use of this opportunity to evaluate the overall student learning

effectiveness.

2.3 Assessment of Learning Effectiveness

Most studies in assessing learning effectiveness of simulation games followed Bloom’s

taxonomy of educational outcomes (Vos, 2014). Bloom’s taxonomy classifies learning

outcomes into three domains: cognitive, affective, and psychomotor (Bloom et. al., 1956).

Each domain represents a hierarchy of learning proceeding from the lower levels of

knowledge comprehension to higher levels of leaning such as application, analysis, synthesis

and evaluation. For example, Gosen and Washbush (2004) found that assessment of

experiential exercise takes three forms: objective learning tests, perceived learning tests and

behavioral measures. Wolfe (1985) identified three desire outcomes in using simulation games

as learning tools: learning, attitudinal and behavioral. While the terminology used were

different, the classification frameworks were essentially the same as Bloom’s taxonomy.

The cognitive learning domain refers mainly to knowledge comprehension and critical

thinking. In the study by Anderson and Lawton (2009), they concluded that most studies on

simulation games seemed only to demonstrate effective learning at lower levels of Bloom’s

cognitive domain but not the higher levels of learning that simulation games attempt to

achieve. The affective learning domain considers students’ attitudes towards the simulation

experiences and what they perceive they have learnt from the games. A review of the

literature by Anderson and Lawton (2009) showed that game participants in general have

favorable attitudes towards the game experiences and perceive that they have learnt a lot from

the games. The psychomotor domain focuses on assessing change and development in

behaviors or skills. There have been some studies to examine the behavioral outcomes of



using simulation games. For example Wolfe and Roberts (1993) conducted a five year

longitudinal study that investigated the career success of those game participants five years

after joining the games and a causal link seemed to exist between game participation and

career success in terms of salary increases and promotions. However, Vos (2014) pointed out

that such conclusion seemed superficial because career success also depended on a number of

other factors such as students’ own ability and characteristics. It might well be that students

with better qualities and leadership skills were more in favor of joining the games.

To assess learning effectiveness, Chin, Dukes and Gamson (2009) suggested to use a pre-test

and post-test design in order to avoid the difficulty of assigning a control group when, in most

cases, all students are involved in the simulation exercises. You cannot ask some soldiers to

have guns while others not to have guns when they come to the battleground. Anderson and

Lawton (2009) recommended that learning effectiveness of simulation exercises could be

assessed in terms of cognitive knowledge about the discipline and attitudes towards the course

and/or discipline. This project followed the suggestions by Chin, Dukes and Gamson (2009)

and Anderson and Lawton (2009) and assessed the learning effectiveness of both the cognitive

and affective domains in simulation games.

This CSE project assessed the affective learning effectiveness by interviews with students and

online surveys and evaluated the cognitive learning effectiveness by student performance in

an individual assignment and in final examination. Interviews with students were conducted

regularly to identify the problems and difficulties facing students during the game periods.

Remedial actions were taken as far as possible to remove the barriers and improve student

learning. Regular feedbacks were also obtained from students concerning their attitudes

towards the game. One pre-CSE and one post-CSE online survey were conducted for each

term. The first survey was launched immediately after the introduction of the simulation game

to the students and the second one was introduced at the end of final game period. This



pre-test and post-test design allowed the project supervisor to assess students’ attitude towards

the CSE and what they perceived to learn from the game.

Student performance data in an individual assignment for the course and in the final

examination were also collected to further evaluate how simulation pedagogy improved

learning effectiveness. The individual assignment required the student to write a five-year

marketing plan for a given scenario facing a chosen company. The framework for developing

the marketing plan was the same as the framework for developing a marketing strategy given

in the CSE in this project. It was therefore expected that the CSE should assist students to

better prepare for writing the plan and for taking the final exam. The individual assignment

and the final exam were chosen because these two assessment components required students

to apply and integrate what they had learnt in the class and hence they represented the higher

levels of leaning in Bloom’s cognitive learning domain and the learning outcomes to be

achieved by using simulation exercises.

2.4 Findings for Assessment of Learning Effectiveness

Online Survey

One pre-CSE and one post-CSE online survey were conducted for each term. Students’

attitudes towards learning from the game were measured by three dimensions ranging from

lower levels to higher levels of learning (refer to the questionnaire in Attachment 3):

Students’ appreciation of marketing knowledge learnt from CSE

Students’ attitudes towards the application of marketing knowledge and other management

skills learnt in the class

Students’ attitudes towards the conceptual reasoning and analytical skills required in

making decisions in the game



The overall evaluation of the game was measured by three attributes, each of which

summarized each of the three learning effectiveness dimensions described. The major results

are presented below.

Demographic Profile of the Respondents

The profile of the respondents for each term is shown in Table 3 based on the information of

the pre-CSE survey for each term. The profile of the respondents in the post-CSE survey was

similar to the pre-CSE survey and was not reported here.

Table 3: Demographic Profile of the Respondents based on pre-CSE Surveys

Demographic Variable

Values First Term (n=67)

Second Term (n=77)

Statistical Significance (Chi-square)

Gender Male 34.3% 23.4% Insignificant Female 65.7% 76.6%

Year of Study Year 1 1.6% 3.9% P < .01 Year 2 11.9% 48.2%

Year 3 74.6% 42.9%

Year 4 11.9% 5.2%

Mode of Study Full Time 70.1% 84.4% P < .05

Others 29.9% 15.6%

Study Major Arts 1.5% 5.2% Insignificant

Social Science 1.5% 3.9%

Accounting 22.3% 29.9%

Finance and Insurance

23.9% 10.3%

HRM 16.4% 16.9%

Marketing 25.4% 27.3%

Others 9.0% 6.5%

Total 100% 100%



The Appreciation of Marketing Knowledge

The results of the learning attributes for students’ appreciation of the marketing knowledge

learnt from taking part in the CSE are shown in Table 4. Two learning attributes, “The game

makes me aware of the importance of information to assist decision making” and “The game

makes me aware of the influence of competitive environment on sales performance”, were

found significant in this study in the first term, but all attributes were insignificant in the

second term.

Table 4: The Appreciation of Marketing Knowledge learnt from CSE

Attributes contributed to Student Learning

Pre-CSE (1st Term)

(n=67)

Post-CSE (1st Term)

(n=61)

Statistical Significance

(t-test)

Pre-CSE (2nd Term)

(n=77)

Post-CSE (2nd Term)

(n=60)


(t-test) The Game makes me aware of the elements considered in developing a marketing plan.*

4.87 5.19 Insignificant 5.05 5.10 Insignificant

The Game makes me aware of the decisions involved in marketing activities (i.e. the decisions for target market and 4Ps).


The Game makes me aware of the impact of the decisions in other functional areas on marketing activities (e.g. production order quantity decisions, hiring decisions for the salespeople etc.).


The Game makes me aware of the importance of information to assist decision making.

5.09 5.60 P < .05 5.29 5.20 Insignificant

The Game makes me aware of the influence of competitive environment on sales performance.

4.91 5.50 P < .01 5.23 5.32 Insignificant

* All measurement items were measured by 7-point Likert scales with 1=strongly disagree and 7=strongly agree.

The Application of Marketing Knowledge and Other Management Skills

Students’ attitudes towards the application of marketing knowledge and other management

skills to decision making in the game were presented in Table 5. Only one learning attribute in

the first term, “The game assists me to learn how to formulate decisions to meet competition”,

was found significant. All other attributes were perceived as similar between the pre-CSE and

post-CSE survey in both terms.



Table 5: The Application of Marketing Knowledge and Other Management Skills learnt


Pre-CSE (1st Term)

(n=67)

Post-CSE (1st Term)

(n=61)


(t-test)

Pre-CSE (2nd Term)

(n=77)

Post-CSE (2nd Term)

(n=60)


(t-test)

The Game assists me to learn how to analyze and use information to make decisions.*


The Game assists me to learn how to integrate the decisions for 4Ps and in other functional areas to maximize sales performance.


The Game assists me to learn how to formulate decisions to meet competition.

4.85 5.33 P < .05 5.08 5.27 Insignificant

The Game improves my communication skills


The Game fosters leadership development


The Game encourages teamwork and collaborative behavior



The Attitudes towards the Conceptual Reasoning and Analytical Skills required in the Game

Students’ attitudes towards the conceptual reasoning and analytical skills emphasized in the

game for decision making are indicated in Table 5. The first learning attribute in Table 5, “The

game urges me to think ahead where the market should be headed”, was found significant in

the first term while all other attributes were not significant in both terms.

To summarize the findings presented, the following student learning attributes were very

much appreciated by the students after the completion of the CSE:

The Game makes me aware of the importance of information to assist decision making

The Game makes me aware of the influence of competitive environment on sales

performance

The Game assists me to learn how to formulate decisions to meet competition



The Game urges me to think ahead where the market should be headed

The Overall Evaluation of The Game

Three attributes, one for each measurement dimensions outlined previously were used to

measure students’ overall evaluation of the game. The findings are showed in Table 6. The

results indicated that students’ perception of the learning attributes greatly improved in the

first term but not in the second term. Similar pattern was found in each measurement

dimension shown in previous tables. One plausible explanation to interpret the results in the

second term was that the prompt remedial actions taken in the first term according to the

students comments during the interviews smoothed the running of the game in the second

term and hence the student expectations prior to the CSE matched with the performance

perception after the CSE. The significantly higher ratings of the pre-CSE survey in the second

term compared to that of the first term further confirmed this explanation.

Overall speaking, the students in the first term expressed favorable attitudes towards the

following learning outcomes:

Table 6: Students’ Attitudes towards Conceptual Reasoning and Analytical Skills required in the game


Pre-CSE (1st Term)

(n=67)

Post-CSE (1st Term)

(n=61)


(t-test)

Pre-CSE (2nd Term)

(n=77)

Post-CSE (2nd Term)

(n=60)


(t-test)

The Game urges me to think ahead where the market should be headed*

4.93 5.40 P < .05 5.22 5.25 Insignificant

The Game requires me to predict where the competition will be.


The Game encourages me to plan my decisions ahead.


* All measurement items were measured by 7-point Likert scales with 1=strongly disagree and 7=strongly agree

The Game increases my understanding of the knowledge in marketing

The Game allows me to apply what I have learned in the class to real situations

The Game improves my conceptual reasoning and analytical skills



Student Performance in the Individual Assignment and Final Examination

The course Marketing Management was taught by a teaching team consisting of two to

sometime four members with membership varied year by year. Although all subject

instructors followed the same assessment rubric to do the markings, there were still some

differences in instructors’ assessment styles, subjective views on the answers provided and the

marking ranges adopted. Only two sections of students were included in the student

performance analysis for this project as these two sections were taught by the same project

supervisor in the last two years. The results are presented in Table 6.

The results showed that student performance was improved in the year 2014-15 compared to

performance in 2013-14. Although the attribution of student performance improvement to the

implementation of CSE might be subject to history errors and influences of the third factor as

there was no control group designed for the same game period, observations by the project

supervisor in the same game period indicated that these errors and influences should be

minimal, even if they could not be totally eliminated.

Team Formation and Group Dynamics

Another interesting result concerning the group dynamics in team performance was identified.

With regard to the two sections of students selected, the team membership in one section was

assigned by the project supervisor while that of the other section was decided by the students

themselves. The game performance of each section for first term and second term is shown in

Table 7. According to the results of Table 8, it seems that game performance for teams with

membership decided by the project supervisor was slightly better than the teams with

membership decided by the students themselves. It might be that the project supervisor tended

to allocate students with different majors in a team which better fostered group dynamics and

hence improved team performance. However, Anderson (2005) found that it was the group



cohesion and willingness to work together interdependently that contributed to the team

success more than the heterogeneity of ideas coming from different experts in a group. The

findings in this research might suggest a more effective way to form teams in carrying out the

group assignments.

Table 7: Student Overall Evaluation of the Learning Attributes for CSE


Pre-CSE (1st Term)

(n=67)

Post-CSE (1st Term)

(n=61)


(t-test)

Pre-CSE (2nd Term)

(n=77)

Post-CSE (2nd Term)

(n=60)


(t-test) The Game increases my understanding of the knowledge in marketing*

4.79 5.41 P < .01 5.14 5.27 Insignificant

The Game allows me to apply what I have learned in the class to real situations

4.46 5.10 P < .01 4.94 5.10 Insignificant

The Game improves my conceptual reasoning and analytical skills

4.82 5.29 P < .05 5.12 5.13 Insignificant


Table 8: Student performance in Individual Assignment and Final Examination

Assessment Method

Year 2013-14 First Term

(n=66)

Year 2013-14 Second Term

(n=61)

Year 2014-15First Term

(n=61)

Year 2014-15 Second Term

(n=55)

Statistical Significance (ANOVA)

Individual Assignment

62.6* 61.4 67.5 67.7 P < .01

Final Examination

53.2* 53.7 57.9 58.9 P < .01

*Average score on the basis of 100.

2.5 Conclusions

This research studies the impact of using simulation games on students learning. The

simulation game selected in this project allowed the students to engage in decision making in

a low risk, dynamic and interactive environment. Through a series of decision making

activities, students learnt how to interpret the information and results after each game period,

how to conceptualize the situation faced, how to formulate the operational and strategic

decisions for the next period, how to integrate theories and concepts with practice, and how to

cope with the team dynamics throughout the game. The project findings showed that

simulation games assisted learning in both the cognitive and affective learning domains. This



project also highlighted a number of implementation issues and challenges facing students

and instructors when using simulation games as learning tools. It is hoped that the experiences

gained in this project could further improve student learning and provide insights to

instructors in other courses who want to adopt simulation games as part of the curriculum.

Some challenges for students

Learning from simulation games requires students to get involved in the process of learning

cycle. Herz and Mertz (1998) indicated that the learning cycle consists of four stages:

concrete experience, reflective observation, abstract conceptualization and active

experimentation. In essence, simulation games allow the students to make decisions according

to the structure game environment and the information provided in each decision period;

reflect and observe the consequences of their actions; develop a conceptual understanding of

the actions taken and the situation faced by analyzing and synthesizing the information learnt

and integrating the theories and concepts with the situation faced, and finally make new and

improved decisions based on the conceptual understanding. Furthermore, the learning effects

are generally higher at the beginning of the game and then deteriorate towards the end of the

game (Vos, 2014). To make the learning process more effective, Tao, Yeh and Hung (2015)

suggested that different activities should be designed throughout the game period to sustain

the development of knowledge and skills.

As pointed out in previous sections, students’ reactions to the CSE came into two extremes.

Some students, especially those who were non-business majors, felt at the beginning of the

game overwhelmed and confused with the vast amount of information provided. This was

particular serious when the student had missed the introduction session of the CSE. It was

therefore important to remind the students at the early stages of the learning cycle the active



learning process involved in CSE and missing the CSE introduction session impeded the

whole learning process. In other words, students’ active participation in the game is required

to make the learning cycle effective. Executive briefings and boardroom report were two

activities to enhance the effectiveness of the learning cycle.

Debriefing was another step to enhance student learning (Petranak, 2000; Crookall, 2010).

Debriefing provides the conceptual framework and theories that guide the students to gain

something out of their learning experiences from the game. Debriefing usually occurs after

each round of the game. The instructor is not only to provide some feedbacks, but to initiate

active discussions with the students so that they can self-reflect the actions taken and connect

their experiences gained over different game periods, and hence deepen their understanding of

the theories and concepts in marketing. Crookall (2010) argued that actual learning for

simulation games not comes from playing the games, but from effective debriefings.

Some challenges for instructors

In addition to the issues of selecting the right game and debriefing mentioned, it is also a

challenge facing instructors to work together in using the simulation games (Vos and Brennan,

2010). First, teaching members have to believe in the pedagogical benefits delivered by using

the games over such traditional methods as lectures and case studies. Second, the instructors

have to be well versed with using the games in every aspect so that they can be confident in

dealing with all possible queries from students. This is challenging to those instructors who

are not exposed to using the games previously. Third, it takes a lot of time to prepare and plan

the games, given that the time is available in view of other responsibilities assumed. These

barriers prohibited the wider use of simulation games as learning tools. Vos and Brennan

(2010) found that those who used the simulation games as a learning tool were usually those

game enthusiasts.



To make simulation game a more effective learning tool, instructors have to get involved

actively in the process as the pedagogical benefits of the games do not come automatically.

Taylor, Backlund and Niklasson (2012) recommended a coaching role for the instructor. In

fact, an instructor has to assume multiple roles that include providing regular feedbacks,

integrating the theories and concepts with the students’ experiences, increasing the levels of

difficulty to keep students involved and challenged over all the game periods, and reducing

team members’ conflicts and stress throughout the game so that some members are not

discouraged with the game experiences.

Another challenge facing the instructors in using simulation games is how to assess student

learning. In general, multiple assessments at different stages of the game were recommended

(Michael and Chen, 2005). Chin, Dukes and Gamson (2009) also suggested the use of pre-

and post-tests to assess learning effectiveness. However, instructors have to consider a

balance between workloads and validity of learning effectiveness assessment. Too many

assessments conducted might mean adding too much workload to both the students and the

instructors and reduce both learning and teaching effectiveness. Given the research and

teaching pressures, and other administrative responsibilities in the university, instructors are

therefore discouraged and reluctant to adopt simulation games due to the extensive

preparations, planning and administrative tasks involved, even if they are fully aware of the

pedagogical benefits of the games. Additional university supports are thus required to

encourage the use of simulation games as learning tools for students.



3. References

[1] Allan, J. (1996), “Learning Outcomes in Higher Education,” Studies in Higher Education, 21(1), 93-108.

[2] Anderson, J. R. (2005), “The Relationship between Student Perceptions of Team Dynamics and Simulation Game Outcomes: An Individual Level Analysis,” Journal of Education for Business, 81(2), 85-90.

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Paper Number: P1082 · 1. Introduction Simulation games have been incorporated into both...

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