Obastacles to using business simulation games in Croatian Bussiness Education Institutions.

Pejic Bach, Mirjana ; Zoroja, Jovana ; Strugar, Ivan 等

1. INTRODUCTION

Simulation games have proven to be a very valuable tool in education, since decisions made during the game allow immediate analysis and consequently represent high quality groundwork for the future business environment (Gilgeous & D'Cruz, 1996). The goal of simulation games is to introduce a participant into a virtual world where decisions can be made without risk. Simulation games allow students to actively participate in the educational process. During a simulation game, students acquire the skill of decision making and that of team or company leadership, thus the students learn-by-doing (Aldrich, 2005).

The goal of the paper is to define and discuss the obstacles to using simulation games in the educational process in Croatia. A questionnaire was conducted among professors at faculties of economics in order to identify these obstacles.

Faculties of economics play an important role in the education of students, as they are expected to provide more opportunities to combine the theoretical knowledge with the analytical skills that will prove useful in the future. Managers believe that educational institutions concentrate more on theoretical issues than on the practical application of different skills. Improving the educational process should be a daily basis concern since, along the theoretical knowledge, it is important to acquire skills in leadership, communication and decision making, because managers are looking for business students who have these skills (Owens Swift & Cook, 2004).

Research on the application of simulation games is being conducted around the world and show that the usage of simulaton games is increasing, although it still remains on a relatively low level (Faria & Wellington, 2004). Whereas numerous studies aim to show advantages to using simulation games, at the same time certain obstacles in applying these in education are being pointed out. A major obstacle, apart from financial investment, time and organizational constraints (Lunce, 2006) lies in the application of new technologies in teaching, which is a focus of Technology Acceptance Model (TAM) that explains the attitude of users toward simplicity and usefulness of new technologies (Di'ez & McIntosh, 2008). On the base of this founding we define expectations related with results of this research:

* Hypothesis 1: Few professors at faculties of economics in Croatia use simulation games (less than 50%);

* Hypothesis 2: The Technology Acceptance Model can be used for explaining application of simulation games in business education.

2. RESEARCH METHODOLOGY AND SAMPLE CHARACTERISTICS

The goal of this research is to identify obstacles to using simulation games at the Faculties of Economics in Croatia. A research questionnaire on the use of simulation games was conducted at these faculties from January to May 2009 (Zoroja,

2009).

The questionnaire was based on different published studies that tackle the usage of simulation games and on few in-depth preinterviews. The details was then adapted to the Croatian educational standard. The questionnaire was sent via e-mail to 64 people at different faculties of economics (five faculties). Respondents were selected according to their research interests by random choice method. Out of the total of 64 questionnaires, 50 respondents participated in the research, which forms a response rate of 78%.

According to academic rank, distribution of respondents is as follows: Masters of Science (40%), Associate Professors (16%), Full Professors (16%), Assistant Professors (18%), Research Assistants (4%) and Doctors of Science (6%).

Processing of the questionnaire was conducted by methods and techniques of descriptive statistics and logistic regression with the SPSS statistical software ver. 17.

3. EMPIRICAL RESULTS

In the research respondents were requested to state whether they apply simulation games in teaching or not. According to the results a small number of respondents (24%) use simulation games in class.

Divided by gender, the percentages of men (26%) and women (22%) who use simulation games are nearly the same.

The respondents were divided into three groups according to their rank: assistants (50%), assistants professors (18%) and professors (32%). The following are included in the category of assistants: research assistants, masters and doctors of science, whereas professors consider both full professors and associate professors.

Considering their academic rank, and taking into consideration only those respondents who use simulation games, the procentage of assistant professors and professors is higher than that of assistants.

Table 2 shows obstacles to using simulation games in class. Divided by usage of simulation games, the respondents were supposed to state what according to their point of view represents an obstacle and what does not. Most of respondents that use simulation games stated that the organizational limits (30%) and lack of funds (28%) are the biggest obstacles, whereas the respondents that do not use simulation games stated that the difficulty in adapting to new technologies (81%) is the biggest obstacle. Starting to use simulation games during class would mean changing the way a lecture is classically performed as well as adapting to new technologies.

In order to further clarify the listed obstacles in using simulation games, the logistic regression model was designed where the usage of simulation games at the faculties of economics is the dependent variable.

Results are presented in the Table 3, where estimated values for logistic regression parameters are presented with p-values in the parenthesis. The data fit the model rather well and parameter (difficulty in adapting to new technologies) is significant at 5% level. Also, gender (male) and academic rank (assistants and assistant professors) are significant at 5% and 1% respectively.

4. DISCUSSION

The results showed that most respondents (76%) do not use simulation games in class. The biggest obstacle for the respondents who do not use simulation games is the lack of knowledge of how to use them, and because of that they believe that simulation games are not necessary in education.

Another major obstacle stated by both the respondents that use the simulation games and those who do not is the lack of understanding by the university administration as well as the lack of funding. Such findings support our first hypothesis that few professors in Croatian business education use simulation games (less than 50%).

The research also indicates difficulties in changing classical teaching methods and in adapting to new technologies. This can be explained within the Technology Acceptance Model (TAM) that specifies the user's attitude towards simplicity and usefulness in applying new technologies. Consequently it confirms the other hypothesis according to which Technology Acceptance Model can be used for explaining application of simulation games in business education. Other factors, measured according to percentages of professors that use simulation games in business education, were not identified as relevant.

Results of this research confirm the results obtained in previously conducted researches (Lean et al, 2006) where obstacles to applying simulation games were also tackled and are the following: the time necessary for lecturers to prepare for a simulation game, a wrong choice of a simulation game, or a choice of topic that does not suit the interest of participants, lack of knowledge about the possibility to use simulation games, financial and technical problems.

Further studies are planned in the future to highlight the benefits of using simulation games. Furthermore, in-depth interviews with professors that use simulation games result in a choice of possible routes that may increase awareness of the advantages in using simulation games at the faculties of economics in Croatia.

5. REFERENCES

Di'ez, E., McIntosh, B.S. (2009). A review of the factors which influence the use and usefulness of information systems. Environmental Modelling & Software, Vol. 24, 588-602.

Faria, A. J., Wellington, W. J. (2004). A survey of simulation game users, former-users and never-users. Simulation and gaming, SAGE, 35; 178

Gilgeous, V., D'Cruz, M.A. (1996). Study of Business and Management Games. Management Development Review, Vol. 9, No. 1, 32-39

Aldrich, C. (2005). Learning by Doing, Pfeiffer, ISBN 0-7879-7735-7, USA

Lean, J., Moizer, J., Towler, M., Abbey, C. (2006). Simulation and Games: Use and Barriers in Higher Education. Active learning in Higher Education, 7; 227

Lunce, L. M. (2006). Simulations, Bringing the Benefits of Situated Learning to the Traditional Classroom. Journal of Applied Educational Technology, Vol. 3, No. 1

Swift, C., Cook, B. (2004). Sales Management Simulation: Bringing Reality to the Classroom. Proceedings of the Society for Marketing Advances. pp. 195-198.

Zoroja, J. (2009). Simulation Games in Business Economy. Specialization thesis. Faculty of Economics and Business, Zagreb

Tab. 1. Characteristics of respondents

 Using Not using
 simulation simulation
Characteristics of respondents games (%) games (%)

Gender Male 26 74
 Female 22 78
Total 24 76
Academic rank Assistants 20 80
 Assistant professors 22 78
 Professors 31 69

Tab. 2. Obstacles to using simulation games

Obstacles to Using Using Not Uusing
Simulation Games Simulation Simulation
 Games (%) Games (%)

Lack of funds Perceived as 28 72
 obstacle

 Not perceived 20 80
 as obstacle

Lack of Perceived as 20 80
understanding obstacle
from the
administration Not perceived 25 75
 as obstacle

Considered Perceived as 0 100
necessary in obstacle
education
 Not perceived 25 75
 as obstacle

Instructions on Perceived as 0 100
ways of usage obstacle

 Not perceived 27 73
 as obstacle

Difficulty in Perceived as 19 81
adapting to new obstacle
technologies
 Not perceived 30 70
 as obstacle

Difficulty in Perceived as
changing obstacle 21 79
classical teaching
methods Not perceived
 as obstacle 25 75

Organizational Perceived as 33 67
limits obstacle

 Not perceived 23 77
 as obstacle

Tab. 3. Results of logistic regression model (usage of
simulation games--dependent variable)

 B Sig.

Academic rank (assistants) 0,097919 *
Academic rank (assistant 2,34783 0,035404 **
 professors)
Academic rank (professors) 2,247493 0,10552
Gender (male) -1,7835 0,078441 *
Lack of funds 0,921471 0,455602
Lack of understanding from the 2,155657 0,127865
 administration
Considered necessary in education 24,60943 0,999202
Instructions on ways of usage 23,73563 0,998671
Difficulty in adapting to new 2,600595 0,039171 *
 technologies
Difficulty in changing classical -0,09734 0,921967
 teaching methods
Organizational limits 2,426559 0,187432
Constant -2,58674 0,115458

** statistically significant at 1% level

* statistically significant at 5% level