تاثیر بازی شبیه سازی در آموزش مدیریت عملیات

This study presents a new simulation game and analyzes its impact on operations management education. The proposed simulation was empirically tested by comparing the number of mistakes during the first and second halves of the game. Data were gathered from 100 teams of four or five undergraduate students in business administration, taking their first course in operations management. To assess learning, instead of relying solely on an overall performance measurement, as is usually done in the skill-based learning literature, we analyzed the evolution of different types of mistakes that were made by students in successive rounds of play. Our results show that although simple decision-making skills can be acquired with traditional teaching methods, simulation games are more effective when students have to develop decision-making abilities for managing complex and dynamic situations.

The present generation of college and university students has never experienced a world without personal computers (PCs). Many have spent much time playing computer games and are now very skilled at learning and applying complex sets of rules through game playing. According to Proserpio and Gioia (2007), the learning style of the new ‘virtual generation’ (V-gen) is very different from that of former generations. It is much more visual, interactive, and focused on problem-solving. While this could be seen as a threat to the traditional teaching style, based on verbal knowledge transfer and Socratic debates, it could also be seen as an opportunity to develop simulation games that build on V-gen skills and encourage the learning of management principles and practices. Simulation games are but one way to acquire knowledge; we do not suggest that they can or should replace lectures, readings, case studies or other learning methods, which have been applied. They have also been around for many years, long before PCs were widely available. Nevertheless, now that a large proportion of students own powerful and interconnected laptops, it is easy to consider simulation games as an alternative to other types of problem-solving activities, one that can provide a complex and rich virtual environment conducive to deep learning. First applied in training in the military and the aeronautics industry, simulation games are now used in the teaching of medicine, nursing, engineering, management, and several other fields. A growing body of literature describes new simulation games and measures their impact on student learning. This article will begin with a review and integration of the existing literature, focusing particularly on the various methods used to assess learning. To contribute to the current literature, the article will also present a new simulation game and analyze its impact on operations management education. The article is organized as follows: Section 2 presents an overview and synthesis of current literature; Section 3 introduces the new simulation game; Section 4 presents the methodology used to evaluate its efficacy; and Section 5 details and analyzes the results. The article concludes with a brief discussion of the limitations of the research and the next steps to be considered.

In this section, we present the results of the lost sales and mistakes made by the undergraduate teams during the first and second halves of the game. Because the variables we measured did not follow a Gaussian bell-shaped distribution, we opted for non-parametric tests (the sign test and Wilcoxon signed-ranks test) rather than Student’s t-test to calculate the p values. Table 5 shows that the mean and the standard deviation of the number of MRP (type I - purchased items) mistakes made by the teams were stable during the game. Table 6 indicates that 28 teams reduced the number of times this MRP mistake was made during the game, whereas 32 teams made this mistake more often during the second half than during the first one. According to paired non-parametrical tests with a p level of 5%, this slight difference is not statistically significant (sign test p value = 0.699; Wilcoxon signed-ranks test p value = 0.752). 34 teams made no mistakes during the entire game. Taking into account the lectures, homework and exam, it appears that the students had already reached a steady-state skill level and that the added value of the simulation was not significant with regard to the calculation of raw materials and purchased items.