The Effects of Computer-Simulation Game Training on ...

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The Effects of Computer-Simulation Game Training on Participants’ Opinions on Leadership Styles Authors: Anna Siewiorek, Andreas Gegenfurtner, Timo Lainema, Eeli Saarinen and Erno Lehtinen Title: The effects of computer-simulation game training on participants’ opinions on leadership styles Journal: British Journal of Educational Technology Year: 2013 Version: Author’s final draft

The original publication is available at: http://onlinelibrary.wiley.com/doi/10.1111/bjet.12084/abstract Please cite the original version: Siewiorek, A., Gegenfurtner, A., Lainema, T., Saarinen, E., & Lehtinen, E. (2013). The effects of computer-simulation game training on participants’ opinions on leadership styles. British Journal of Educational Technology, 44 (6), 1012-1035. doi: 10.1111/bjet.12084

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The Effects of Computer-Simulation Game Training on Participants’ Opinions on Leadership Styles Anna Siewiorek, Andreas Gegenfurtner, Timo Lainema, Eeli Saarinen and Erno Lehtinen Abstract: The objective of this study is to elucidate new information on the possibility of leadership training through business computer-simulation gaming in a virtual working context. In the study, a business-simulation gaming session was organised for graduate students (n = 26). The participants played the simulation game in virtual teams that were geographically dispersed and that were brought together by the use of technology. Before the gaming session, the team leaders were preselected and trained in how to operate the simulation game. Data consist of pre- and posttest questionnaires (the Multifactor Leadership Questionnaire measuring transformational, transactional and passive/avoidance leadership styles) and answers to open-ended questions. The results showed the difference in participants’ opinions on leadership styles before and after the training. After the gaming sessions, team members scored lower in transformational and transactional scales than team leaders. Only team leaders’ leadership styles correlated with game performance. However, shared leadership among team members was typical for most successful teams. Implications for leadership training are discussed. Practitioner Notes What is already known about this topic • There have been attempts to use simulation games for corporate leadership training but not in higher education. • It is not effective to teach leadership styles through conventional, lecture-based teaching methods. • Students are more highly motivated by simulation games than by more traditional instructional presentations. What this paper adds • Novel implementation of leadership training through simulation gaming in higher education. • The simulation game training changed participants’ opinions on leadership styles. • Shared leadership among team members was typical for most successful teams. Implications for practice and/or policy • More simulation games should be implemented into higher education to advance the participants’ understanding on the leadership styles. • The discrepancy between team members’ and team leaders’ interpretations as to how leadership styles were applied during the study offer powerful experience to be used in future leadership trainings. • The results provide important guidance for instructors to design simulation trainings to enhance leadership styles learning. Introduction Many educators consider games and simulations as useful tools in teaching topics and skills that have proved to be difficult to deal with in traditional educational situations. Difficult

Computer-Simulation Game Training 3 teachable skills include many complex and ill-defined skills such as leadership. However, there is still relatively little research-based knowledge of the impact of games on leadership training. This study examines the opportunities of using a collaborative computer-simulation game as a leadership training tool. Learning with games and simulations When we discuss the learning environment of this study, we refer to it as a simulation game— instead of a game or a simulation. On one hand, the word simulation is often considered too mechanistic for educational purposes. Simulation refers to activities where an optimum for some problem is searched for, while this is not usually the aim of an educational game (Lainema, 2003). On the other hand, the word game can imply time wasting, not taking things too seriously and engaging in an exercise designed purely for entertainment. Authenticity and realism have a role in business games such as the one described in this paper as they aim at providing a learning experience, which illustrates some of the critical features of the reality to the participants (Saunders, 1995). Keys and Wolfe (1990) define a (management) simulation game as a simplified simulated experiential environment that contains enough verisimilitude, or illusion of reality, to include real-world-like responses by those participating in the exercise. The concept of simulation gaming seems to offer the right combination and balance between the two. Simulation gaming is also the term that the educational gaming community has adopted (Greenblat Stein, 1988). Games and simulations provide new opportunities to deal with complex and risky reallife processes in a safe educational context (Gee, 2008; Winn, 2002). Studies have shown, for example, that simulation games can successfully foster learning of complex problem-solving (Tennyson & Breuer, 2002), decision-making (Salas, Wildman & Piccolo, 2009; Tompson & Dass, 2000) and collaboration skills (Leemkuil, de Jong, de Hoog & Christoph, 2003). One of the key features of simulation games is that they provide outcomes and feedback in real time (Laurillard, 1998). Some of the educational games can be played in teams in which each person has a distinctive assigned role and team members have to coordinate their activities, just like in modern work- places (Hakkarainen, Palonen, Paavola & Lehtinen, 2004; Lehtinen, 2003; Siewiorek, Saarinen, Lainema & Lehtinen, 2012). Simulating a workplace team context in multiplayer digital training affords the chance to incidentally learn social skills, such as leadership, in realistic and authentic learner-centred environments (Gegenfurtner, 2011; Knogler et al., 2013; Lainema & Lainema, 2007; Siewiorek, 2012). In spite of a growing body of literature highlighting the educational potential of computer games and simulations, some obstacles can make simulation games difficult to implement in educational settings. For example, learners may perceive the simulation to be unrealistic or perceive the group collaboration to be inefficient and thus they lose interest and the motivation to play (Adobor & Daneshfar, 2006; Gegenfurtner & Vauras, 2012; Gegenfurtner, Veermans & Vauras, 2013). In addition, the evidence supporting the educational potential of computer games is still limited and contradictory, particularly regarding the effectiveness of games for concrete educational purposes (Jenkins, 2002; Ritterfeld, Shen, Wang, Nocera & Wong, 2009). Many game studies are either anecdotal or hypothetical. Anderson and Lawton (2009) summarise that today, the effi- cacy of business games in achieving cognitive learning outcomes is still unclear. There are several pedagogical approaches that can be used when simulation games are applied, such as learning by doing, learning from mistakes, goal-oriented learning and roleplaying (Prensky, 2001). Simulations and games have been associated with many learning theories. These theories are, among, others, discovery learning (de Jong & van Joolingen, 1998), situated learning (Winn, 2002), implicit learning (Ciavarro, Dobson & Goodman, 2008), activity theory (Kuutti, 1996) and constructivism (Kebritchi & Hirumi, 2008). Simulation games have also been characterised as a form of experiential learning (Kolb,

Computer-Simulation Game Training 4 1984) because the process of knowledge creation relies on the transformation of selfexperience (Haapasalo & Hyvönen, 2001). The cycle of experiential learning is very similar to the organisational structure of typical games (Herz & Merz, 1998). According to Gredler (1996), educational games are experiential exercises. They offer here-and-now concrete experiences to validate and test abstract concepts presented in the gaming environment. Constructivism focuses on the process of knowledge construction and the development of reflexive awareness of that process (Bednar, Cunningham, Duffy & Perry, 1992). Learning is considered to be an active process, in which meaning is developed based on experience. Learning should also be situated in a rich context based on authentic tasks. The game-based simulation environment used in the study includes many of the characteristics that have been highlighted in theories of experiential learning and constructivism. Approaches to leadership Research on leadership has expanded over the years and many theorists have tried to define leader roles and leadership processes. For example, DuBrin (1990) defined leadership as “the process of influencing the activities of an individual or group to achieve certain objectives in a given situation” (p 255). Wills (1994), however, defined a leader in brief terms: “The leader is one who mobilizes others toward a goal shared by leaders and followers” (p 17). One common element among the various definitions has involved the process of influence (Bryman, 1992). Leadership involves persuading people to set aside, for a time, their individual concerns and pursuits and work in support of the communal interest. The broad and varied studies on leadership suggest that there are many appropriate ways to lead. However, there is no agreement upon a working definition of leadership, or on what good or effective leadership should be (Smith, Montagno & Kuzmenko, 2004). Instead, there are many leadership style definitions. In our earlier studies (Siewiorek & Gegenfurtner, 2010; Siewiorek & Lehtinen, 2011; Siewiorek et al, 2012) we have analysed how experiences in business simulation games and game environments are related to different leadership styles, including such as heroic, post heroic, authoritarian, shared and democratic leadership. In this study we focus on transactional and transformational leadership styles. According to Burns (1978), the difference between transformational and transactional leadership is in terms of what leaders and followers offer one another. Transformational leaders offer a purpose that transcends short-term goals and focuses on higher order intrinsic needs. Transactional leaders, in contrast, focus on the proper exchange of resources. If transformational leadership results in followers identifying with the needs of the leader, the transactional leader gives followers something they want in exchange for something the leader wants (Kuhnert & Lewis, 1987). The Multifactor Leadership Questionnaire (MLQ, Bass & Avolio, 2000) used in measuring transformational and transactional leadership styles also consists of a third dimension describing passive/avoidance leadership. Passive leaders avoid specifying agreements, clarifying expectations, and providing goals and standards to be achieved by followers. Passive leadership often occurs when there is an absence or avoidance of leadership. In addition to transformational and transactional styles, other leadership styles are to be found in the literature. Heroic leadership is characterised by omnipotence, rightness and codependency as the main characteristics of a leader. Post-heroic leadership refers to empowerment of members, risk taking and the development of members. A widely used classification is to describe leaders as authoritarian or democratic. Authoritarian leaders have all the control and determine all the policies, activity steps and work tasks, whereas democratic leaders encourage group decisions and build organisational flexibility. Close to authoritarian leadership styles are coercive leaders, who demand immediate compliance to their orders and dictate each step taken. There has been a need for new leadership forms— particularly in knowledge-intensive organisations and teams— characterised as shared leadership, where there is mutual influence and all members participate in the decision-

Computer-Simulation Game Training 5 making process (Bass & Bass, 2008; Crevani, Lindgren & Packendorff, 2007; Goleman, 2000). A new challenge for the leadership is due to globalisation and development of information and communication technology, more and more work is done in virtual teams and organisations (Lähteenmäki, Saarinen, Fischlmayr & Lainema, 2010). Leadership training and simulation gaming Most leadership training initiatives fail to train leaders because typical programs teach leadership theory, concepts and principles. This training promotes leadership literacy but not leadership competence (Allio, 2005). However, potential candidates become leaders by practice, by perform- ing deliberate acts of leadership. Some researchers claim that many of the qualities and attributes that assist them in leadership effectiveness are innate (Blank, 2001). While at the same time, it is obvious that early childhood development, education and later on-the-job experiences encourage and nurture leadership abilities (Bass, 1990; Conger, 1992). Skills and abilities utilised by leaders such as communicating, problem solving, visioning, decision making and negotiating can be developed by proper leadership training. Although leadership training is relatively new in the literature, there is an increasing body of knowledge on the issue (eg, Day, 2001; McCauley & Douglas, 2004; Palus & Horth, 2004). Leadership competence develops when an individual is forced to address the challenge of innovating, inspiring and adapting. The leader in training will develop a portfolio of behaviours to draw upon to respond to specific challenges in the future. In addition, evidence suggests that the most effective leadership programs will focus on building self-knowledge, and skills in rhetoric and critical thinking. For example, facing adversity, struggling with unfamiliar situations, exposure to different people, problem-solving activities and hardships and making mistakes are reported to be the most developmental types of experiences (Dentico, 1999). McCall (2004) suggests that the primary source of learning leadership is experience. Experience as a leader or a group member in demanding and challenging situations seem to be particularly beneficial for learning leadership skills. This kind of experience and systematic reflection of the experiences can be facilitated in previously planned simulated environments (Johnsen, Eid, Pallesen, Bartonen & Nissestad, 2009). Simulation gaming in teams serves as a promising platform for leadership training within formal education because, in these environments, leader trainees can experience challenges of leadership within complex situations, which includes communication, conflict resolution, delegation, motivating, decision making and problem solving. On the other hand, participants of the groups can evaluate different leaders in, at least partly, standardised situations. One of the methods to evaluate the learning process during leadership training is to compare the relationship between a leader’s self-evaluation and group members’ evaluations of the leader’s behaviour. According to previous studies, leaders evaluate their leadership style more positively than group members do, but, with increasing training, the self-evaluation and the others’ evaluations tend to come closer together (Johnsen et al, 2009). Researchers have tried for decades to examine the effectiveness of simulation games in management and leadership training. For example, Farrell (2005) compared simulation games with traditional teaching methods for undergraduate students in business management and found that students perceived the simulation game as a more effective learning tool. Li, Greenberg and Nicholls (2007) conducted a similar study with MBA students. They also showed that the students thought the simulation game was superior to a lecture-centred approach. Washbush and Gosen’s (1998) study, in which they compared the before and after scenarios following an enter- prise simulation game played by teams of undergraduate business students, showed that students improved their exam score after the simulation. The effectiveness of the simulation game in teaching operations management was demonstrated in Olhager and Persson’s (2006) study. In addition, the research implies that experiential approaches appear to be the most successful in meeting the leadership training objectives

Computer-Simulation Game Training 6 (Bass, 1990). One of the aims in planning leadership training simulations is to provide participants with challenging experiences, which increase awareness of their own leadership behaviour and of the demands of different situations (Raybourn, 2006). Purpose of the study This study examines the outcomes of using a collaborative computer-simulation game as a leadership training tool. In particular, we are interested in whether this environment could serve as a tool to provide participants with the experience of leadership styles in practice. The focus of the study is to examine if students’ opinions on leadership styles before and after participating in a computer-supported collaborative-gaming session will change. A second focus is to identify if their opinions on leadership differ depending on the participant’s role (leader vs. team member) in the team. In addition, we aim at observing what kind of new challenges distance members participating through network tools bring for the group leadership. We are also interested in investigating if there are any effects of leadership style on team performance. Research questions and hypotheses Is there any difference in team leaders’ and team members’ opinions on leadership styles after participating in collaborative computer-simulation game training? The two-day gaming session without systematic feedback is not expected to be enough for the development of a reciprocal awareness of group processes between the team leader and the team members. Thus, it is assumed that in the posttest, the team-leaders’ self-evaluations of leadership styles will differ from team members’ evaluations (Hypothesis 1a). However, it is expected that the challenging experiences during the simulation-game sessions increase team leaders’ and team members’ awareness of the leadership styles (Hypothesis 1b). This can be seen as changes in their evaluations after the experience when compared with their ideal ratings before the experience. To what extent does leadership style correlate with team performance? It was expected that team performance at the end of the collaborative computer-simulation game training would correlate positively with transformational leadership (Hypothesis 2a) and transactional leadership (Hypothesis 2b) and would correlate negatively with passive/avoidance leadership (Hypothesis 2c). What kind of leadership processes emerges in teams during the gaming sessions? It was expected that various kinds of leadership processes would emerge in teams during the simulation-gaming sessions due to leaders being preselected before the sessions and given leadership authority and responsibility. Method The simulation computer game RealGame, http://www.realgame.fi (Lainema, 2003), is a business-simulation computer game that provides an experience of managing a business. During the game play, the participants (in teams of three or four) manage their own manufacturing company, and they are able to follow their company’s operations and material flows in real time, thus being provided with a dynamic and transparent view of cause–effects in business organisation. Simulation participants are immersed in a realistic business environment where they buy materials,

Computer-Simulation Game Training 7 produce goods and compete with other teams. They are challenged by difficult decisions such as which market to enter, at what prices to buy and sell or how many units to produce. Meanwhile, they have to deal with cash-flow problems, supply-chain bottlenecks and competition from other players. The game operator can use an interface to manipulate the game-clock speed in order to adapt it to the participants’ gradually developing decisionmaking abilities; usually the clock speed is slower at the beginning of the game, whereas it runs faster towards the end of the gaming session. In addition, the game operator can create additional “simulated” companies so that the participants can observe and interact with the supply, and the demand and different business concepts. In summary, RealGame is a continuously processed dynamical system, which involves many activities that occur in everyday business situations. RealGame is not planned for directly teaching leadership skills, but when applied in teamwork, it provides a rich platform for exercising different aspects of leadership in challenging face-to-face and virtual small group situations. (For more studies on RealGame, see Lainema & Lainema, 2007; Lainema & Nurmi, 2006; and Siewiorek, Saarinen, Lainema & Lehtinen, 2012).

Figure 1. The simulation game interface. Description of the design Data were gathered during RealGame gaming sessions at a Finnish university in February 2010. A group of students (n = 26; 10 females and 16 males, aged between 22 and 25 years) participated in the study. Because the participants of the study were partly international exchange students, the language of the gaming session was English. None of the participants, except the selected leaders, had experience in playing the simulation game before the training

Computer-Simulation Game Training 8 sessions. Participation was voluntary and the gaming sessions were not a part of students study program. The participants were selected randomly; an email was sent to the students at two Finnish universities with the information about the gaming session, and they were asked to participate in the session. The number of participants was slightly lower than the optimal number of players in the RealGame environment. In the middle of the term students had timetable problems to participate in an extracurricular activity that took two whole days. Before the gaming sessions, the team leaders were selected based on their pretest answers to the MLQ (Bass & Avolio, 2000). Their answers were analysed using MLQ and the Multifactor Leadership Questionnaire Feedback Report (Bass & Avolio, 2005). The MLQ consists of three subscales: transformational, transactional and passive/avoidance leadership styles. Team leaders were selected so that half of them scored high in transformational and half in transactional subscales of the MLQ relative to the answers of all participants. A training session for eight selected leaders was organised 2 days before the gaming sessions. During the training, the leaders were taught to operate the software and were taught the rules of the simulation game. As a result of the training, they became experts in operating the simulation game, and we expected that this knowledge would add to their authority as team leaders. The leaders’ goal was to inform their team about the simulation game and lead the team during the gaming sessions. The 26 participants were divided into smaller teams, each comprising of three or four students. As a result, there were eight teams (eight companies), which formed a materials value chain of subcontractors and producers. Some teams were subcontractor companies, which were manufacturing Processor units and Electronics. Both products were needed in producing BioCounters (high-tech laboratory equipment). The subcontractor companies were selling their products to the BioCounter manufacturers. Figure 1 presents the example of the RealGame BioCounter manufacturer interface that participants saw when managing their game company. The internal clock of the simulation runs in 1-hour batches which length is set by the simulation game operator (1 simulation hour may take, for example, from 40 to 10 seconds, depending on the participants’ skills). The participants are not tied to making decisions at specified points of time but they can make decisions whenever they choose to. The participants see the internal and external business processes evolve, for example, hour by hour. Lainema (2004, p 42) describes an example of what the gaming tasks might include (the times are simulation internal clock times—imagine that one simulation game hour takes 20 real world seconds): 8 AM: The participants notice that they are short of product BioCounter. There are three unfilled orders with the amount of 150 BioCounters and the inventory includes only 13 units. The participants change the final assembly production cell to produce BioCounters instead of the BioCounter DLX model. At the same time they also note that one of the production cells in the preceding production phase has run out of raw material Electronics. They order 10 000 units of Electronics from a supplier who promises to deliver the products within 2 days. 10 AM: The company runs out of cash. The participants contact the bank and receive a loan of 2 000 000 euros, with interest of 4 % pa, term being 12 months. The cash shows now 525 000 euros. Noon: Because of the previous incident, the participants decide to check their Accounts payable and receiv- able. They note that incoming cash flow will cover the outgoing expenses until the end of next week. 2 PM: The participants run a market report of their company’s market share within each market area. They note that they are losing their share in Europe and decide to invest in advertising in that area. A marketing campaign of 1 000 000 euros is started. They also note that this expense must be paid after 2 weeks.

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The participants also check their market prices compared with those of their competitors. They note that they can increase the price of BioCounter in Europe but the other market areas remain unchanged. 5 PM: Some customers in North America inform that BioCounter DLX deliveries have arrived some 1–3 days late. The participants change the auto delivery method from Ship to Air, which will increase the delivery cost per unit by 55 euros but the deliveries should arrive 7–8 days faster. They also modify the promised delivery time in their North American offers from 10 days to 5 days. This, they hope, will also increase demand for their products. To compensate for the increased delivery costs the price of all products for North America is increased by 3%. 6 PM: The participants run the real-time income statement and note that their Profit-% has increased by 1.2 percentage units compared with the profit 1 week ago. Also some other key figures (like ROI, inventory turnover, and debt–equity ratio) have got higher. In order to present the challenges of steering a modern organisation with an international supply chain and time delays along the chain, the team members were dispersed geographically during the gaming sessions. Figure 2 illustrates the gaming session design. Some teams consisted of two sites; one team member (a satellite member) was separated from her or his team members and was located in another IT classroom, and all satellite members were located in the same IT classroom. Because of practical difficulties two of the teams did not have a satellite member. These two sites (team members and a satellite) could see exactly the same business decisionmaking computer interface and both of them could steer their company at the same time (using mouse and keyboard—although they needed to agree whose turn it was to act as a decision implementer at any point in time). Both sites of each company had a computer to use and a headset for communicating online. Participants were using Skype (Skype Communications SARL, 23-29 Rives de Clausen, L-2165 Luxembourg, www.skype.com/en/; a software applica- tion that allows users to make telephone calls or chat online over the Internet) to communicate with each other. Students participated in two 7-hour gaming sessions that were organised over 2 successive days. All the parties in Figure 2 were connected with each other over the computer network, using Skype. Teams 1 to 3: • Produced Processors and Electronics and were selling these as profitably as possible to Teams4–8 • Teams1 and 2 had a satellite member, and they were expected to guide him or her via Skype to negotiate with Teams 4–8 to get the best terms possible when selling Processors and Electronics to these teams. Teams 4 to 8: • Were supposed to order Processors and Electronics with the best terms possible from Teams 1 to 3 • Could also negotiate good terms with the satellites of Teams 1 and 2 • Teams 5–8 had a satellite member, and they were expected to guide him or her via Skype to negotiate with Teams 1–3 to get the best terms possible when buying Processors and Electronics.

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Figure 2. The graphical representation of the users design interface. Data collection Data were gathered in the form of pre- and posttest questionnaires that included scale questions (see the MLQ, by Bass & Avolio, 2000) and open-ended questions referring to leadership (see Appendix A for the detailed questions). For the purpose of this study, the leaders’ and participants’ responses to pre- and posttest questionnaires were analysed, and quantitative and qualitative research methods were implemented. The MLQ was utilised to measure transformational and transactional leadership styles. The MLQ has two forms: a leader form and a rater form. The leader form was designed to be completed by an individual to measure self-perceived leadership styles. The rater form was developed to be completed by individuals who are asked to measure the perception of the leadership styles of a designated leader. For detailed information on MLQ, its scoring, assessment scales and example items, see http://www.mindgarden.com/products/mlq.htm The data were collected using Webropol, a web-based survey tool (for more information, see http://www.webropol.com). The link to the pretest questionnaire was sent to all participants via email a few days before the gaming sessions. In our study, we preselected leaders of the teams using a pretest (MLQ questionnaire).

Computer-Simulation Game Training 11 Our goal was to choose, on the basis of the pretest, the participants who showed different leadership profiles. After analysing the pretest answers using the Multifactor Leadership Questionnaire Feedback Report (Bass & Avolio, 2005), eight participants were chosen whose scores were high in transformational (four participants) and transactional (four participants) leadership styles. They were assigned the roles of leaders during the gaming sessions. The training session on how to operate the game software was organised for the selected leaders 2 days before the gaming session. Due to two trained leaders being unable to come to the gaming session, two additional leaders were selected just before the gaming session. These replacing leaders had similar profiles than the originally selected leaders but got only shorter training before the beginning of the game. Team members were assigned randomly into the different teams. The link to the posttest questionnaire was sent to all participants via email after the second gaming session. There were two versions of the posttest: one for the leaders (selfassessment) and one for the rest of the participants in order to assess their leaders (see Appendix A2 and A3 for the detailed questions). Analysis Quantitative analysis Analyses were done at two levels: individual and team. At the individual level, differences between team leaders and team members (satellite team members and ordinary team members) were analysed using the Mann–Whitney U-test for two-group comparisons and the Kruskal–Wallis H-test for three-group comparisons. Development from pretest to posttest within groups was analysed using one-way repeated measures ANOVA. U and Z statistics from the Mann–Whitney and the matched-pairs test were complemented with estimates of Cohen’s d. All analyses were performed by using the original subscales of the MLQ questionnaire, because the relatively small sample size prohibited factor-analytic methods (MacCallum, Widaman, Zhang & Hong, 1999). However, estimation of reliability indicated that, despite the small sample size, measures had adequate statistical properties for exploratory research (Hair, Black, Babin & Anderson, 2009), with Cronbach’s alpha values ranging from 0.68 for transformational leadership, to 0.66 for transactional leadership and 0.73 for passive/avoidance leadership. The alpha values of transformational and transactional are slightly lower than 0.7, which is normally considered as the limit of good reliability. At the group level, differences in team performance were estimated with the Kruskal–Wallis H test, Mann–Whitney U-test and Cohen’s d. Correlations between team performance variables and leadership styles were computed using the Pearson correlation coefficient ρ. Qualitative analysis Qualitative data consist of leaders’ and participants’ answers to the posttest. The posttest included the open-ended questions regarding leadership in the teams (see Appendix A2 and A3 for the detailed questions). Analysis of the qualitative data had two phases. We first coded all expressions of the participants’ answers that referred to leadership and division of roles in a team; this coding was based on the leadership style coding scheme (see Appendix B). We then determined the dominating leadership style of each team based on the coding of participants’ answers; these leadership styles were elucidated in teams according to team members’ opinions. Two independent raters coded the qualitative data, and they agreed in all cases but one. In this case, one rater coded the team as heroic leadership and the other as shared leadership. After discussion between the raters, the team was coded into the shared-leadership category. The intercoder reliability for the qualitative data (deciding on the type of leadership in each of the eight teams) had a Cohen’s kappa value of 0.75 (SE = 0.17; 95% CI = 0.45, 1.00).

Computer-Simulation Game Training 12 Results Effects of the computer-simulation gaming session on participants’ opinions on leadership styles are explored on two levels: individual and team. On the individual level, we address the first research question: is there any difference in participants’ opinions on leadership styles before and after participating in a collaborative computer-simulation gaming session? On the team level, we address the second research question: how does leadership style correlate with team performance? Results for both levels are specified in turn. Team leaders’ and members’ leadership style opinions This section starts with describing between-group differences in leadership style opinions of team leaders and team members before and after gaming session; we then report within-group differences that resulted from participating in the computer-simulation gaming session. First, Table 1 presents mean scores and standard deviations of leadership opinions for team leaders and team members.

Table 1. Mean scores and standard deviatons by group and measurement time Leadership preferences of satellite team members and ordinary team members did not differ. Because there were no statistically significant differences and because the team function of satellite members and ordinary members was identical, the two groups were combined into one group. Consequently, analyses were based on two groups: team leaders and team members. The pretest estimates indicate that, between groups, there were no statistically significant differences for transformational, transactional, and passive/avoidance leadership before the computer- simulation gaming session. The results also show that there was very little variance in the leadership styles of the participants. Even though the eight participants who scored highest in transformational or transactional leadership style were selected to be leaders, there were no statistically significant differences between leaders’ and members’ leadership style opinions. After the gaming session, however, significant differences between team leaders and team members emerged for transactional leadership (U = 28.50, p < 0.05, Cohen’s d = 0.87) and passive/avoidance leadership (U = 27.00, p < 0.05, Cohen’s d = 0.89). These posttest findings indicate that the team leaders’ self-rating was significantly higher for the transactional leadership category and significantly lower in the passive/avoidance leadership category compared with the team members’ peer ratings. Correlation analysis of all participants showed that in the pretest, when participants expressed their general leadership opinions, transformational and transactional leadership styles were clearly separate dimensions, and there was no correlation between the subscales (r = 0.07). In the posttest, however, when team members evaluated the behaviour of their team leader during the simulation game, there was a moderate correlation (r=0.49, p