Academia.eduAcademia.edu

Outline

Title
Abstract
Figures
Introduction
Hypotheses
Methodology
Subjects
Hypothesis Testing
Discussion of Experiment 1 Findings
Results
Discussion
Implications
Limitations
Conclusion
References
All Topics
Computer Science

The Effects of Video Gaming on Work Group Performance

Profile image of Dr. Douglas L. DeanDr. Douglas L. Dean

2016

Abstract

Organizational tasks are complex and time-sensitive, requiring group effort to achieve goals under pressure. To improve group performance, organizations often invest in a services designed to strengthen teams (e.g., ropes courses). However, such activities are time-and resource-expensive and have demonstrated mixed results. To proffer a more practical (shorter and less expensive) alternative, we explore the potential of video gaming as a team building activity. To this end, we employed a multi-experiment study in which we administered competitive and cooperative video games to newly formed work teams. To theoretically explain the effects of video gaming on group performance, we adapt the theoretical construct to flow to the group level. Our results reveal that all forms of video gaming had a positive effect on group performance. However, competitive versus cooperative gaming have different effects on the sub-constructs of group flow. Therefore, optimal results are obtained with cooperative-competitive video games.

Figures (8)
Figure 1: Overview of Existing Group Performance Research
Figure 1: Overview of Existing Group Performance Research
Note: ATG-T: Individual Attractions to the Group-Task, ATG-S: Individual Attractions to the Group- Social, GI-T: Group Integration-Task, GI-S: Group Integration-Social.
Note: ATG-T: Individual Attractions to the Group-Task, ATG-S: Individual Attractions to the Group- Social, GI-T: Group Integration-Task, GI-S: Group Integration-Social.
In this study, we seek to extend Matheson et al.’s (1997) findings and answer the call of Liu et al (2013) by exploring the effects of competition, cooperation, and winning. Although we are not certain that Matheson et al.’s sports context will generalize to the work group context, we want to explore whether there are similar effects of cooperation, competition, and winning. In particular, we expect that cooperation will improve performance because it should improve the group’s ability to communicate efficiently and effectively. In addition, competition should also improve performance because it unites the Liu et al. (2013) called for research into the effects of cooperative versus competitive video gaming. In the literature, the closest existing research is in the context of sports teams (Matheson et al. 1997). In their study, Matheson et al. (1997) explored the effects on group cohesion of interactive versus coactive sports groups who either won or lost. An interactive sports team is one where the group’s performance is based on the interactions between players; for example, volleyball or rugby. A coactive sports team is one where the group’s performance is based on the individual and non-interactive performances of each team member; for example, swimming or gymnastics. In their study, they found that winning and losing had differing effects on the two different types of groups. For coactive groups, winning led to less cohesion while losing led to more cohesion. The opposite was found for interactive groups where winning led to higher cohesion. Table 1 summarizes these findings in terms of group cohesion. In our study, we compare the coactive group to the individual treatment and the interactive group to the cooperative treatments.
In this study, we seek to extend Matheson et al.’s (1997) findings and answer the call of Liu et al (2013) by exploring the effects of competition, cooperation, and winning. Although we are not certain that Matheson et al.’s sports context will generalize to the work group context, we want to explore whether there are similar effects of cooperation, competition, and winning. In particular, we expect that cooperation will improve performance because it should improve the group’s ability to communicate efficiently and effectively. In addition, competition should also improve performance because it unites the Liu et al. (2013) called for research into the effects of cooperative versus competitive video gaming. In the literature, the closest existing research is in the context of sports teams (Matheson et al. 1997). In their study, Matheson et al. (1997) explored the effects on group cohesion of interactive versus coactive sports groups who either won or lost. An interactive sports team is one where the group’s performance is based on the interactions between players; for example, volleyball or rugby. A coactive sports team is one where the group’s performance is based on the individual and non-interactive performances of each team member; for example, swimming or gymnastics. In their study, they found that winning and losing had differing effects on the two different types of groups. For coactive groups, winning led to less cohesion while losing led to more cohesion. The opposite was found for interactive groups where winning led to higher cohesion. Table 1 summarizes these findings in terms of group cohesion. In our study, we compare the coactive group to the individual treatment and the interactive group to the cooperative treatments.
Figure 3 visualizes the performance increase (measured in points earned) of the posttest over the pretest. The results indicate an approximately 20% performance improvement for the collaborative video gaming treatment and almost no effect of the goal training treatment. A repeated measures ANOVA analysis shows a clear effect of treatment (F = 5.282, p = 0.007) with no difference between group sizes of three and four and no difference between the two different video games. A priori power analysis conducted with G*Power resulted in power of 0.95 for our sample size, which is well above the 0.80 threshold recommended by Cohen (1988). However, to test the hypotheses of our theory, we examine the group flow, group cohesion, and goal commitment scales next.
Figure 3 visualizes the performance increase (measured in points earned) of the posttest over the pretest. The results indicate an approximately 20% performance improvement for the collaborative video gaming treatment and almost no effect of the goal training treatment. A repeated measures ANOVA analysis shows a clear effect of treatment (F = 5.282, p = 0.007) with no difference between group sizes of three and four and no difference between the two different video games. A priori power analysis conducted with G*Power resulted in power of 0.95 for our sample size, which is well above the 0.80 threshold recommended by Cohen (1988). However, to test the hypotheses of our theory, we examine the group flow, group cohesion, and goal commitment scales next.
in our group flow theory of three treatments: control/none, goal setting, and collaborative video gaming (CVG). Most of our hypotheses were supported. Group cohesion had a significant positive effect on group performance (8 = 0.45, p < 0.05), thus supporting H1. Group flow also had a significant positive effect on group performance (6 = 0.63, p < 0.05) supporting H4. However, goal commitment did not have a significant effect in our model after accounting for group flow and cohesion. Nevertheless, a test of goa commitment before including the other exogenous variables demonstrated a significant positive effect (6 = 0.15, p < 0.05). This indicates that the effect of goal commitment is better captured through the separate effects of flow and cohesion, which are thus the more potent antecedents of performance and should therefore receive greater attention when developing teams in organizations. Additionally, CVG appears to be a valid treatment for improving both group flow (6 = 0.30, p < 0.001) and group cohesion (6 = 0.29, p < 0.001). Lastly, interdependence produced some unexpected findings. While it did not interact with group cohesion to a significant level, we found that interdependence actually reduced the effect of group flow on task performance (6 = 0.61, p < 0.05) — counter to our hypothesis. Another interpretation of this finding is that flow and interdependence are tradeoffs which do not coexist well, yet both enhance task performance (as indicated by a post-hoc test, the direct effect of interdependence on performance: B = 0.18, p < 0.01). Perhaps this dampening effect indicates the extra effort and time for required interdependent tasks, which cannot be performed in parallel.
in our group flow theory of three treatments: control/none, goal setting, and collaborative video gaming (CVG). Most of our hypotheses were supported. Group cohesion had a significant positive effect on group performance (8 = 0.45, p < 0.05), thus supporting H1. Group flow also had a significant positive effect on group performance (6 = 0.63, p < 0.05) supporting H4. However, goal commitment did not have a significant effect in our model after accounting for group flow and cohesion. Nevertheless, a test of goa commitment before including the other exogenous variables demonstrated a significant positive effect (6 = 0.15, p < 0.05). This indicates that the effect of goal commitment is better captured through the separate effects of flow and cohesion, which are thus the more potent antecedents of performance and should therefore receive greater attention when developing teams in organizations. Additionally, CVG appears to be a valid treatment for improving both group flow (6 = 0.30, p < 0.001) and group cohesion (6 = 0.29, p < 0.001). Lastly, interdependence produced some unexpected findings. While it did not interact with group cohesion to a significant level, we found that interdependence actually reduced the effect of group flow on task performance (6 = 0.61, p < 0.05) — counter to our hypothesis. Another interpretation of this finding is that flow and interdependence are tradeoffs which do not coexist well, yet both enhance task performance (as indicated by a post-hoc test, the direct effect of interdependence on performance: B = 0.18, p < 0.01). Perhaps this dampening effect indicates the extra effort and time for required interdependent tasks, which cannot be performed in parallel.
Those in individual treatments were asked to play either Rock Band or Halo Reach for 40 minutes of solo play. They were instructed not to p ay with eac h other, help each other, nor record or com pare score or points. Those in competitive treatments participated in game modes that were competitive between contact and would not play with the ot promote flow through application of ski the members of their own group of 4. They would her group at score (Rock Band) or lowest deaths/highest kills (Halo) in any given round would receive a large candy bar. The administrators of the experiment encouraged competitiveness within the group in order to 1 against ap all. The two members of the grou propriate challenge (Csikszentmiha keep track of who won and lost, but woul D with t yi 1990). d have no he highest Those in cooperative treatments participated in game modes that required players to collaborate and work together within their own group to be as successful as possible. For Rock Band, they were told to play together and see how high they could get their group scores. For Halo Reach, they were instructed to get as far through the campaign as they possibly could by completing cooperative missions. Those in cooperative-competitive treatments were directly competing as a group against another group for candy bars. For Rock Band, the group with the highest score for any given song at the end of the time were awarded large candy bars. For Halo Reach, groups would play as many rounds as they could of capture the flag in the permitted time. Groups would record their wins and the group with the most wins would be awarded large candy bars. Upon completing the first task, each group was randomly assigned a treatment in a 2 x 2 factorial design including a control group (see Table 3). Those in the control group were asked to spend 40 minutes working independently on homework and were instructed to not speak to each other.
Those in individual treatments were asked to play either Rock Band or Halo Reach for 40 minutes of solo play. They were instructed not to p ay with eac h other, help each other, nor record or com pare score or points. Those in competitive treatments participated in game modes that were competitive between contact and would not play with the ot promote flow through application of ski the members of their own group of 4. They would her group at score (Rock Band) or lowest deaths/highest kills (Halo) in any given round would receive a large candy bar. The administrators of the experiment encouraged competitiveness within the group in order to 1 against ap all. The two members of the grou propriate challenge (Csikszentmiha keep track of who won and lost, but woul D with t yi 1990). d have no he highest Those in cooperative treatments participated in game modes that required players to collaborate and work together within their own group to be as successful as possible. For Rock Band, they were told to play together and see how high they could get their group scores. For Halo Reach, they were instructed to get as far through the campaign as they possibly could by completing cooperative missions. Those in cooperative-competitive treatments were directly competing as a group against another group for candy bars. For Rock Band, the group with the highest score for any given song at the end of the time were awarded large candy bars. For Halo Reach, groups would play as many rounds as they could of capture the flag in the permitted time. Groups would record their wins and the group with the most wins would be awarded large candy bars. Upon completing the first task, each group was randomly assigned a treatment in a 2 x 2 factorial design including a control group (see Table 3). Those in the control group were asked to spend 40 minutes working independently on homework and were instructed to not speak to each other.
Each row summarizes ANOVA performed at the group-level including the covariates: group size, video game performance (where they ranked compared to competitors), and the height of their first tower. Based on this analysis, there appears to be a clear effect of video gaming on group performance. In addition, adding a competitive aspect to the gaming also improves performance at least marginally. However, it should be noted that when groups competed against each other in the video gaming treatment, their subsequent performance on the Task 2 was affected by whether they won or lost during the competition (6 = 0.173, p = 0.043). In particular, those who win during video gaming tend perform better on later tasks. Competitive-cooperative gaming produced the largest increase, followed by competitive video gaming (without cooperation), followed by cooperative gaming (without competition), which was followed by individual video gaming. Table 4 provides an alternative summary of the results where dummy codes (0 or 1) are used to mark whether each treatment included video gaming, competition, or cooperation. The percent scores represent the groups improvement from Task 1 to Task 2. For example, the first treatment represents the mean of the control group who played no video games (48.87%) versus all other groups which included some form of video game playing (80.95%). The second treatment represents the mean improvement of all treatments that didn’t include any competition (e.g. individual video gaming and cooperative-only video gaming: 70.56%) versus those that did (competitive-only video gaming and cooperative-competitive video gaming: 90.99%).
Each row summarizes ANOVA performed at the group-level including the covariates: group size, video game performance (where they ranked compared to competitors), and the height of their first tower. Based on this analysis, there appears to be a clear effect of video gaming on group performance. In addition, adding a competitive aspect to the gaming also improves performance at least marginally. However, it should be noted that when groups competed against each other in the video gaming treatment, their subsequent performance on the Task 2 was affected by whether they won or lost during the competition (6 = 0.173, p = 0.043). In particular, those who win during video gaming tend perform better on later tasks. Competitive-cooperative gaming produced the largest increase, followed by competitive video gaming (without cooperation), followed by cooperative gaming (without competition), which was followed by individual video gaming. Table 4 provides an alternative summary of the results where dummy codes (0 or 1) are used to mark whether each treatment included video gaming, competition, or cooperation. The percent scores represent the groups improvement from Task 1 to Task 2. For example, the first treatment represents the mean of the control group who played no video games (48.87%) versus all other groups which included some form of video game playing (80.95%). The second treatment represents the mean improvement of all treatments that didn’t include any competition (e.g. individual video gaming and cooperative-only video gaming: 70.56%) versus those that did (competitive-only video gaming and cooperative-competitive video gaming: 90.99%).
Group cohesion increased group performance just as in Experiment 1. However, when looking at the group flow sub-constructs (rather than the entire 2™4 order factor), the effect of group flow on performance appears to be primarily driven by group communication and time dissociation. When implementing interdependence as a moderator, heightened enjoyment also has an effect. In other words, heightened enjoyment only improves group performance when the group members depend on each other for their own performance.
Group cohesion increased group performance just as in Experiment 1. However, when looking at the group flow sub-constructs (rather than the entire 2™4 order factor), the effect of group flow on performance appears to be primarily driven by group communication and time dissociation. When implementing interdependence as a moderator, heightened enjoyment also has an effect. In other words, heightened enjoyment only improves group performance when the group members depend on each other for their own performance.

Related papers

It's a team game : exploring factors that influence team experience
Eleanor Martin

2015

Many multiplayer games feature teams, and whether they are pitted against each other or against the game itself it seems likely that the way these teams bond will affect the players&#39; experience. What are the factors that influence the experience of being a team member in a game? To what extent can the game designer manipulate the cohesion of the teams by changing the game design? How does the satisfaction of the player with their team relate to their feeling of cohesion? How does cohesion differ between tabletop and online games? These issues become particularly important where the group dynamic is central to the desired outcome of the game e.g. educational games aiming to place the players in specific social situations. Four studies were conducted on four similar simulation games (two tabletop, two online) used for teaching in International Development Studies. These games explore farming in sub-Saharan Africa and require 12-30 players to play in small groups. The group dynamic...

View PDFchevron_right
Games teams play: A method for investigating team coordination and performance
Michael Brannick

Behavior Research Methods, 1992

Teams are playing an increasingly important role in the workplace. However, reviews of the team performance literature have suggested that there are serious deficiencies in our understanding of team processes and performance (e.g., Dyer, 1984). These difficulties may be attributable, in part, to the lack of laboratory methodologies to investigate team performance. This paper describes the use of low-fidelity simulations as a potentially useful paradigm for researching team coordination and performance. This paradigm is advantageous in that it offers relatively high levels of experimental control and task representation at a low cost.

View PDFchevron_right
The Good, the Bad and the Neutral: An Analysis of Team-Gaming Activity
Nikolaos Avouris

This paper describes a preliminary study where a multiplayer location-based game's logfiles were used for the assessment of the overall practice of teams. We explore the use of activity metrics previously introduced and applied to CSCL settings. We argue that these metrics, if adapted in a meaningful way, will provide insight of the progress of a location-based gaming activity and its quality regarding the score. Moreover, this can be achieved in an automated way. A small set of activity metrics, related to game characteristics and player activity, is applied to a set of gaming activities. The results are analyzed regarding team performance and score. The paper proposes a way to analyze group activity in the context of location-based games while taking into account the characteristics of successful collaborative activities. Future work is proposed towards the development of automated metrics for the analysis of location-based gaming activities with emphasis on collaboration and group dynamics.

View PDFchevron_right
Exploring the Influence of Group characteristics on Interactions during Collaborative Gaming
Philip Bonanno

IADIS International Conference: e-Learning held in Lisbon, Portugal, 2007

Collaborative gaming is evolving into the latest pedagogically stimulating scenario motivating research from different perspectives. Group-based gaming is analysed through a methodology that integrates the role of various variables in mediating interactions. An interactions-oriented pedagogical model categorises task and person-oriented interactions (T&POIs) along the domain, technology and community dimensions, and across three pedagogical levels. Using this model, P&TOIs, directionality of interactions, ...

View PDFchevron_right
Individual Achievement versus Team Performance: An Empirical Study with Business Games
Antonio Carlos Aidar Sauaia

Undergraduate students (160) were ranked according to their performance in three objective tests (two multiple-choice quizzes and one objective exam) and then grouped in teams of 5 to 6. During seven weeks the teams managed companies in a medium complexity business game (MMG). One would expect that better performance in the objective tests (individual knowledge acquisition) would produce better performance in the business game (knowledge deployment in teamwork). The results however did not indicate any consistent and significant correlation between level of individual knowledge and company performance. This shows that theoretical knowledge is not sufficient to explain teamwork successful performance.

View PDFchevron_right
Learning teamwork through a computer game: for the sake of performance or collaborative learning?
Anna-Maija Lämsä

Educational Technology Research and Development

Our study examined using a computer-based learning game as a tool to facilitate teaching and learning teamwork skills. The game was applied to an undergraduate level human resource management course at a business school in Finland. We focused on students’ experiences and key learning outcomes of collaborative learning of teamwork skills through the game, and our analysis highlighted two key features of learning outcomes. First, the computer-based learning game promoted students’ self-reflection and evaluation of their individual team roles. Second, although the game taught students the importance of continuous information sharing in teamwork, their evaluation of team outcomes was performance driven; students predominantly took team efficiency as a sign of good teamwork. This case revealed the benefits and challenges of using computer-based learning games as a pedagogical tool. We identified what is required from lecturers and students for the game to be successful, and how team valu...

View PDFchevron_right
Variations in psychological factors and experience-dependent changes in team-based video game performance
Lisa Castaneda

Intelligence, 2020

Success in many types of activities relies upon the performance of skilled individuals. Across formal and more informal environments, the amount of experience an individual has accumulated has been observed to predict skilled performance. Psychological traits have also been found to relate to the development of skilled performance. Questions remain regarding what factors influence the development of skilled performance within teambased activities. Factors including variations in psychological traits and how teammates are selected, in addition to the amount of accumulated experience, may differ in how strongly they influence changes in the skilled performance of individuals. In the present study, the degree to which psychological factors interacted with accumulated experience with regard to skilled performance was examined within a team-based activity. Personality, social, and cognitive measures were collected from players of a team-based online video game. Subsequently, their experience and performance playing video game matches where their teammates were selected by the players versus randomly assigned were assessed across a three-month period. Longitudinal models revealed that performance improved with the number of matches played, with the rate of improvement affected by how teammates were selected and individual differences in specific psychological measures, number processing ability, fluid intelligence, theory of mind ability, and neuroticism. These psychological factors and the method by which teammates were selected moderated the degree to which individuals improved their performance with experience. In line with previous research, these findings indicated that psychological factors, in addition to experience, contributed to the development of skilled performance within a team-based activity.

View PDFchevron_right
Cooperation, coordination, and trust in virtual teams: insights from virtual games
M. Korsgaard

… : Convergence of the …, 2010

View PDFchevron_right
Stealth Assessment of Teams in a Digital Game Environment
Ivo Wenzler

Lecture Notes in Computer Science, 2014

There is not much research on team collaboration in digital entertainment games, nor is there much evidence for the efficacy of game-based team training or the validity of game-based team assessment. This is a shortcoming because of an increasing pervasiveness of serious games in organizational life, e.g. for operational training, management and leadership. Is it possible to establish marked relationships between psychometric constructs that measure 'team composition and performance' and 'analytics' that unobtrusively measure gameplay performance? If so, what are the implications for gamebased team research and assessment? The authors conducted explorative, quasi-experimental (field) experiments with the multiplayer serious game TeamUp. One field experiment was conducted with 150 police officers as part of task-specific two-day team training. Research data were gathered through pre-game and post-game questionnaires on team constructs such as 'psychological safety' and 'team cohesion'. A large quantity of in-game data was logged to construct indicators like 'time needed to complete the task', 'speak time' and 'avoidable mistakes' to measure team performance. The conclusion of the analysis is that 'team cohesion' and 'psychological safety' correlate moderately and significantly with in-game performance indicators. Teams with an unequal individual game performance speak the most, while teams with an equally low or equally high individual performance spend significantly less time speaking. The indicative findings support the need to further develop validated analytics and game-based environments for team research and assessment.

View PDFchevron_right
Distributed Team Performance in a Computer Game: The Implications of Task Difficulty
James Bliss

PsycEXTRA Dataset, 2000

The use of computer game based architectures may help provide a safe, controlled environment in which geographically dispersed military units can develop leadership skills while rehearsing a specific task such as search and rescue. The purpose of this study was to investigate the relationships among task difficulty, team task performance, personality and computer game experience using a modified version of the popular video game, Half Life 2 ™. Twenty dyads searched a virtual environment to find a target avatar while disregarding distractor avatars. Task difficulty was represented by low or high numbers of distracters. Findings showed that manipulating difficulty in this way led to differences in search efficiency, but not overall accuracy or task completion time. Personality and gaming experience did not influence team performance outcomes as expected. This research suggests researchers and trainers must act judiciously when modifying game characteristics, such as task difficulty, to design and implement immersive training programs.

View PDFchevron_right

References (80)

  1. Admiraal, W., Huizenga, J., Akkerman, S., and Dam, G. t. 2011. "The Concept of Flow in Collaborative Game- Based Learning," Computers in Human Behavior (27:3), pp. 1185-1194.
  2. Agarwal, R., and Karahanna, E. 2000. "Time Flies When You're Having Fun: Cognitive Absorption and Beliefs About Information Technology Usage," MIS Quarterly (24:4), pp. 665-694.
  3. Ahronson, A., and Cameron, J. E. 2007. "The Nature and Consequences of Group Cohesion in a Military Sample," Military Psychology (19:1), p. 9.
  4. Ansoff, H. I. 1970. Corporate Strategy: An Analytic Approach to Business Policy for Growth and Expansion. Penguin Books.
  5. Aubé, C., Brunelle, E., and Rousseau, V. 2013. "Flow Experience and Team Performance: The Role of Team Goal Commitment and Information Exchange," Motivation and Emotion), pp. 1-11.
  6. Bakker, A. B., Oerlemans, W., Demerouti, E., Slot, B. B., and Ali, D. K. 2011. "Flow and Performance: A Study among Talented Dutch Soccer Players," Psychology of Sport and Exercise (12:4), pp. 442-450.
  7. Bandura, A. 1991. "Social Cognitive Theory of Self-Regulation," Organizational Behavior and Human Decision Processes (50:2), pp. 248-287.
  8. Beal, D. J., Cohen, R. R., Burke, M. J., and McLendon, C. L. 2003. "Cohesion and Performance in Groups: A Meta- Analytic Clarification of Construct Relations," Journal of Applied Psychology (88:6), pp. 989-1004.
  9. Bower, B. 1995. "Return of the Group," Science News (148:21), p. 328.
  10. Boyle, I. T. 2003. The Impact of Adventure-Based Training on Team Cohesion and Psychological Skills Development in Elite Sporting Teams. Universal-Publishers.
  11. Bruner, M. W., and Spink, K. S. 2010. "Evaluating a Team Building Intervention in a Youth Exercise Setting," Group Dynamics: Theory, Research, and Practice (14:4), p. 304.
  12. Carless, S. A., and De Paola, C. 2000. "The Measurement of Cohesion in Work Teams," Small Group Research (31:1), pp. 71-88.
  13. Carron, A. V. 1982. "Cohesiveness in Sport Groups: Interpretations and Considerations," Journal of Sport Psychology (4:2).
  14. Carron, A. V., Colman, M. M., Wheeler, J., and Stevens, D. 2002. "Cohesion and Performance in Sport: A Meta Analysis," Journal of Sport & Exercise Psychology (24:2).
  15. Carron, A. V., Widmeyer, W. N., and Brawley, L. R. 1985. "The Development of an Instrument to Assess Cohesion in Sport Teams: The Group Environment Questionnaire," Journal of sport psychology (7:3).
  16. Cartwright, D. 1968. "The Nature of Group Cohesiveness," Group dynamics: Research and theory (91), p. 109.
  17. Castaño, N., Watts, T., and Tekleab, A. G. 2013. "A Reexamination of the Cohesion-Performance Relationship Meta-Analyses: A Comprehensive Approach,").
  18. Chen, J. 2007. "Flow in Games (and Everything Else)," Communications of the ACM (50:4), pp. 31-34.
  19. Chin, W. W., Marcolin, B. L., and Newsted, P. R. 2003. "A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo Simulation Study and an Electronic-Mail Emotion/Adoption Study," Information Systems Research (14:2), pp. 189-217.
  20. Choi, D., and Kim, J. 2004. "Why People Continue to Play Online Games: In Search of Critical Design Factors to Increase Customer Loyalty to Online Contents," CyberPsychology & Behavior (7:1), pp. 11-24.
  21. Cohen, J. 1988. Statistical Power Analysis for the Behavioral Sciences. Psychology Press.
  22. Costello, J. F. 2004. "Developing Team Cohesion: A Quasi-Field Experiment," DTIC Document.
  23. Csikszentmihalyi, M. 1990. Flow: The Psychology of Optimal Experience. New York: Harper and Row.
  24. DeChurch, L. A., and Mesmer-Magnus, J. R. 2010. "The Cognitive Underpinnings of Effective Teamwork: A Meta- Analysis," Journal of Applied Psychology (95:1), p. 32.
  25. Dennis, A. R., Fuller, R. M., and Valacich, J. S. 2008. "Media, Tasks, and Communication Processes: A Theory of Media Synchronicity," MIS quarterly (32:3), pp. 575-600.
  26. Dervitsiotis, K. N. 2012. "An Innovation-Based Approach for Coping with Increasing Complexity in the Global Economy," Total Quality Management & Business Excellence (23:9-10), pp. 997-1011.
  27. Ensley, M. D., and Pearson, A. W. 2005. "An Exploratory Comparison of the Behavioral Dynamics of Top Management Teams in Family and Nonfamily New Ventures: Cohesion, Conflict, Potency, and Consensus," Entrepreneurship Theory and Practice (29:3), pp. 267-284.
  28. Evans, C. R., and Dion, K. L. 2012. "Group Cohesion and Performance a Meta-Analysis," Small Group Research (43:6), pp. 690-701.
  29. Fang, X. W., Zhang, J. L., and Chan, S. S. 2013. "Development of an Instrument for Studying Flow in Computer Game Play," International Journal of Human-Computer Interaction (29:7), pp. 456-470.
  30. Festinger, L. 1954. "A Theory of Social Comparison Processes," Human Relations (7:2), pp. 117-140.
  31. Festinger, L., Back, K. W., and Schachter, S. 1950. Social Pressures in Informal Groups: A Study of Human Factors in Housing. Stanford University Press.
  32. Forbes, D. P., and Milliken, F. J. 1999. "Cognition and Corporate Governance: Understanding Boards of Directors as Strategic Decision-Making Groups," Academy of Management Review (24:3), pp. 489-505.
  33. Fornell, C., and Bookstein, F. L. 1982. "Two Structural Equation Models: Lisrel and Pls Applied to Consumer Exit- Voice Theory," Journal of Marketing Research (19:4), pp. 440-452.
  34. Gaskin, J., and Berente, N. 2011. "Video Game Design in the Mba Curriculum: An Experiential Learning Approach for Teaching Design Thinking," Communications of the Association for Information Systems (29:1), pp. 103-122.
  35. Gefen, D., and Straub, D. W. 2005. "A Practical Guide to Factorial Validity Using Pls-Graph: Tutorial and Annotated Example," Communications of the AIS (16:5), pp. 91-109.
  36. Gully, S. M., Devine, D. J., and Whitney, D. J. 1995. "A Meta-Analysis of Cohesion and Performance Effects of Level of Analysis and Task Interdependence," Small Group Research (26:4), pp. 497-520.
  37. Hoffman, D. L., and Novak, T. P. 1996. "Marketing in Hypermedia Computer-Mediated Environments: Conceptual Foundations," Journal of Marketing (60:3), pp. 50-68.
  38. Hsu, C. L., and Lu, H. P. 2004. "Why Do People Play on-Line Games? An Extended Tam with Social Influences and Flow Experience," Information & Management (41:7), pp. 853-868.
  39. Huntemann, N. B., and Payne, M. T. 2009. Joystick Soldiers: The Politics of Play in Military Video Games. Routledge.
  40. Jennett, C., Cox, A. L., Cairns, P., Dhoparee, S., Epps, A., Tijs, T., and Walton, A. 2008. "Measuring and Defining the Experience of Immersion in Games," International Journal of Human-Computer Studies (66:9), pp. 641-661.
  41. Johnson, D. W., and Johnson, F. P. 1991. Joining Together: Group Theory and Group Skills. Prentice-Hall, Inc.
  42. Keith, M., Anderson, G., Dean, D. L., and Gaskin, J. E. 2014. "The Effects of Team Flow on Performance: A Video Game Experiment," SIGHCI proceedings).
  43. Klein, H. J., and Mulvey, P. W. 1995. "Two Investigations of the Relationships among Group Goals, Goal Commitment, Cohesion, and Performance," Organizational Behavior and Human Decision Processes (61:1), pp. 44-53.
  44. Klein, H. J., Wesson, M. J., Hollenbeck, J. R., and Alge, B. J. 1999. "Goal Commitment and the Goal-Setting Process: Conceptual Clarification and Empirical Synthesis," Journal of Applied Psychology (84:6), p. 885.
  45. LaFasto, F., and Larson, C. 2001. When Teams Work Best: 6,000 Team Members and Leaders Tell What It Takes to Succeed. Sage.
  46. Lenhart, A., Kahne, J., Middaugh, E., Macgill, A. R., Evans, C., and Vitak, J. 2008. "Teens, Video Games, and Civics: Teens' Gaming Experiences Are Diverse and Include Significant Social Interaction and Civic Engagement," Pew Internet & American Life Project).
  47. Levi, D. 2013. Group Dynamics for Teams. Sage.
  48. Liang, H., Saraf, N., Hu, Q., and Xue, Y. 2007. "Assimilation of Enterprise Systems: The Effect of Institutional Pressures and the Mediating Role of Top Management," MIS Quarterly (31:1), pp. 59-87.
  49. Liu, D., Li, X., and Santhanam, R. 2013. "Digital Games and Beyond: What Happens When Players Compete," Mis Quarterly (37:1), pp. 111-124.
  50. Locke, E. A., and Latham, G. P. 1990. A Theory of Goal Setting & Task Performance. Prentice-Hall, Inc.
  51. Lowry, P., Gaskin, J., Twyman, N., Hammer, B., and Roberts, T. 2013a. "Proposing the Hedonic-Motivation System Adoption Model (Hmsam) to Increase Understanding of Adoption of Hedonically Motivated Systems," Journal of the Association for Information Systems (14:11), pp. 617-671.
  52. Lowry, P. B., Gaskin, J., Twyman, N., Hammer, B., and Roberts, T. 2012. "Taking 'Fun and Games' Seriously: Proposing the Hedonic-Motivation System Adoption Model (Hmsam)," Journal of the association for information systems (14:11), pp. 617-671.
  53. Lowry, P. B., Gaskin, J. E., Twyman, N. W., Hammer, B., and Roberts, T. L. 2013b. "Taking" Fun and Games" Seriously: Proposing the Hedonic-Motivation System Adoption Model (Hmsam)," Journal of the Association for Information Systems (14:11).
  54. Matheson, H., Mathes, S., and Murray, M. 1997. "The Effect of Winning and Losing on Female Interactive and Coactive Team Cohesion," Journal of Sport Behavior (20:3), p. 284.
  55. Mathieu, J. E., Heffner, T. S., Goodwin, G. F., Salas, E., and Cannon-Bowers, J. A. 2000. "The Influence of Shared Mental Models on Team Process and Performance," Journal of Applied Psychology (85:2), pp. 273-283.
  56. Mathieu, J. E., Tannenbaum, S. I., Donsbach, J. S., and Alliger, G. M. 2014. "A Review and Integration of Team Composition Models Moving toward a Dynamic and Temporal Framework," Journal of Management (40:1), pp. 130-160.
  57. Mullen, B., and Copper, C. 1994. "The Relation between Group Cohesiveness and Performance: An Integration," Psychological bulletin (115:2), p. 210.
  58. Nakamura, J., and Csikszentmihalyi, M. 2002. "The Concept of Flow," in Handbook of Positive Psychology, S.J. Lopez and C.R. Synder (eds.). London: Oxford University Press, pp. 89-105.
  59. Park, J., Jung, W., and Yang, J.-E. 2012. "Investigating the Effect of Communication Characteristics on Crew Performance under the Simulated Emergency Condition of Nuclear Power Plants," Reliability Engineering & System Safety (101), pp. 1-13.
  60. Pavlou, P. A., Liang, H. G., and Xue, Y. J. 2007. "Understanding and Mitigating Uncertainty in Online Exchange Relationships: A Principal-Agent Perspective," MIS Quarterly (31:1), pp. 105-136.
  61. Ringle, C. M., Wende, S., and Will, S. 2005. "Smartpls 2.0 (M3) Beta." Hamburg, Germany.
  62. Roberts, K. H., and O'Reilly, C. A. 1976. "Interpersonal, Work Group, and Organizational Communication: A Systemic Approach to Understanding Organizations," DTIC Document.
  63. Roberts, K. H., and Rousseau, D. M. 1989. "Research in Nearly Failure-Free, High-Reliability Organizations: Having the Bubble," Engineering Management, IEEE Transactions on (36:2), pp. 132-139.
  64. Rutkowski, A.-F., Saunders, C., Vogel, D., and Van Genuchten, M. 2007. ""Is It Already 4 Am in Your Time Zone?" Focus Immersion and Temporal Dissociation in Virtual Teams," Small group research (38:1), pp. 98-129.
  65. Salas, E. E., and Fiore, S. M. 2004. Team Cognition: Understanding the Factors That Drive Process and Performance. American Psychological Association.
  66. Senécal, J., Loughead, T. M., and Bloom, G. A. 2008. "A Season-Long Team-Building Intervention: Examining the Effect of Team Goal Setting on Cohesion," Journal of Sport & Exercise Psychology (30:2).
  67. Sexton, J. B., and Helmreich, R. L. 2000. "Analyzing Cockpit Communications: The Links between Language, Performance, Error, and Workload," Journal of Human Performance in Extreme Environments (5:1), p. 6.
  68. Sharma, R., and Yetton, P. 2007. "The Contingent Effects of Training, Technical Complexity, and Task Interdependence on Successful Information Systems Implementation," MIS Quarterly (31:2), pp. 219-238.
  69. Shaw, J. B., and Barrett-Power, E. 1998. "The Effects of Diversity on Small Work Group Processes and Performance," Human Relations (51:10), pp. 1307-1325.
  70. Sherry, J. 2004. "Flow and Media Enjoyment," Communication Theory (14:4), pp. 328-347.
  71. Smith, K. G., Smith, K. A., Olian, J. D., Sims Jr, H. P., O'Bannon, D. P., and Scully, J. A. 1994. "Top Management Team Demography and Process: The Role of Social Integration and Communication," Administrative science quarterly), pp. 412-438.
  72. Stewart, G. L., Manz, C. C., and Sims, H. P. 1999. Team Work and Group Dynamics. Wiley New York.
  73. Straub, D., Boudreau, M.-C., and Gefen, D. 2004. "Validation Guidelines for I.S. Positivist Research," Communications of the Association for Information systems (13), pp. 380-427.
  74. Sundstrom, E., De Meuse, K. P., and Futrell, D. 1990. "Work Teams: Applications and Effectiveness," American psychologist (45:2), p. 120.
  75. Sweetser, P., and Wyeth, P. 2005. "Gameflow: A Model for Evaluating Player Enjoyment in Games," ACM Computers in Entertainment (3:3), pp. 1-25.
  76. Tellegen, A., and Atkinson, G. 1974. "Openness to Absorbing and Self-Altering Experiences ('Absorption'), a Trait Related to Hypnotic Susceptibility," Journal of Abnormal Psychology (83:3), pp. 268-277.
  77. Tjosvold, D., Yu, Z. y., and Hui, C. 2004. "Team Learning from Mistakes: The Contribution of Cooperative Goals and Problem Solving*," Journal of Management Studies (41:7), pp. 1223-1245.
  78. Weick, K. E., Sutcliffe, K. M., and Obstfeld, D. 2008. "Organizing for High Reliability: Processes of Collective Mindfulness," Crisis management (3), pp. 81-123.
  79. Weinberg, R. S., and Gould, D. 2011. Foundations of Sport and Exercise Psychology. Human Kinetics.
  80. Winter, J. K., Waner, K. K., and Neal-Mansfield, J. C. 2008. "Team Climate and Productivity for Similar Majors Versus Mixed Majors," Journal of Education for Business (83:5), pp. 265-269.

Related papers

The effects of playing cooperative and competitive video games on teamwork and team performance
John Leddo

Playing video games is a pervasive activity among middle school students. Researchers are now investigating whether such play carries any educational benefits. One aspect of many video games is teamwork. The goal of the present research was to investigate whether playing video games cooperatively with or competitively against others affects later teamwork behavior and team performance. 60 middle school students, all without previous video game playing experience, participated in the present study. They were randomly assigned to one of three experimental conditions: no video game playing, cooperative video game playing, and competitive video game playing. Those in the video game conditions then were taught how to play Modern Warfare 3 and played for two hours. They were randomly paired with another subject from the same condition and either played with or against that person. Two weeks later, all participants were randomly paired with new partners from the same experimental condition and played a Prisoner's Dilemma game where points are awarded to players based on whether they play cooperatively or competitively with each other. Total team scores were tallied after 20 trials. Results showed that those who played Modern Warfare 3 cooperatively scored the highest, while those who played it competitively scored the lowest. Results suggest that video game playing can bolster teamwork and team performance when played cooperatively and impair teamwork and team performance when played competitively.

View PDFchevron_right
The Effects of Team Flow on Performance: A Video Game Experiment
Dr. Douglas L. Dean

2014

Research on effective team work has traditionally explained team performance as a result of team cohesion and goal commitment. Team cohesion was originally defined as the general level of attraction the team members had to all others in their group. This social relations-based concept of team cohesion is generally a strong indicator of team performance. However, more recent research has stressed the importance of incorporating the team members’ mutual level of commitment to the team task as another sub-dimension of cohesion. When including task commitment, team cohesion is a somewhat weaker predictor of team performance (Beal et al., 2003). To better conceptualize the role of the task engagement and to explain team performance, we incorporate a variable more relevant to the characteristics of a team task: team flow. The concept of “flow” has been well researched and theorized at the individual level. However, in an experiment based on collaborative video gaming, we demonstrate that ...

View PDFchevron_right
COMPUTER GAMES AS A TOOL TO ENHANCE REMOTE TEAM AND COLLABORATION EXPERIENCE
Ján Papula

Proceedings of the 15th International Technology, Education and Development Conference, INTED2021

The Covid-19 pandemic was indeed a global game changer. It impacted literally every part of our lives. The most notable part for most of us was the switch to remote work and collaboration. As meeting rooms were exchanged for Zoom calls and office spaces for our living rooms, we settled in to study the impact of remote working on our workforce. Initially the data coming in where excellent. They showed up to 60% productivity jumps, more free time for employees. Meetings were suddenly starting on time, and we saved on average more than 1 hour of our daily time commuting from work and back. Companies started to cancel office leases and where slowly planning migration to permanent working from home environment. However, as the pandemic drag on problems started to emerge. Mainly integration of new employees into the working process became a huge problem and drop our rates for new employees surged by as much as 30%. The main reason lack of communication, team interaction and personal oversight. New employees were missing the presence on the workplace, they failed in getting to know their new colleagues and felt lost under the load of new work left with just online calls to provide guidance. With first remote freshman arriving University of Comenius where facing the similar problem. To measure the effectiveness of various online integration tools and methods we have designed a scientific experiment in which we tried to measure the level of student integration achieved with the help of the most rapidly growing entertainment activity of our current time: gaming. In our experiment we have randomly assigned 60 students to 8 member teams. Over the course of two weeks two online classes where conducted. The experimental group of students that have never ever met physically in their lives was tasked with playing what during the pandemic became the most streamed game on twitch.tv platform Among US. A game oriented at cooperation that forced students to personal interaction and communication. At the conclusion of our study we found out that students noticed significant increase in trust between the team members. Students further rated that interpersonal communication in the team improved rapidly during the two weeks. In our article we aim to further analyse the impact and improvement of team abilities and cooperation in a remote team via introduction of computer games as a teambuilding tool.

View PDFchevron_right
Effects of serious games on perceived team cohesiveness in a multi-user virtual environment
Michael Cardus, Birgül Kutlu Bayraktar

Computers in Human Behavior, 2016

This study aims to explore the effects of a serious game on perceived team cohesiveness in a multiuser virtual environment. A one-shot case study/post-test only experiment design was used in this study. A questionnaire was administered to the participants, who played the serious game Zoom. Multiple regression analysis was used to test the proposed framework. The results indicated that the overall framework is statistically significant. The user interface elements of the game and the attitudes of the participants towards the game affected perceived team cohesiveness, whilst the personality factor "extraversion" was found to have a moderator effect on these relationships. The study is limited by the sample size, the self-reported survey and the fact that it had only one game play. The proposed framework of the study can be used by educators, researchers and managers working with groups to foster team cohesiveness in their organizations. This study differs from previous studies mainly by the application of a statistical model to observe the effects of multiuser virtual environment serious games on perceived team cohesiveness.

View PDFchevron_right
Enhancing Teamwork through Games: A Systematic Literature Review
Sakhi Aggrawal, Henrietta Boowuo

2023 IEEE Frontiers in Education Conference (FIE), 2023

This paper presents a systematic literature review that examines the enhancement of teamwork through games. The importance of teamwork in various domains is highlighted, emphasizing its role in achieving common goals and fostering effective group efforts. However, teaching teamwork poses challenges, as educators need to address dynamic interactions and develop students' collaborative skills and abilities. Furthermore, the history of games in education is explored, tracing their roots to John Locke's educational theories and their application in facilitating engaging and effective learning experiences. The methodology section outlines the inclusion and exclusion criteria for selecting relevant studies. Peer-reviewed articles published after 2010 were included, focusing on primary research that specifically addresses teamwork. Two electronic databases, Taylor & Francis, PubMed, and IEEE Xplore, were utilized to gather resources, ensuring reliable and abundant data. The data analysis involved a summary and evaluation of published research on enhanced teamwork approaches. A systematic literature review table was constructed to synthesize and summarize the selected studies. The PRISMA model was followed for identifying, assessing eligibility, and including relevant articles in the review. The results section presents key findings from the selected studies, showcasing their study designs, research questions, target populations, domains, and learning outcomes. The studies highlight the potential of teamwork to enhance team performance in games and the effectiveness of game-based training for fostering teamwork. Additionally, computer-based learning games were found to encourage collaborative learning and help students understand the significance of teamwork in achieving desired outcomes. This systematic literature review contributes to the understanding of how games can be used as effective tools for enhancing teamwork. It provides insights into the existing research landscape and identifies gaps and opportunities for further investigation. The findings have implications for educators, trainers, and organizations seeking to foster effective teamwork skills through game-based approaches. This paper can serve as a valuable resource for researchers and practitioners interested in exploring the intersection of teamwork and games in various contexts.

View PDFchevron_right

Related topics

  • Computer Science
    • 580 California St., Suite 400
    San Francisco, CA, 94104
    © 2025 Academia. All rights reserved