| Simulation complexity |
More complex simulations contribute to more learning than less complex simulations (p-value < 0.01) (Wolfe, 1978Wolfe, J. (1978). The effects of game complexity on the acquisition of business policy knowledge. Decision Sciences, 9(1), 143-155.). |
The complexity, despite having a moderate statistical correlation with the perceived learning intensity of business games participants (r = 0.343, p-value < 0.01), did not compose the regression model. Redundancy was identified with the Debriefing and Duration variables. |
| Realism, produced through complexity, is a determining factor for learning of business games participants (Hall & Cox, 1994Hall, J., & Cox, B. (1994). Complexity: it is really that simple. Developments in Business Simulations and Experiential Exercises, 21, 30-34.). |
In the factorial model of main components,
the most Complex Simulation variable was associated with the Complexity factor (factorial load = 0.723 and commonality = 0.589) (Sauaia, 1995Sauaia, A. C. A. (1995). Satisfação e aprendizagem em jogos de empresas: contribuições para a educação gerencial. Tese de doutorado, Universidade de São Paulo, São Paulo, SP, Brasil.). |
| Duration of the simulation rounds |
The simple linear regression model indicated that the duration can be predicted from the number of decisions (assumed as proxy for complexity) with significant beta weight (β = 0.829, p-value < 0.01), leading to the proposition that the duration of the simulation, together with the complexity, influences the learning of business game participants (Hall & Cox, 1994Hall, J., & Cox, B. (1994). Complexity: it is really that simple. Developments in Business Simulations and Experiential Exercises, 21, 30-34.). |
The duration of the simulation rounds presented a moderate statistically significant correlation with the perceived learning intensity of business games participants (r = 0.424, p-value < 0.01) and composed the regression model (β = 0.352, p-value ≅ 0.000). In addition, it presented a statistically significant correlation with the complexity of the simulation (r = 0.368, p-value < 0.01). |
| In the factorial model of main components, the longest Duration variable was associated with the factors Learning Climate (factorial load = 0.439), Satisfaction (factorial load = 0.420) and Complexity (factorial load = 0.381). The commonality was 0.601 (Sauaia, 1995Sauaia, A. C. A. (1995). Satisfação e aprendizagem em jogos de empresas: contribuições para a educação gerencial. Tese de doutorado, Universidade de São Paulo, São Paulo, SP, Brasil.). |
| Professor |
No statistically significant correlation or beta weight (p-value > 0.05) was found between student learning and professor (Mayer et al., 2011Mayer, B. W., Dale, K. M., Fraccastoro, K. A., & Moss, G. (2011). Improving transfer of learning: relationship to methods of using business simulation. Simulation and Gaming, 42(1), 64-84.). |
No statistically significant correlation or beta weight was identified between the perceived learning intensity of business games participants and the professor of the simulation. The professor presented a statistically significant correlation with the debriefing stage (r = 0.211, p-value < 0.05). |
| In the factorial model of main components, the variable professor was associated to the Cognitive learning (factorial load = 0.324) and Parameters of the experience (factorial load = 0.397) factors. The commonality was 0.475 (Sauaia, 1995Sauaia, A. C. A. (1995). Satisfação e aprendizagem em jogos de empresas: contribuições para a educação gerencial. Tese de doutorado, Universidade de São Paulo, São Paulo, SP, Brasil.). |
| Debriefing |
The quantum of perceived learning of business games participants with debriefing is superior to that of those who participated in simulations without debriefing (p-value < 0.05). The mean effect size (d = 0.45) shows an average improvement of 18% because of the debriefing (Lacruz, forthcomingLacruz, A. J. (forthcoming). Influência do debriefing no aprendizado em jogos de empresas: um delineamento experimental.). |
The debriefing stage presented a moderate statistically significant correlation with the perceived learning intensity of business games participants (r = 0.479, p-value < 0.01) and composed the regression model (β = 0.406, p-value ≅ 0.000). In addition, it presented a statistically significant correlation with the complexity (r = 0.207, p-value < 0.05) and professor (r = 0.211, p-value < 0.05) variables. |
| In business games, there is a risk that the participants do not complete the experiential learning cycle due to a lack of reflective activities, suggesting the need to add new stages to the process that could stimulate the analysis of the results of the simulation rounds so that reflective observations may contribute to the completion of the experiential learning cycle (Dias et al., 2013aDias, G. P. P., Sauaia, A. C. A., & Yoshizaki, H. T. Y. (2013a). Estilos de aprendizagem Felder-Silverman e o aprendizado com jogos de empresas. Revista de Administração de Empresas, 53(5), 469-484.). |
| Manual |
There is a significant correlation between learning and the business game manual (r = 0.32, p-value = 0.001). In addition, the results of the regression analysis indicated that learning can be predicted from the way students learned the simulation with significant beta weight for learning from the manual (β = 0.34, p-value = 0.001) (Mayer et al., 2011Mayer, B. W., Dale, K. M., Fraccastoro, K. A., & Moss, G. (2011). Improving transfer of learning: relationship to methods of using business simulation. Simulation and Gaming, 42(1), 64-84.). |
No statistically significant correlation or beta weight was identified between the perceived learning intensity of business games participants and the simulation manual, nor with any of the other variables considered to evaluate the simulation dynamics. |
| Team |
There is a significant correlation between learning and the team (r = 0.20, p-value = 0.049). In addition, the results of regression analysis indicated that the transfer of learning can be predicted from the way students learned the simulation with significant beta weight for learning from the team (β = 0.24, p-value = 0.018) (Mayer et al., 2011Mayer, B. W., Dale, K. M., Fraccastoro, K. A., & Moss, G. (2011). Improving transfer of learning: relationship to methods of using business simulation. Simulation and Gaming, 42(1), 64-84.). |
No statistically significant correlation or beta weight was identified between the perceived learning intensity of business games participants and the team, nor with any of the other variables considered to evaluate the simulation dynamics. |
| In the main component factorial model, the variable Teammates was associated with the Cognitive learning (factorial load = 0.305) and Team performance (factorial load = 0.508) factors. The commonality was 0.538 (Sauaia, 1995Sauaia, A. C. A. (1995). Satisfação e aprendizagem em jogos de empresas: contribuições para a educação gerencial. Tese de doutorado, Universidade de São Paulo, São Paulo, SP, Brasil.). |
