Date of Award

2018

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Education

Abstract

The problem addressed by this study was that it was unknown how Glo-Bus Strategy Simulation student login activity related to simulated company performance. Also, student perceptions about login activity were unknown. The purpose was to use correlation and regression analysis to study relationships between login activity (three predictor independent variables) and simulation scores (seven outcome dependent variables) and then analyze them considering student perceptions about login activity. Knowing the predictor values of each login activity (frequency, duration, reports-opening) could provide guidance to simulation software designers and to simulation faculty. In the literature, there were studies about strategy simulation login activity, but they did not fully address how various login activities were related to simulation multi-functional scores. Instead, published studies focused on other aspects of simulation: teamwork, soft skills, engagement level, team processes or other non-Glo-Bus strategy simulations. Some studies about strategy simulations called for more narrowly defined objectives and student accountability. This study supported that call – revealing that opening reports (more meaningful engagement) was more predictive than frequency or duration. The literature also included research on learning theories. This study considered how certain learning theories were demonstrated by login activities correlation and regression with performance and how learning theories were demonstrated by student perceptions. The study included operating from a base of several typical assumptions and limitations (convenience samples and complex variables). Also, the study included common research practices in using software ex post facto data and student questionnaire data. Key findings of the study were multi-fold. First, regression analysis revealed the strong predictive value of opening reports as a login activity which influenced functional (socio and technical) scores. Second, regression revealed finance as a technical function was the strongest predictor of socio scores. Third, student perceptions supported the power of reports and simulations use of Novaks (2010) Meaningful Learning Requirements. Several recommendations for practice and for further research resulted from these findings.

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