The Influence of Business Simulation Game Experience on Students Perceived Learning Outcomes and Satisfaction
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Abstract
The objectives of this research were to examine students' perceived learning outcomes and satisfaction with the management accounting course at a private university in Guangdong, China, which integrated the business simulation game, iBizSim. Sample data was collected from target population by using quantitative method and questionnaire as a tool. The researchers have encountered challenges in incorporating experiential learning, game-based learning, and authentic team-based learning into the business curriculum, despite mounting evidence that collaborative learning can enhance learning outcomes and satisfaction. Previous studies exploring the impact of concept understanding, skills development, and affective evaluation on learning outcomes remain limited, and there are no existing hypotheses relating to these latent variables. By addressing these gaps, this research contributes to the advancement of knowledge in the field. In this study, 427 surveys were collected and analyzed using Structural Equation Modeling (SEM) with SPSS 26.0 and Amos 23.0 to test hypotheses and confirm causal relationships among variables. The quantitative results supported the proposition that experience generation from the business simulation game positively influences learner perceived learning outcomes and satisfaction. Improved conceptual understanding, affective evaluation, and teamwork were identified as contributing factors. However, no significant influence was found between skills development and perceived learning outcomes, consistent with limited previous research on this aspect. Based on these findings, it is recommended that teachers of business management courses adopt simulation-based instruction in team-based and experience-generated environments to enhance perceived learning outcomes and satisfaction.
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Arbaugh, J. B., & Benbunan-Finch, R. (2006). An investigation of epistemological and social dimensions of teaching in online learning environments. Academy of Management Learning & Education. 5 (4), 435-447.
Baber, H. (2020). Determinants of students’ perceived learning outcome and satisfaction in online learning during the pandemic of COVID-19. Journal of Education and e-learning Research. 7 (3), 285-292. https://doi.org/10.20448/journal.509.2020.73.285. 292.
Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin. 107 (2), 238–246. https://doi.org/10.1037/0033-2909.107.2.238
Cronbach, L. J. (1951). Coefficient Alpha and The Internal Structure of Tests. Psychometrika 16, 297–334. https://doi.org/10.1007/BF02310555.
Cui, Y. T., & Zhao Z. Q. (2020). The impact of virtual reality technology on students' learning performance: a meta-analysis based on 59 experimental or quasi-experimental studies. Distance education in China, 550 (11), 59-67+77. https://doi.org/10.13541/j.cnki. chinade.2020.11.007.
Engel, K. S., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of Psychological Research Online. 8 (8), 23-74.
Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research. 18 (1), 39-50.
Fuchs, L. S., & Fuchs, D. (2007). A model for implementing responsiveness to intervention. Teaching Exceptional Children. 39 (5), 14-19. https://doi.org/10.1177/004005990 703900503
George, D., & Mallery, M. (2010). SPSS For Windows Step by Step: A Simple Guide and Reference, 17.0 Update, 10th ed. Pearson Press.
Ginsburg, H. P., Lee, J. S., & Boyd, J. S. (2014). Mathematics education for young children: What it is and how to promote it. Routledge. https://doi.org/10.1002/j.2379-3988. 2008.tb00054.x
Gros, B., & López, M. (2016). Students as co-creators of technology-rich learning activities in higher education. International Journal of Educational Technology in Higher Education. 13 (1), 28.
Gosen, J., & Washbush, J. (2004). A Review of Scholarship on Assessing Experiential Learning Effectiveness. Simulation & Gaming. 35 (2), 270-293. https://doi.org/10. 1177/1046878104263544.
Hair, J. F., Black., W. C., Babin. B. J., Anderson., R. E., &L.Tatham., R. (2006). Multivariant Data Analysis. Pearson International Edition.
Ikhsan, R. B., Saraswati, L. A., Muchardie, B. G., & Susilo, A. (2019). The determinants of students' perceived learning outcomes and satisfaction in BINUS online learning. Paper presented at the 2019 5th International Conference on New Media Studies (CONMEDIA). IEEE, 68-73.
Jääskä, E., Lehtinen, J., Kujala, J., & Kauppila, O. (2022). Game-based learning and students’ motivation in project management education. Project Leadership and Society. 3, 1000 55. https://doi.org/10.1016/j.plas.2022.100055
Jaccard, D., Bonnier, K. E., & Hellström, M., (2022). How might serious games trigger a transformation in project management education? Lessons learned from 10 Years of experimentations. Project Leadership and Society. 3, 100047 https://doi.org/10.1016/j. plas.2022.100047.
Johnson, W. D., Johnson, T. R., & Smith, A. K. (1998). Cooperative learning returns to college what evidence is there that it works? Change: The Magazine of Higher Learning, 30 (4), 26-35.
Kolb, A. Y., & Kolb, D. A. (2009). The Learning Way: Meta-cognitive Aspects of Experiential Learning. Simulation & Gaming, 40 (3), 297-327. https://doi.org/10.1177/104687 8108325713.
Lohmann, G., Pratt, M. A., Benckendorff, P., Strickland, P., Reynolds, P., & Whitelaw, P. A. (2019). Online business simulations: authentic teamwork, learning outcomes, and satisfaction. Higher Education, 77 (3), 455-472.
Lovelace, K. J., Eggers, F., & Dyck, L. R. (2016). I Do and I Understand: Assessing the Utility of Web-Based Management Simulations to Develop Critical Thinking Skills. Academy of Management Learning & Education, 15 (1), 100-121. https://doi.org/10.5465/amle. 2013.0203
Mohsen, K., Abdollahi, S., & Omar, S. (2018). Evaluating the educational value of simulation games: Learners' perspective. Innovations in Education and Teaching International.
Norman, G. (2010). Likert scales, levels of measurement and the “laws” of statistics. Advances in Health Sciences Education, 15 (5), 625-632.
Ranchhod, A., Gurău, C., Loukis, E., & Trivedi, R. (2014). Evaluating the educational effectiveness of simulation games: A value generation model. Information Sciences, 264, 75-90. https://doi.org/10.1016/j.ins.2013.09.008.
Salas, E., Wildman, J. L., & Piccolo, R. F. (2009). Using Simulation-Based Training to Enhance Management Education. Academy of Management Learning & Education, 8 (4), 559-573. https://doi.org/10.5465/amle.2009.47785474.
Sharma, G. P., Verma, R. C., & Pathare, P. (2005). Mathematical modeling of infrared radiation thin layer drying of onion slices. Journal of Food Engineering, 71 (3), 282–286.
Sica, C., & Ghisi, M. (2007). The Italian versions of the Beck Anxiety Inventory and the Beck Depression Inventory-II: Psychometric properties and discriminant power. In M.A. Lange (Ed.), Leading - Edge psychological tests and testing research (pp. 27-50). Nova.
Wu, J. H., & Wang, Y. M. (2006). Measuring KMS success: A respecification of the DeLone and McLean’s model. Information and Management, 43 (6), 728–739. https://doi.org/ 10.1016/j.im.2006.05.002