1,511
Views
35
CrossRef citations to date
0
Altmetric
Articles

Investigating the effect of flow experience on learning performance and entrepreneurial self-efficacy in a business simulation systems context

& ORCID Icon
Pages 1593-1608 | Received 14 Apr 2019, Accepted 21 Feb 2020, Published online: 03 Mar 2020

References

  • Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423.
  • Aube, C., Brunelle, E., & Rousseau, V. (2014). Flow experience and team performance: The role of team goal commitment and information exchange. Motivation and Emotion, 38(1), 120–130.
  • Bagheri, A., & Abbariki, M. (2017). Competencies of disabled entrepreneurs in Iran: Implications for learning and development. Disability & Society, 32(1), 69–92.
  • Bandura, A. (1986). Social foundation of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice Hall.
  • Bandura, A. (1989). Human agency in social cognitive theory. American Psychologist, 44(9), 1175–1184.
  • Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman.
  • Barbosa, S. D., Gerhardt, M. W., & Kickul, J. R. (2007). The role of cognitive style and risk preference on entrepreneurial self-efficacy and entrepreneurial intentions. Journal of Leadership & Organizational Studies, 13(4), 86–104.
  • Bird, B. (1988). Implementing entrepreneurial ideas: The case for intention. Academy of Management Review, 13(3), 442–453.
  • Calder, B. J., Phillips, L. W., & Tybout, A. M. (1981). Designing research for application. Journal of Consumer Research, 8(2), 197–207.
  • Chang, C. C., Liang, C., Chou, P. N., & Lin, G. Y. (2017). Is game-based learning better in flow experience and various types of cognitive load than non-game-based learning? Perspective from multimedia and media richness. Computers in Human Behavior, 71, 218–227.
  • Chang, K.-E., Wu, L.-J., Weng, S.-E., & Sung, Y.-T. (2012). Embedding game-based problem-solving phase into problem-posing system for mathematics learning. Computers & Education, 58, 775–786.
  • Chen, C. C., Greene, P. G., & Crick, A. (1998). Does entrepreneurial self-efficacy distinguish entrepreneurs from managers? Journal of Business Venturing, 13, 295–316.
  • Chin, W. W., & Newsted, P. R. (1999). Structural equation modeling analysis with small samples using partial least squares. In R. Hoyle (Ed.), Statistical strategies for small sample research (pp. 307–341). Thousand Oaks, California: Sage Publications.
  • Cox, L. W., Mueller, S. L., & Moss, S. E. (2002). The impact of entrepreneurship education on entrepreneurial self-efficacy. International Journal of Entrepreneurship Education, 1(2), 2–23.
  • Csikszentmihalyi, M. (1990). Flow. The psychology of optimal experience. New York: Harper & Row.
  • Csikszentmihalyi, M. (1991). Flow: The psychology of optimal experience. New York: Harper Perennial.
  • Edelman, L. F., Brush, C., & Manolova, T. S. (2008). Entrepreneurship education: Correspondence between practices of nascent entrepreneurs and textbook prescriptions for success. Academy of Management Learning and Education, 7(1), 56–70.
  • Florin, J., Karri, R., & Rossiter, N. (2007). Fostering entrepreneurial drive in business education: An attitudinal approach. Journal of Management Education, 31(1), 17–42.
  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
  • Fox, J., Pittaway, L., & Uzuegbunam, I. (2018). Simulations in entrepreneurship education: Serious games and learning through play. Entrepreneurship Education and Pedagogy, 1(1), 61–89.
  • Ghani, J. A. (1995). Flow in human–computer interactions: Test of a model. In J. M. Carey (Ed.), Human factors in information systems (pp. 291–311). Norwood, NJ: Ablex.
  • Gielnik, M. M., Frese, M., Kahara-Kawuki, A., Katono, I. W., Kyejjusa, S., Ngoma, M., … Dlugosch, T. J. (2015). Action and action-regulation in entrepreneurship: Evaluating a student training for promoting entrepreneurship. Academy of Management Learning & Education, 14(1), 69–94.
  • Gist, M. E., & Mitchell, T. R. (1992). Self-efficacy: A theoretical analysis of its determinants and malleability. Academy of Management Review, 17, 183–211.
  • Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis. New York: Macmillan.
  • Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135.
  • Hou, H. T., & Li, M. C. (2014). Evaluating multiple aspects of a digital educational problem-solving-based adventure game. Computers in Human Behavior, 30, 29–38.
  • Hsieh, Y. H., Lin, Y. C., & Hou, H. T. (2016). Exploring the role of flow experience, learning performance and potential behavior clusters in elementary students’ game-based learning. Interactive Learning Environments, 24(1), 178–193.
  • Hung, C. Y., Sun, J. C. Y., & Yu, P. T. (2015). The benefits of a challenge: Student motivation and flow experience in tablet-PC-game-based learning. Interactive Learning Environments, 23(2), 172–190.
  • Hwang, G. J., Wu, P. H., & Chen, C. C. (2012). An online game approach for improving students’ learning performance in web-based problem-solving activities. Computers & Education, 59(4), 1246–1256.
  • Ibanez, M. B., Di Serio, A., Villaran, D., & Kloos, C. D. (2014). Experimenting with electromagnetism using augmented reality: Impact on flow student experience and educational effectiveness. Computers & Education, 71, 1–13.
  • Kassean, H., Vanevenhoven, J., Liguori, E., & Winkel, D. E. (2015). Entrepreneurship education: A need for reflection, real-world experience and action. International Journal of Entrepreneurial Behaviour & Research, 21(5), 690–708.
  • Kiili, K. (2005). Digital game-based learning: Towards an experiential gaming model. The Internet and Higher Education, 8(1), 13–24.
  • Kiili, K. (2006). Evaluations of an experiential gaming model. Human Technology: An Interdisciplinary Journal on Humans in ICT Environments, 2(2), 187–201.
  • Lainema, T., & Lainema, K. (2007). Advancing acquisition of business know-how: Critical learning elements. Journal of Research on Technology in Education, 40(2), 183–198.
  • Lee, Y. H., Hsiao, C., & Ho, C. H. (2014). The effects of various multimedia instructional materials on students’ learning responses and outcomes: A comparative experimental study. Computers in Human Behavior, 40, 119–132.
  • Lin, C. P., & Joe, S. W. (2012). To share or not to share: Assessing knowledge sharing, interemployee helping, and their antecedents among online knowledge workers. Journal of Business Ethics, 108(4), 439–449.
  • Lin, H.-M., & Tsai, C.-C. (2008). Conceptions of learning management among undergraduate students in Taiwan. Management Learning, 39, 561–578.
  • Lin, H.-H., Yen, W.-C., & Wang, Y.-S. (2018). Investigating the effect of learning method and motivation on learning performance in a business simulation system context: An experimental study. Computers & Education, 127, 30–40.
  • Liu, C. C., Cheng, Y. B., & Huang, C. W. (2011). The effect of simulation games on the learning of computational problem solving. Computers & Education, 57(3), 1907–1918.
  • McGee, J. E., Peterson, M., Mueller, S. L., & Sequeira, J. M. (2009). Entrepreneurial self-efficacy: refining the measure. Entrepreneurship Theory and Practice, 33(4), 965–988.
  • Mueller, S. L., & Goic, S. (2003). East-West differences in entrepreneurial self-efficacy: Implications for entrepreneurship education in transition economies. International Journal of Entrepreneurship Education, 1(4), 613–632.
  • Newbery, R., Lean, J., Moizer, J., & Haddoud, M. (2018). Entrepreneurial identity formation during the initial entrepreneurial experience: The influence of simulation feedback and existing identity. Journal of Business Research, 85, 51–59.
  • Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory. New York: McGraw-Hill.
  • Pando-Garcia, J., Periañez-Cañadillas, I., & Charterina, J. (2016). Business simulation games with and without supervision: An analysis based on the TAM model. Journal of Business Research, 69(5), 1731–1736.
  • Park, J., Parsons, D., & Ryu, H. (2010). To flow and not to freeze: Applying flow experience to mobile learning. IEEE Transactions on Learning Technologies, 3(1), 56–67.
  • Peterman, N. E., & Kennedy, J. (2003). Enterprise education: Influencing students’ perceptions of entrepreneurship. Entrepreneurship Theory and Practice, 28(2), 129–144.
  • Piccoli, G., Ahmad, R., & Lves, B. (2001). Web-based virtual learning environments: A research framework and a preliminary assessment of effectiveness in basic IT skills training. MIS Quarterly, 25(4), 401–426.
  • Premkumar, G., & Bhattacherjee, A. (2008). Explaining information technology usage: A test of competing models. Omega, 36(1), 64–75.
  • Prensky, M. (2001). Fun play and games: What makes games engaging. Digital Game-Based Learning, 5, 1–5.
  • Reinartz, W., Haenlein, M., & Henseler, J. (2009). An empirical comparison of the efficacy of covariance-based and variance-based SEM. International Journal of Research in Marketing, 26(4), 332–344.
  • Rogers, Y., & Muller, H. (2006). A framework for designing sensor-based interactions to promote exploration and reflection in play. International Journal of Human-Computer Studies, 64(1), 1–14.
  • Saeed, S., Yousafzai, S. Y., Yani-De-Soriano, M., & Muffatto, M. (2015). The role of perceived university support in the formation of students’ entrepreneurial intention. Journal of Small Business Management, 53(4), 1127–1145.
  • Snell, L., Sok, P., & Danaher, T. S. (2015). Achieving growth-quality of work life ambidexterity in small firms. Journal of Service Theory and Practice, 25(5), 529–550.
  • St-Jean, E., Radu-Lefebvre, M., & Mathieu, C. (2018). Can less be more? Mentoring functions, learning goal orientation, and novice entrepreneurs’ self-efficacy. International Journal of Entrepreneurial Behaviour & Research, 24(1), 2–21.
  • Sun, J. C. Y., Kuo, C. Y., Hou, H. T., & Lin, Y. Y. (2017). Exploring learners’ sequential behavioral patterns, flow experience, and learning performance in an anti-phishing educational game. Educational Technology & Society, 20(1), 45–60.
  • Tuunanen, T., & Govindji, H. (2016). Understanding flow experience from users’ requirements. Behaviour & Information Technology, 35(2), 134–150.
  • Wang, L. C., & Chen, M. P. (2010). The effects of game strategy and preference-matching on flow experience and programming performance in game-based learning. Innovations in Education and Teaching International, 47(1), 39–52.
  • Wang, C. C., & Hsu, M. C. (2014). An exploratory study using inexpensive electroencephalography (EEG) to understand flow experience in computer-based instruction. Information & Management, 51(7), 912–923.
  • Young, M. R., Klemz, B. R., & Murphy, J. W. (2003). Enhancing learning outcomes: The effects of instructional technology, learning styles, instructional methods, and student behavior. Journal of Marketing Education, 25(2), 130–142.
  • Zhao, H., Seibert, S. E., & Hills, G. E. (2005). The mediating role of self-efficacy in the development of entrepreneurial intentions. Journal of Applied Psychology, 90(6), 1265–1272.
  • Zulfiqar, S., Sarwar, B., Aziz, S., Chandia, K. E., & Khan, M. K. (2018). An analysis of influence of business simulation games on business school students’ attitude and intention toward entrepreneurial activities. Journal of Educational Computing, 57(1), 1–25.