Assessing the mediating role of student engagement on the relationship between student interactions and student performance in entrepreneurship education
DOI:
https://doi.org/10.32890/gbmr2024.16.1.5Keywords:
Entrepreneurship Education, Massive Enrolment, Technology Mediated Learning, Student Performance, SmartPLSAbstract
Previous literature suggested that more studies are needed in the context of technology mediated learning in entrepreneurship education. Hence, this study aims is to gauge the understanding of the factors influencing student performance for the Fundamentals of Entrepreneurship (ENT300) subject. This study is underpinned by the Social Learning Theory: Groups, Nets, and Sets. This study was conducted in the Universiti Teknologi MARA Perlis Branch (UiTM Perlis) using survey. 281 students had participated in this study. Data were analyzed using SmartPLS. Since the research model for the study was reflective-formative, the second order approach was used to assess the structural model. The results of this study reveal positive influence between Student Interactions and Student Engagement, as well as between Student Engagement and student performance variables (Satisfaction, Efficiency, and Effectiveness). Also, Student Engagement plays a significant role as a mediator between Student Interactions and student performance variables. This study contributes to the literature of the development of Social Learning Theory: Groups, Nets, and Sets. Finally, this study makes practical contributions to the higher learning institution that plans to use a technology mediated learning approach for large enrolment subject.
Downloads
References
Albloy, A. M., & Mohamed, W. M. (2019). Perceptions And Attitudes of Saudi Arabia University Students Towards Using WhatsApp As Students-teachers Interactive Tool. Advances in Social Sciences Research Journal –, 6(11), 93–109.
Allen, E., & Seaman, J. (2011). Going the distance: Online Education in the United States, 2011. In Workforce. http://www.onlinelearningsurvey.com/highered.html
Ally, M. (2005). Foundations of educational theory for online learning. In T. Anderson & F. Elloumi (Eds.), Theory and practice of online learning (pp. 3–31). Athabasca University.
Anderson, T. (2005). Toward a Theory of Onlie Learning. In T. Anderson & F. Elloumi (Eds.), Theory and practice of online learning (Issue 1997, pp. 33–60). Athabasca University.
Anderson, T. (2016). Theories for Learning with Emerging Technologies. In Emergence and Innovation in Digital Learning (pp. 35–50). https://doi.org/10.15215/aupress/9781771991490.01 Anthony, B., Kamaludin, A., Romli, A., Raffei, A. F. M., Nincarean A/L Eh Phon, D., Abdullah, A.,
Ming, G. L., Shukor, N. A., Nordin, M. S., & Baba, S. (2019). Exploring the role of blended learning for teaching and learning effectiveness in institutions of higher learning: An empirical investigation. Education and Information Technologies, 24(6), 3433–3466. https://doi.org/10.1007/s10639-019-09941-z
Anthonysamy, L., Koo, A. C., & Hew, S. H. (2020). Self-regulated learning strategies and nonacademic outcomes in higher education blended learning environments: A one decade review. Education and Information Technologies. https://doi.org/10.1007/s10639-020-10134-2 Bernard, R. M., Abrami, P. C., Borokhovski, E., Wade, C. a., Tamim, R. M., Surkes, M. a., & Bethel,
E. C. (2009). A Meta-Analysis of Three Types of Interaction Treatments in Distance Education. Review of Educational Research, 79(3), 1243–1289. https://doi.org/10.3102/0034654309333844
Broadbent, J. (2017). Comparing online and blended learner’s self-regulated learning strategies and academic performance. Internet and Higher Education, 33, 24–32. https://doi.org/10.1016/j.iheduc.2017.01.004
Cain, M. K., & Zhang, Z. (2016). Univariate and multivariate skewness and kurtosis for measuring nonnormality : Prevalence, influence and estimation. Behavior Research Methods. https://doi.org/10.3758/s13428-016-0814-1
Chin, W. W. (1998). The Partial Least Squares Approach to Structural Equation Modeling. In G. A. Marcoulides (Ed.), Modern Methods for Business Research. Lawrence Erlbaum Associates.
Chong, Y., & Soo, H. S. (2021). Evaluation of first-year university students ’ engagement to enhance student vevelopment. Asian Journal of University Education, 17(2), 113–121.
Coleman, E., & Connor, E. O. (2019). The role of WhatsApp ® in medical education ; a scoping review and instructional design model. BMC Medical Education, 8.
Dixson, M. D. (2010). Creating effective student engagement in online courses : What do students find engaging ? Journal of the Scholarship of Teaching and Learning, 10(2), 1–13. Global Business Management Review: Vol. 16 Number 1 June 2024
Drysdale, J. S., Graham, C. R., Spring, K. J., & Halverson, L. R. (2013). An analysis of research trends in dissertations and theses studying blended learning. The Internet and Higher Education, 17, 90–100. https://doi.org/10.1016/j.iheduc.2012.11.003
Finstad, K. (2010). Interacting with Computers The Usability Metric for User Experience. Interacting with Computers, 22(5), 323–327. https://doi.org/10.1016/j.intcom.2010.04.004
Fook, C. Y., Narasuman, S., Aziz, N. A., Mustafa, S. M. S., & Han, C. T. (2021). Smartphone usage among university students. Asian Journal of University Education, 17(1), 283–291. https://doi.org/10.24191/ajue.v17i1.12622
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2014). A primer on partial least squares structural equation modeling (PLS-SEM). SAGE. https://doi.org/10.1108/EBR-10-2013-0128
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-20180203
Halverson, L. R., & Graham, C. R. (2019). Learner Engagement in Blended Learning Environments: A Conceptual Framework. Online Learning, 23(2), 145–178. https://doi.org/10.24059/olj.v23i2.1481
Halverson, L. R., Graham, C. R., Spring, K. J., Drysdale, J. S., & Henrie, C. R. (2014). A thematic analysis of the most highly cited scholarship in the first decade of blended learning research. The
Internet and Higher Education, 20, 20–34. https://doi.org/10.1016/j.iheduc.2013.09.004
Hassan, A., Anwar, I., Saleem, I., Islam, K. M. B., & Hussain, S. A. (2021). Individual entrepreneurial orientation, entrepreneurship education and entrepreneurial intention: The mediating role of entrepreneurial motivations. Asian Journal of University Education, 17(2), 236–251. https://doi.org/10.1177/09504222211007051
Havik, T., & Westergård, E. (2019). Do Teachers Matter ? Students ’ Perceptions of Classroom Interactions and Student Engagement Do Teachers Matter ? Students ’ Perceptions of Classroom. Scandinavian Journal of Educational Research, 0(0), 1–20. https://doi.org/10.1080/00313831.2019.1577754
Henseler, J., Ringle, C. M., & Sarstedt, M. (2014). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20, 277–319. https://doi.org/10.1108/S1474-7979(2009)0000020014
Kock, N., & Lynn, G. S. (2012). Lateral collinearity and misleading results in variance-based SEM: An illustration and recommendations. Journal of the Association for Information Systems Some, 13(7), 546–580. https://doi.org/10.1016/s0193-953x(18)30902-x
Kratochvil, J. (2014). Efficiency of e-learning in an information literacy course for medical students at the Masaryk University. The Electronic Library, 32(3), 322–340. https://doi.org/10.1108/EL-072012-0087
Krejcie, R. V, & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30, 607–610.
Kuo, Y.-C., Walker, A. E., Schroder, K. E. E., & Belland, B. R. (2014). Interaction, Internet selfefficacy, and self-regulated learning as predictors of student satisfaction in online education courses. The Internet and Higher Education, 20, 35–50. https://doi.org/10.1016/j.iheduc.2013.10.001 Global Business Management Review: Vol. 16 Number 1 June 2024
Lin, H. M., Lee, M. H., Liang, J. C., Chang, H. Y., Huang, P., & Tsai, C. C. (2019). A review of using partial least square structural equation modeling in e-learning research. British Journal of Educational Technology, 0(0), 1–19. https://doi.org/10.1111/bjet.12890
Nasirun, N., Noor, S. M., Yusoff, R. Z., & Othman, A. A. (2015). A Comparison Between Web Enhancer Learners and Blended Learners in Flipped Classroom : A Quasi-Experimental Approach. International Academic Research Journal of Business and Technology, 1(2), 100–107.
Noesgaard, S. S., & Ørngreen, R. (2015). The effectiveness of e-learning: An explorative and integrative review of the definitions, methodologies and factors that promote e-Learning effectiveness. Electronic Journal of E-Learning, 13(4), 278–290.
Noraini, N., Noor, S. M., Yusoff, R. Z., & Othman, A. A. (2017). Student engagement, student interactions and student satisfaction in blended leaning: A case of entrepreneurship education. Advanced Science Letters, 23(8), 7952–7955. https://doi.org/10.1166/asl.2017.9617
Overbaugh, R. C., & Nickel, C. E. (2011). A comparison of student satisfaction and value of academic community between blended and online sections of a university-level educational foundations course. The Internet and Higher Education, 14(3), 164–174. https://doi.org/10.1016/j.iheduc.2010.12.001
Povera, A., & Babulai, V. (2019). School close immediatedly if API reach very unhealthy level. The New Straits Times.
Poysa, S., Vasalampi, K., Muotka, J., Lerkkanen, M.-K., Poikkeus, A., & Nurmi, J. (2018). Teacher – student interaction and lower secondary school students ’ situational engagement. British Journal of Educational Psychology, 1–19. https://doi.org/10.1111/bjep.12244
Raes, A., Detienne, L., Windey, I., & Depaepe, F. (2019). A systematic literature review on synchronous hybrid learning : gaps identified. Learning Environments Research, 1–22. https://doi.org/10.1007/s10984-019-09303-z
Ratten, V., & Usmanij, P. (2020). Entrepreneurship education: Time for a change in research direction? International Journal of Management Education, In Press. https://doi.org/10.1016/j.ijme.2020.100367
Renner, D., Laumer, S., & Weitzel, T. (2014). Effectiveness and Efficiency of Blended Learning – A Literature Review. Americas Conference on Information Systems, Savannah, 2014, 1–13.
Sakr, M. (2019). ‘It just opened my eyes a bit more’: student engagement with Instagram to develop understanding of complex concepts. Teaching in Higher Education, 0(0), 1–14. https://doi.org/10.1080/13562517.2019.1613356
Sarstedt, M., Hair, J. F., Cheah, J. H., Becker, J. M., & Ringle, C. M. (2019). How to specify, estimate, and validate higher-order constructs in PLS-SEM. Australasian Marketing Journal, 27(3), 197–211. https://doi.org/10.1016/j.ausmj.2019.05.003
So, H.-J., & Brush, T. a. (2008). Student perceptions of collaborative learning, social presence and satisfaction in a blended learning environment: Relationships and critical factors. Computers & Education, 51(1), 318–336. https://doi.org/10.1016/j.compedu.2007.05.009
Sousa, M. J., Carmo, M., Gonçalves, A. C., Cruz, R., & Martins, J. M. (2019). Creating knowledge and entrepreneurial capacity for HE students with digital education methodologies: Differences in the perceptions of students and entrepreneurs. Journal of Business Research, 94 (February 2018), 227–240. https://doi.org/10.1016/j.jbusres.2018.02.005
Talaei-khoei, A., & Daniel, J. (2020). Can Facebook Improve Students ’ Engagement in Flipped Classes ? Community of Inquiry Approach 2. Students ’ Engagement : Community of Inquiry ( COI ). 53rd Hawaii International Conference on System Sciences, 3, 3–11. Global Business Management Review: Vol. 16 Number 1 June 2024
The Star. (2019). Online lessons for students if haze keeps schools closed, says Education Ministry. The Star.
Vo, H. M., Zhu, C., & Diep, N. A. (2017). The effect of blended learning on student performance at course-level in higher education: A meta-analysis. Studies in Educational Evaluation, 53, 17–28. https://doi.org/10.1016/j.stueduc.2017.01.002
Wu, J.-H., Tennyson, R. D., & Hsia, T.-L. (2010). A study of student satisfaction in a blended e-learning system environment. Computers & Education, 55(1), 155–164. https://doi.org/10.1016/j.compedu.2009.12.012
Xu, L., Peng, X., & Prybutok, V. (2019). Formative measurements in operations management research: Using partial least squares. Quality Management Journal, 26(1), 18–31. https://doi.org/10.1080/10686967.2018.1542287
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Disclaimer
Global Business Management Review (GBMR) has taken all reasonable measures to ensure that material contained in this website is the original work of the author(s). However, the Journal gives no warranty and accepts no responsibility for the accuracy or the completeness of the material; no reliance should be made by any user on the material. The user should check with the authors for confirmation.
Articles published in the Global Business Management Review (GBMR) do not represent the views held by the editors and members of the editorial board. Authors are responsible for all aspects of their articles except the editorial screen design.
Submission of an article is done with the understanding that the article has not been published before (except in the form of an abstract or as part of a published lecture, or thesis) that it is not under consideration for publication somewhere else; that if and when the article is accepted for publication, the author's consent to automatic transfer of the copyright to the publisher.
