Pengembangan Model Strategic Learning Enabler untuk Meningkatkan Produktivitas Generasi Z dalam Pendidikan Tinggi Digital
DOI:
https://doi.org/10.55606/jurrafi.v5i2.8886Keywords:
Adaptive Learning, Digital Governance, Generation Z, Learning Analytics, Student ProductivityAbstract
This study aims to develop a Strategic Learning Enabler model by reconfiguring the role of Information and Communication Technology (ICT) units to enhance Generation Z student productivity in digital higher education. The research is motivated by the gap between digital transformation demands and the predominantly technical-operational role of ICT units. Using a quantitative explanatory design, this study examines the causal relationships among ICT role reconfiguration, adaptive learning systems, and student productivity. Data were collected through questionnaires distributed to Generation Z students engaged in digital learning environments and analyzed using Structural Equation Modeling (SEM). The findings indicate that Generation Z students exhibit high responsiveness to structured tasks but lack continuity in learning activities due to weak self-regulated learning. The study also reveals that adaptive learning systems significantly mediate the relationship between ICT transformation and student productivity. The proposed model emphasizes digital governance, learning analytics, and micro-tasking structures as key components in building sustainable academic productivity. This research contributes both theoretically and practically by offering an institutional framework for digital learning transformation in higher education.
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References
Baumeister, R. F., Vohs, K. D., & Tice, D. M. (2008). The Strength Model of Self-Control. Current Directions in Psychological Science, 16(6), 351–355. Https://Doi.Org/10.1111/J.1467-8721.2007.00534.X
Bond, M., Bedenlier, S., Marín, V. I., & Händel, M. (2020). Emergency Remote Teaching in Higher Education: Mapping the First Global Online Semester. International Journal of Educational Technology in Higher Education, 17(1), 1–24. Https://Doi.Org/10.1186/S41239-020-00282-X
Bond, M., Marín, V. I., Dolch, C., Bedenlier, S., & Zawacki-Richter, O. (2018). Digital Transformation in Higher Education: A Systematic Review of Research. International Journal of Educational Technology in Higher Education, 15(1), 1–20.
Ifenthaler, D., & Yau, J. Y.-K. (2020). Utilising Learning Analytics to Support Study Success in Higher Education: A Systematic Review. Educational Technology Research and Development, 68, 1961–1990. Https://Doi.Org/10.1007/S11423-020-09788-W
Kopp, M., Gröblinger, O., & Adams, S. (2019). Five Common Assumptions that Prevent Digital Transformation at Higher Education Institutions. INTED2019 Proceedings, 1448–1457. Https://Doi.Org/10.21125/Inted.2019.0442
Ophir, E., Nass, C., & Wagner, A. D. (2009). Cognitive Control in Media Multitaskers. Proceedings of the National Academy of Sciences, 106(37), 15583–15587. Https://Doi.Org/10.1073/Pnas.0903620106
Prensky, M. (2001). Digital Natives, Digital Immigrants. On the Horizon, 9(5), 1–6.
Selwyn, N. (2023). Education and Technology: Key Issues and Debates (3rd Ed.). Bloomsbury Academic.
Siemens, G. (2013). Learning Analytics: The Emergence of A Discipline. American Behavioral Scientist, 57(10), 1380–1400. Https://Doi.Org/10.1177/0002764213498851
Sweller, J. (2011). Cognitive Load Theory. Psychology of Learning and Motivation, 55, 37–76. Https://Doi.Org/10.1016/B978-0-12-387691-1.00002-8
Turner, A. (2015). Generation Z: Technology and Social Interest. The Journal of Individual Psychology, 71(2), 103–113.
Vesin, B., Mangaroska, K., & Giannakos, M. (2018). Learning in Smart Environments: User-Centered Design and Analytics of an Adaptive Learning System. Smart Learning Environments, 5(24), 1–24. Https://Doi.Org/Https://Doi.Org/10.1186/S40561-018-0071-0
Vial, G. (2019). Understanding Digital Transformation: A Review and Research Agenda. The Journal of Strategic Information Systems, 28(2), 118–144. Https://Doi.Org/10.1016/J.Jsis.2019.01.003
Williamson, B., & Eynon, R. (2020). Historical Threads, Missing Links, and Future Directions in AI in Education. Learning, Media and Technology, 45(3), 223–235. Https://Doi.Org/10.1080/17439884.2020.1798995
Zimmerman, B. J. (2002). Becoming A Self-Regulated Learner: An Overview. Theory into Practice, 41(2), 64–70. Https://Doi.Org/10.1207/S15430421tip4102_2
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