Implementing Personalized Learning in Universities Classrooms: Lecturers’ Challenges and Perceptions

Agnes Herawati

doi:10.21512/humaniora.v14i2.8890

Authors

Agnes Herawati Bina Nusantara University

DOI:

https://doi.org/10.21512/humaniora.v14i2.8890

Keywords:

personalized learning, active learning, students’ motivations, lecturers’ challenges

Abstract

The research aimed to investigate the challenges faced by university lecturers and how they overcome them, as well as the perceptions towards the implementation of a personalized learning approach. Personalized learning was considered a teaching approach that emphasized how to achieve the learning objectives, students’ active learning, and self-regulated learning that could not be fully served in traditional classes. This approach focused on each student’s learning pace and their active participation in the learning process. In the long run, implementing personalized learning was hoped to develop students into responsible and lifelong learners. Although lecturers showed an excellent perception of the implementation of personalized learning, however, it was no doubt that conducting this approach brought some new experiences and challenges for the lecturers as well. Mixed method was applied in the research. The result shows the difference between personalized learning and traditional one in terms of time management, students’ responsibilities and motivations, and class interaction, and those become the most challenging matters faced by the lecturers. How lecturers make use of technology to realize better-personalized learning classes and other crucial things that are needed by the lecturers in implementing personalized learning are also presented.

Dimensions

Plum Analytics

Author Biography

Agnes Herawati, Bina Nusantara University

English Department - Bina Nusantara University

References

Akyuz, Y. (2020). Personalized learning in education. American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS), 69(1), 175-194.

Alamri, H., Lowell, V., Watson, W., & Watson, S. L. (2020). Using personalized learning as an instructional approach to motivate learners in online higher education: Learner self-determination and intrinsic motivation. Journal of Research on Technology in Education, 52(3), 322-352. https://doi.org/10.1080/15391523.2020.1728449.

Basilaia, G., & Kvavadze, D. (2020). Transition to online education in schools during a SARS-CoV-2 Coronavirus (COVID-19) pandemic in Georgia. Pedagogical Research, 5(4), 1-19. https://doi.org/10.29333/pr/7937.

Becker, S. A., Cummins, M., Davis, A., Freeman, A., Hall-Giesinger, C., & Ananthanarayanan, V. (2017). Horizon report: 2017 higher education edition. Retrieved from https://eric.ed.gov/?id=ED582134.

Brown, C. P., & Englehardt, J. (2017). A case study of how a sample of preservice lecturers made sense of incorporating iPads into their instruction with children. Journal of Early Childhood Teacher Education, 38(1), 19-38. https://doi.org/10.1080/10901027.2016.1274695.

Bulger, M. (2016). Personalized learning: The conversations we’re not having. Data & Society, 1-29.

Christodoulou, A., & Angeli, C. (2022). Adaptive learning techniques for a personalized educational software in developing lecturers’ technological pedagogical content knowledge. Frontiers in Education, 7, 1-14. https://doi.org/10.3389/feduc.2022.789397.

Dawadi, S., Shrestha, S., & Giri, R. A. (2021). Mixed-methods research: A discussion on its types, challenges, and criticisms. Journal of Practical Studies in Education, 2(2), 25-36. https://doi.org/10.46809/jpse.v2i2.20.

Hsieh, C. W., & Chen, S. Y. (2016). A cognitive style perspective to handheld devices: Customization vs. personalization. International Review of Research in Open and Distance Learning, 17(1), 1-22. https://doi.org/10.19173/irrodl.v17i1.2168.

Hwang, G. J., Xie, H., Wah, B. W., & Gašević, D. (2020). Vision, challenges, roles and research issues of Artificial Intelligence in Education. Computers and Education: Artificial Intelligence, 1, 1-5. https://doi.org/10.1016/j.caeai.2020.100001.

Lee, D., Huh, Y., Lin, C. Y., Reigeluth, C. M., & Lee, E. (2021). Differences in personalized learning practice and technology use in high- and low-performing learner-centered schools in the United States. Educational Technology Research and Development, 69(2), 1221-1245. https://doi.org/10.1007/s11423-021-09937-y.

LeGeros, L., Bishop, P., Netcoh, S., & Downes, J. (2022). Informing the implementation of personalized learning in the middle grades through a school-wide genius hour. RMLE Online, 45(1), 1-22. https://doi.org/10.1080/19404476.2022.2009707.

Luke, C., & Young, V. M. (2020). Integrating micro-credentials into professional approaches to supporting learning: Lessons from five districts. Retrieved from https://digitalpromise.dspacedirect.org/handle/20.500.12265/103.

Rollins, J. R. (2017). College and career ready through personalized learning: Business and industry perspective of the Don Tyson School of Innovation. ProQuest Dissertations and Theses. Retrieved from https://search.proquest.com/dissertations-theses/college-career-ready-through-personalized/docview/1972896596/se-2?accountid=41849.

Shemshack, A., & Spector, J. M. (2020). A systematic literature review of personalized learning terms. Smart Learning Environments, 7, 33. https://doi.org/10.1186/s40561-020-00140-9.

Spector, J. M. (2016). The potential of smart technologies for learning and instruction. International Journal of Smart Technology and Learning, 1(1), 21-32. https://doi.org/10.1504/ijsmarttl.2016.078163.

Sun, L., Tang, Y., & Zuo, W. (2020). Coronavirus pushes education online. Nature Materials, 19(6), 687. https://doi.org/10.1038/s41563-020-0678-8.

Walkington, C., & Bernacki, M. L. (2020). Appraising research on personalized learning: Definitions, theoretical alignment, advancements, and future directions. Journal of Research on Technology in Education, 52(3), 235-252. https://doi.org/10.1080/15391523.2020.1747757.