The recent COVID-19 pandemic has presented challenges to post-secondary education, including that campuses have been closed, removing face-to-face instruction options. Meanwhile, this crisis has also presented unique opportunities to create a “tipping point” or conditions that foster innovative teaching practices. In light of such a “danger-opportunity,” the feasibility of introducing microlearning (ML), a technology-mediated teaching and learning (T&L) strategy, has recently been revisited by some institutions. ML offers learning opportunities through small bursts of training materials that learners can comprehend in a short time, according to their preferred schedule and location. Initially considered as “add-on” complementary online learning resources to provide learners with an active and more engaging learning experience through flexible learning modes, the possibility of an institution-wide implementation of ML has been further explored during the COVID-19 lockdown. This paper presents an exploratory case study examining two post-secondary education institutions’ ML introductions. Using the SAMR model as the lens, their approaches to adopting ML are examined through analysis of quantitative questionnaires and qualitative teacher reflections. Overall, ML appears to be a promising direction that may not only be able to help institutions survive, but possibly offer an enhanced teaching and learning experience, post-pandemic. However, its current implementations face many challenges, both practical and pedagogical, and their impacts have yet to achieve transformation. With the insights gained, some possible strategies for moving the adoption of ML to the next level are offered. Copyright © 2021 The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.
CitationWang, T., Towey, D., Ng, R. Y.‑K., & Gill, A. S. (2021). Towards post‑pandemic transformative teaching and learning: Case studies of microlearning implementations in two post-secondary educational institutions. SN Computer Science, 2(4). Retrieved from https://doi.org/10.1007/s42979-021-00663-z
- Microlearning (ML)
- Innovation implementation
- Education change
- COVID-19 outbreak