A targeted e-learning approach for keeping universities open during the COVID-19 pandemic while reducing student physical interactions

In their new paper, Sing Chen Yeo, Clin K. Y. Lai, Jacinda Tan and Joshua J. Gooley demonstrate that, instead of fully closing campuses, converting a small number of classes to e-learning can decrease the potential for disease transmission while minimising disruption to university operations. Analysing 24 million student connections to the Wi-Fi network on campus during the COVID-19 pandemic, the research team found that the gathering of students on campus was significantly reduced (by 30%) after the transition to e-learning for classes with >50 students. It dropped by an additional 25% after e-learning was implemented for classes with >25 students. In contrast, students with in-class learning were detected at nearly twice the rate (about 60–80%) as students with e-learning only or no class. Such a targeted e-learning approach could then be used to keep universities open while reducing student physical interactions when necessary. This study, which was possible thanks to the ALSET Data Lake, also illustrates the capacities of applied data analytics to inform university policies.

 

Yeo SC, Lai CKY, Tan J, Gooley JJ (2021) A targeted e-learning approach for keeping universities open during the COVID-19 pandemic while reducing student physical interactions. PLoS ONE 16(4): e0249839. https://doi.org/10.1371/journal.pone.0249839