Proceedings of The 3rd International Conference on Academic Research in Science, Technology and Engineering
COVID19 and e-learning: the Adaptive Lockdown Prototype
Agostino Marengo, Alessandro Pagano
It was March 2020 in Italy, and the nation with all the world is facing the COVID-19 pandemic. Most countries were in lockdown, being asked to “Stay home. Stay safe”. Lockdown has closed schools and universities in most countries. UNESCO estimates that over 90% of the world’s students are not currently attending school in response to the pandemic, with over 1.5 billion learners affected (UNESCO, 2020). The shifting to online learning was a rapid process, and it was wideout of need. This paper will describe the development and implementation of an Adaptive System Prototype, called Adaptive Lockdown Prototype, to face the lack of e-learning innovation during the pandemic lockdown, to face the students’ and teachers’ necessities, managing an automated and customized learning experience. There is much literature about the pure hypothesis of personalized learning environments, but few are articles about the development of those environments. The research team’s goal was to develop an adaptive learning plugin implemented on mostly used, Open Source, Learning Management Systems. The primary purpose was to maximize a students’ performance during the lockdown, allowing them to manage a customized learning experience. This paper describes the main steps for the implementation of the Adaptive Lockdown Prototype.
Keywords: Adaptive learning, e-learning, Personalized Learning Environments, LMS, Open Source.