Analysis of Drivers of Digital Learning in COVID-19 and Post-COVID-19 Scenario Using an ISM Approach

Agrawal, Rohit; Wankhede, Vishal Ashok; Nair, Rashmi S.

Learning through Internet is becoming necessary for easy understanding of complex problems and knowledge sharing process. A new pedagogy is being demanded in the teaching process which includes digital platforms for better understanding. Moreover, software and hardware have been developed for ease of access to the materials and smooth learning. The COVID-19 pandemic brought various challenges in livelihood of human life. One of these challenges is teaching and learning process. Although teaching and learning include usage of digital media, there exist a need to digitalize the education system. In this regard, this study aimed to analyse the drivers of digital learning in COVID-19 and post-COVID-19 scenario. Sixteen drivers pertaining to digital learning have been considered for analysis. Interpretive structural modelling (ISM) approach has been used to analyse drivers of digital learning and to develop a structural model. The developed structural model was further validated using MICMAC analysis. Results reveal that low Internet cost and government supports are the two prominent drivers of digital learning. The implementation of developed ISM model would create smooth learning environment in COVID-19 and motivates for innovation in post-COVID-19 scenario.