A framework for the drivers or enablers of digital learning - an interpretive structural modelling approach

Shreeharsha Mruthyunjaya Kulenur, Nagesh Parashivamurthy, Anand Gurumurthy and Thangamani Gurunathan

International Journal of Intelligent Enterprise, 2026, vol. 13, issue 3/4, 487-512

Abstract: The education sector has drastically changed since the 2019 coronavirus disease (COVID-19), as institutes and universities have incorporated digital technologies to overcome the interruptions in learning due to lockdowns imposed by governments in various countries. When normalcy returned, institutions continued to provide digital learning (DL), complementing conventional face-to-face learning. New edtech companies also emerged to meet the needs of individuals and organisations to upskill themselves or their employees. In this context, this paper attempts to understand the drivers or enablers that make an individual/learner opt for DL when conventional learning methods are also available. None of the papers has explored the relationship between them. Hence, interpretive structural modelling (ISM) is utilised to develop the hierarchical model of the drivers. The results reveal that, besides the learner's motivation, the awareness of using digital capabilities and the amount of technical support and service provided by the learning service providers are critical.

Keywords: learners; digital learning; DL; drivers; enablers; relationship; interpretive structural modelling; ISM. (search for similar items in EconPapers)
Date: 2026
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