Factors Determining Digital Learning Ecosystem Smartness in Schools

Eka Jeladze, Kai Pata, James Sunney Quaicoe
pp. 32 – 55, download


This paper discusses the factors that determine school’s digital learning ecosystem smartness. A dataset was collected from 52 schools in Ghana, Georgia and Estonia. Qualitative school observations and interviews were transformed to the quantitative categories and compound variables using the grid-based approach. We found three distinctive digital learning ecosystem types that described some possible developmental stages in the ecosystem. Discriminant analysis revealed two functions. Most dominant compound variables in the first function were the top-down external provision of digital resources and ICT incentives. The second function characterizes with bottom-up proactiveness of the schools. Path modelling between the compound variables revealed the growing complexity in connectivity among the mediating, transformative and flow components, that determines the smartness of learning ecosystem. Such interconnected components form specific fitness niches which have been co-created in organizations through collective effort, making school ecosystem responsive to the socio-technical regime and externally provided opportunities in the countries.

Keywords: digital learning ecosystem, school

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