VUCA Learning Environments Demand Complex Data and Knowledge Management

Leadership has increasingly become a major research focus in the corporate sector as well as in the higher education sector (HES). However, there is a lack of clear understanding of how leadership and potential features and benefits of Information and Communications Technology (ICT) interact together in the HES context and how to lead most effectively within our emerging volatile, uncertain, complex, and ambiguous (VUCA) learning environments. The intrinsic potential of the available educational datasets can be exploited using sophisticated data-analysis techniques such as automatic reasoning to find patterns and extract information and knowledge in order to enhance decision-making and deliver better learning resources to the users. Moreover, education information sharing and analysis in conjunction with non-traditional data sources (e.g., social media, web content, and linked data) can provide an important component to facilitating the development of the next generation of VUCA learning services, in particular, personalisation and inference reasoning. A conceptual chapter is presented for the purpose of analysing HES organization-environment relations. The theoretical umbrella adopted here is the linked data (LD) and semantic web (SW) theories -- a promising solution for the integration and exploitation of HES data about students, resources, courses, syllabi, and institutions. SW describes a new way to make resource content more meaningful to machines, whereas the meaning of data is provided using ontologies.The use of SW technologies as data representation formalism enables the creation of a common model, thus interconnecting a variety of heterogeneous data sources. Volatility, uncertainty, ambiguity, and complexity can be managed using technologies related to the representation of LD and SW.