Big and open linked data analytics: a study on changing roles and skills in the higher educational process - Lněnička, Martin; Kopáčková, Hana; Máchová, Renáta; Komárková, Jitka (Springer Nature Switzerland AG, 2020)
The concept of openness and information sharing (linking) together with increasing amounts of data available significantly affect the current educational system. Institutions as well as other stakeholders are facing challenges how to successfully deal with them and potentially profit from them. In this regard, this paper explores opportunities of big and open linked data analytics in the educational process intended to develop the new set of skills. A comprehensive literature review resulted in a framework of relevant skills, namely soft, hard, and data analytics skills. Their importance was evaluated using a Delphi method. In order to determine the relationships between involved stakeholders, their roles and requirements, a stakeholder theory is utilized. It resulted in the identification of current and emerging roles of stakeholders in the data analytics ecosystem. A structural classification of stakeholders' influences and impacts then represents a necessary background for establishing strategies for the development of the right skills needed to gain the value from these data. This paper provides a comprehensive view on big and open linked data analytics in the educational context, defines and interlinks data-related with current roles as well as the skills required to perform data analytics.
Analytika big a open linked dat: studie o měnících se rolích a dovednostech v procesu vysokoškolského vzdělávání
Keywords: analytics; higher education; skills; Delphi method; stakeholder theory; framework; analytika; vysokoškolské vzdělávání; dovednosti; delfská metoda; teorie zúčastněných stran; rámec