Big and open linked data analytics: a study on changing roles and skills in the higher educational process

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F20%3A39916068" target="_blank" >RIV/00216275:25410/20:39916068 - isvavai.cz</a>

Result on the web

<a href="https://educationaltechnologyjournal.springeropen.com/articles/10.1186/s41239-020-00208-z" target="_blank" >https://educationaltechnologyjournal.springeropen.com/articles/10.1186/s41239-020-00208-z</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1186/s41239-020-00208-z" target="_blank" >10.1186/s41239-020-00208-z</a>

Result language

angličtina

Original language name

Big and open linked data analytics: a study on changing roles and skills in the higher educational process

Original language description

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&apos; 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.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

50302 - Education, special (to gifted persons, those with learning disabilities)

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

International Journal of Educational Technology in Higher Education

ISSN

2365-9440

e-ISSN

—

Volume of the periodical

17

Issue of the periodical within the volume

1

Country of publishing house

CH - SWITZERLAND

Number of pages

30

Pages from-to

28

UT code for WoS article

000562112800001

EID of the result in the Scopus database

2-s2.0-85089556920