TY - JOUR
T1 - The Components of Data Governance Framework for MOOC Providers in Indonesia
AU - Chandra, Yakob Utama
AU - Prabowo, Harjanto
AU - Gaol, Ford Lumban
AU - Purwandari, Betty
N1 - Publisher Copyright:
© 2024 Yakob Utama Chandra, Harjanto Prabowo, Ford Lumban Gaol and Betty Purwandari. This open-access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.
PY - 2024
Y1 - 2024
N2 - The COVID-19 pandemic had a universal and synchronous impact on all countries globally, leading to the implementation of the social distancing policy that mandated all activities take place within one’s own house. One of the implementations is distance education. Since the pandemic, e-learning, which is the dominant use of information technology in the education sector, has gained widespread recognition and acceptance as a mainstream concept in contemporary society. An illustration of this is the growth of the Massive Open Online Course (MOOC), which has attracted the attention of both public and private universities, prompting them to adopt its implementation. The rise of MOOCs can be ascribed to the internet’s ability to provide a more dynamic and flexible learning environment in comparison to traditional methods. The pandemic coincided with the establishment of digital campuses in schools and universities in recent decades. However, one important characteristic of these digital campuses is that they prioritize processes but overlook data and lack standards. Therefore, this study aims to identify important data governance components for MOOC providers in Indonesia from various past publications to construct a data governance framework. By examining the initial topic, the fundamental elements of data governance were ascertained. This study employed the Systematic Literature Review (SLR) methodology to address the research issue. The results derived from the SLR led to the initial derivation of six main components and 128 sub-components. Subsequently, interviews were carried out with 10 specialists representing 8 MOOC providers. The interview data were subsequently used to calculate the outcomes of the components using the fuzzy Delphi method. Based on statistical computation, six components, and 112 sub-components were deemed genuine and accepted by the eight MOOC providers in Indonesia. The subsequent phase of this study aims to construct a data governance system specifically tailored for MOOC providers in Indonesia.
AB - The COVID-19 pandemic had a universal and synchronous impact on all countries globally, leading to the implementation of the social distancing policy that mandated all activities take place within one’s own house. One of the implementations is distance education. Since the pandemic, e-learning, which is the dominant use of information technology in the education sector, has gained widespread recognition and acceptance as a mainstream concept in contemporary society. An illustration of this is the growth of the Massive Open Online Course (MOOC), which has attracted the attention of both public and private universities, prompting them to adopt its implementation. The rise of MOOCs can be ascribed to the internet’s ability to provide a more dynamic and flexible learning environment in comparison to traditional methods. The pandemic coincided with the establishment of digital campuses in schools and universities in recent decades. However, one important characteristic of these digital campuses is that they prioritize processes but overlook data and lack standards. Therefore, this study aims to identify important data governance components for MOOC providers in Indonesia from various past publications to construct a data governance framework. By examining the initial topic, the fundamental elements of data governance were ascertained. This study employed the Systematic Literature Review (SLR) methodology to address the research issue. The results derived from the SLR led to the initial derivation of six main components and 128 sub-components. Subsequently, interviews were carried out with 10 specialists representing 8 MOOC providers. The interview data were subsequently used to calculate the outcomes of the components using the fuzzy Delphi method. Based on statistical computation, six components, and 112 sub-components were deemed genuine and accepted by the eight MOOC providers in Indonesia. The subsequent phase of this study aims to construct a data governance system specifically tailored for MOOC providers in Indonesia.
KW - Components
KW - Data
KW - Governance
KW - MOOC
KW - Systematic Literature Review
UR - http://www.scopus.com/inward/record.url?scp=85209872013&partnerID=8YFLogxK
U2 - 10.3844/jcssp.2024.1636.1656
DO - 10.3844/jcssp.2024.1636.1656
M3 - Article
AN - SCOPUS:85209872013
SN - 1549-3636
VL - 20
SP - 1636
EP - 1656
JO - Journal of Computer Science
JF - Journal of Computer Science
IS - 12
ER -