A bibliometric perspective of learning analytics research landscape. Issue 10 (2nd November 2018)

• Record Type: Journal Article
• Authors: Waheed, Hajra; Hassan, Saeed-Ul; Aljohani, Naif Radi; Wasif, Muhammad
• Is Part Of: Behaviour & information technology. Volume 37:Issue 10/11(2018)
• Page Start: 941
• Page End: 957
• Publication Date: 2018-11-02
• Subjects: Learning analytics -- academic analytics -- educational analytics -- decision-making -- bibliometrics; Electronic data processing -- Periodicals; Human engineering -- Periodicals; Information technology -- Periodicals; 303.4833
• DOI: 10.1080/0144929X.2018.1467967
• Languages: English
• ISSNs: 0144-929X

Abstract

ABSTRACT: Learning analytics is an emerging field of research, motivated by the wide spectrum of the available educational information that can be analysed to provide a data-driven decision about various learning problems. This study intends to examine the research landscape of learning analytics to deliver a comprehensive understanding of the research activities in this multidisciplinary field, using scientific literature from the Scopus database. An array of state-of-the-art bibliometric indices is deployed on 2811 procured publication datasets: publication counts, citation counts, co-authorship patterns, citation networks and term co-occurrence. The results indicate that the field of learning analytics appears to have been instantiated around 2011; thus, before this time period no significant research activity can be observed. The temporal evolution indicates that the terms 'students', 'teachers', 'higher education institutions' and 'learning process' appear to be the major components of the field. More recent trends in the field are the tools that tap into Big Data analytics and data mining techniques for more rational data-driven decision-making services. A future direction research depicts a need to integrate learning analytics research with multidisciplinary smart education and smart library services. The vision towards smart city research requires a meta-level of smart learning analytics value integration and policy-making.