The coronavirus (COVID-19) pandemic has been a global crisis, affecting many areas of society, including higher education, which has not been immune to its effects. This study, therefore, examines COVID-19 from the perspective of higher education, applying data mining and analytics approaches, i.e., t-SNE analysis, text-mining, and social network…

This paper presents a review of peer-reviewed publications (2007-2017) on digital open educational practices (OEPs). It explores trends and patterns in this emerging area of study by examining paper abstracts and bibliographic data indexed in the Scopus database using a combination of descriptive statistics, text mining, social network analysis,…

The purpose of this research is to examine the research that has been done on MOOCs by applying data mining and analytic approaches and to depict the current state of MOOC research. The text mining revealed four broad themes: (I) MOOCs as a mainstreaming learning model in HE, (II) motivation and engagement issues in MOOCs, (III) assessment issues…

Since the first offering of a Massive Open Online Course (MOOC) in 2008, the body of literature on this new phenomenon of open learning has grown tremendously. In this regard, this article intends to identify and map patterns in research on MOOCs by reviewing 362 empirical articles published in peer-reviewed journals from 2008 to 2015. For the…

The blending learning model, a combination of onsite and online learning modalities formulated by relevant pedagogies, modalities, and technologies, offers learning experiences that involve the different factors shaping each modality, such as time, space, path, and pace, through sequential or parallel designs. In its relatively short history, this…