Higher education systems (HES) have become increasingly absorbed in applying big data analytics due to competition as well as economic pressures. Many studies have been conducted that applied big data analytics in HES; however, a systematic review (SR) of the research is scarce. In this paper, the authors conducted a systematic mapping study to address this deficiency. The qualitative and quantitative analysis of the mapping study resulted in highlighting the research progression over the last decade, and identification of three major themes, 12 subthemes, 10 motivation factors, 10 major challenges, three categories of tools and support techniques, and 16 models for applying big data analytics in higher education. This result contributes to the ongoing research on applying big data analytics in HES. It provides a better understanding of the level of contribution to research as well as identifies gaps for future research direction.
Systematic Mapping Study on Process Mining in Agile Software Development
