Opportunities and challenges for big data analytics in US higher education: A conceptual model for implementation. Issue 3 (June 2018)

• Record Type: Journal Article
• Authors: Attaran, Mohsen; Stark, John; Stotler, Derek
• Is Part Of: Industry & higher education. Volume 32:Issue 3(2018)
• Page Start: 169
• Page End: 182
• Publication Date: 2018-06
• Subjects: Adaptive learning -- big data -- enrolment management -- predictive analytics -- student performance management -- targeted student advising; Business and education -- Periodicals; University cooperation -- Periodicals; 378.104
• DOI: 10.1177/0950422218770937
• Languages: English
• ISSNs: 0950-4222

Abstract

Business leaders around the world are using emerging technologies to capitalize on data, to create business value and to compete effectively in a digitally driven world. They rely on data analytics to accelerate time to insight and to gain a better understanding of their customers' needs and wants. However, big data and data analytics solutions in higher education are new topics. There has been limited progress in accumulating the extremely rich data that flow through higher education systems for the purpose of acquiring usable information for students, instructors, administrators and the public. The key objective of this article is to propose a conceptual model for the successful implementation of analytics in higher education. The article also examines some of the potential benefits of big data and analytics as applied to the world of higher education and explores implementation challenges that can be expected. Furthermore, the study reviews key attributes of successful analytics platforms and illustrates some of the routes that might be taken to implement these technologies in education. Finally, it highlights the successful implementation of analytics solutions in several universities.