Bibliographic review of the impact of Learning Analytics in virtual environments of Higher Education

Abstract

Learning analytics (LA) is a form of data analysis in Learning Management Systems (LMS) that allows teachers, tutors, education specialists and online learning managers to find trends, students' online patterns and information associated with their learning processes. The fundamental goal of LA in virtual classrooms and online education is to enhance the learning experience and process. This paper aims to review the impact and some of the benefits achieved through the use of learning analytics in higher education institutions (HEIs) for students, teachers and managers. The search for relevant literature was conducted through online databases including Web of Science WOS, SCOPUS, Science Direct, IEEE, Emerald, Springer, ERIC and Association for Computing Machinery (ACM). The state of the art reveals that learning analytics provide a number of benefits for students, faculty, and HEI management. The benefits include prediction and identification of course objective fulfillment, curriculum development and improvement, determination of the best student learning outcomes, improved instructor performance, and tracking of student attrition and retention. It is recommended that higher education institutions adopt the use of learning analytics in their online teaching and learning.