Learning Analytics Methods, Benefits, and Challenges in Higher Education: A Systematic Literature Review

Abstract

Higher education for the 21st century continues to promote discoveries in the field through learning analytics (LA). The problem is that the rapid embrace of of LA diverts educators' attention from clearly identifying requirements and implications of using LA in higher education. LA is a promising emerging field, yet higher education stakeholders need to become further familiar with issues related to the use of LA in higher education. Few studies have synthesized previous studies to provide an overview of LA issues in higher education. To address the problem, a systemic literature review was conducted to provide an overview of methods, benefits, and challenges of using LA in higher education. The literature review revealed that LA uses various methods including visual data analysis techniques, social network analysis, semantic, and educational data mining including prediction, clustering, relationship mining, discovery with models, and separation of data for human judgment to analyze data. The benefits include targeted course offerings, curriculum development, student learning outcomes, behavior and process, personalized learning, improved instructor performance, post-educational employment opportunities, and enhanced research in the field of education. Challenges include issues related to data tracking, collection, evaluation, analysis; lack of connection to learning sciences; optimizing learning environments, and ethical and privacy issues. Such a comprehensive overview provides an integrative report for faculty, course developers, and administrators about methods, benefits, and challenges of LA so that they may apply LA more effectively to improve teaching and learning in higher education.

Social Learning Analytics in Higher Education. An experience at the Primary Education stage

“…As stated by Nunn, Avella, Kanai and Kebritchi (2016), the need is highlighted for a better understanding of what is being realised in the networks in order to study the data and optimize the results obtained. These can then be used to enhance teaching and learning.…”

Use of Learning Analytics Data in Health Care–Related Educational Disciplines: Systematic Review (Preprint)

“…While a universal definition of learning analytics has not yet reached a consensus, there is general agreement that it is a relatively new [4] and emerging [5,6] tool in academic research which can be used to track and store students' online learning activities [5,7]. Higher education institutions collect a vast amount of information from students regarding their use of e-learning resources in the form of activity logs and other digital footprints such as time and date, student demographics, course enrolments, survey questionnaires, library usage, and academic grades [8].…”

Machine Learning Based On Big Data Extraction of Massive Educational Knowledge

“…These methods are useful for the creation of relevant knowledge owing to their bearing upon the initial massive data. Below, we present a comparative table of approaches to the learning analytics, proposed in the existing literature [30]: Table 1. Learning analytics methods.…”