Key Elements that Influence Adaptive Learning Through Data Analytics

Abstract

Despite the obvious benefits and growing interest in the use of adaptive learning in teaching, its widespread implementation presents some challenges such as data privacy and the lack of information in the literature on how different variables affect adaptive learning. The purpose of this research was to develop a new way of exploring the elements that affect adaptive learning through data analytics. It was a mixed research, where a literature review and a structural analysis were carried out. A panel of twelve experts allowed to reveal important findings. The results underline the potential of adaptive learning to revolutionize education by addressing the particular needs of each student, through variables such as learning style, predictive models and analysis of learning patterns, among others. It is concluded, among other aspects, that the implementation of adaptive learning remains a challenge, but considering its possible advantages, investment in research on how to increase its adoption rate by managing the identified variables will bear fruit in student, institutional, and economic performance.