The added value of Learning Analytics in Higher Education

Abstract

Learning Analytics (LA) is a field of research and practice that uses data analysis to comprehend and optimize learning and the environment in which learning takes place. As an AI tool in higher education, LA is expected to improve student learning and support the academic community in teaching delivery, institutional management, long-term research and development, innovation, data-driven decision-making, and more. We have conducted a literature review to explore these issues and examine the added value of LA in higher education. We have focused on the key issues that educational institutions need to consider to get the most out of LA use. The findings of this review reveal that the proper use of the LA toolkit can enhance the development of an appropriate educational environment through the careful determination of ethics and policies that support the main institutional objective, and the study of opportunities, challenges, and trends in the sector. The key challenges of using AI tools like LA in Higher Education are data privacy and protection, data ownership, data heterogeneity, potential biases in AI algorithms, and the need for alignment of institutional strategies for LA with pedagogical approaches. The trends highlight the current advances in LA that give added value in higher education.

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