Transforming Curriculum Design with AI Learning Analytics in the University Context

Abstract

This article examines the potential of AI-based learning analytics to revolutionize adaptive curricula in higher education institutions. Drawing on the synthesis of existing evidence, the study assesses the ability of artificial intelligence to adapt to the individual student through data-driven instructional approaches. It examines key areas of ethics that include data privacy, algorithmic bias, and providing access to the data-driven instructional approaches. It records the preparedness of the institution and teachers. Despite the phenomenal potential of AI integration to enable inclusive and adaptive spaces of learning, the study identifies the need for careful deployment fueled by ethics and instructional fit. The results inspire balanced practice in AI adoption that guarantees that the human aspects of instruction are retained as the data analysis strength of AI comes into play.

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