Unlocking the Potential of Learning Analytics in Digital Education: from Passive Reporting to Active Intervention

Learning analytics (LA) has emerged as a powerful approach to improving student success, personalizing learning, and guiding institutional decision-making. Despite the availability of rich learner data from learning management systems (LMS) and digital platforms, the use of LA remains underdeveloped in higher education. Most institutions confine analytics to descriptive reporting - tracking logins, task completion, and grades, without advancing toward predictive, personalized, or intervention-oriented applications. This underutilization results in missed opportunities to identify at-risk learners early, support adaptive pathways, and continuously refine curriculum design. This concept paper adopts a qualitative and conceptual research design, drawing on recent literature and theoretical models such as the Technology Acceptance Model (TAM) and Diffusion of Innovations (DOI), to propose the Integrated Learning Analytics Adoption Framework (ILAAF). The framework emphasizes five strategic pillars - vision and governance, capacity building, technology integration, pedagogical alignment, and continuous evaluation, supported by an operational workflow that transforms raw data into actionable insights. The findings highlight that adopting ILAAF can shift LA from passive reporting to active, learner-centered practice. The paper recommends strategic institutional adoption, capacity development, and ethical governance to ensure LA becomes a dynamic driver of engagement, equity, and long-term student success.

Learning Analytics, Educational Technology, Personalized Learning

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