Data-Driven Adaptive Learning Management: A Decision-Making Model

Author(s)	Prof. Dr. Semen M. Levin
Country	Russia
Abstract	Adaptive learning has gained broad traction in higher education, yet its practical impact remains uneven. This paper argues that the root cause is conceptual rather than technological: adaptive learning continues to be treated as a tool for individual-level personalisation, whilst its role as a process embedded within educational management is largely overlooked. To bridge this gap, the study proposes a model of adaptive educational control that reconceptualises adaptive learning as a multi-level feedback system. The model integrates data collection, analysis, decision-making, intervention, and evaluation across four nested levels – learner, instructor, course, and – а institution. By introducing an explicit decision-making layer and incorporating evaluation-driven redesign, the proposed framework transforms adaptive learning from a predictive pipeline into a coordinated system of data-informed educational governance.
Keywords	adaptive learning, educational systems management, decision-making, decision support systems, learning analytics, socio-technical systems, higher education, control loop, data analytics, digital education
Field	Computer > Data / Information
Published In	Volume 8, Issue 3, May-June 2026
Published On	2026-05-05
DOI	https://doi.org/10.36948/ijfmr.2026.v08i03.76569

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