Abstract

The study shows the existence of a broad conformity between Whitehead’s organismic cosmology and the contemporary theory of complex systems at a relevant level of abstraction. One of the most promising directions of educational transformation in the age of big data and artificial intelligence – personalized learning – is conceived as a system of systems and reveals its close congruence with a number of basic Whiteheadian concepts. A new functional structure of personalized learning systems is proposed, including all the core elements of a full learning sequence. A multiobjective optimization problem, which is subject to strong constraints, uncertain outcomes, and continued development, is under consideration. It is argued that many of Whitehead’s concepts can be used constructively in designing and implementing advanced personalized learning systems after being adapted and expanded and account for the requirements of emerging big data and artificial intelligence research. Special attention is paid to the main factors that determine the multi-modality of personalized learning – learning styles, contexts, and didactic variability. The effecttiveness of personalized learning is a data-driven problem.