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Adaptive learning is a technique to use data-driven instruction to adjust and tailor learning experiences to meet the individual needs of each student. Adaptive learning systems can track data such as student progress, engagement, and performance, and use the data to provide personalized learning experiences.

Adaptive learning can be defined as a teaching process that adapts automatically to each student or learner, meaning that the courses, the assessments, or the teaching resources are used to tailor the course to each individual’s progress, abilities, and even choices. The goal is of course to allow each individual to learn efficiently and to optimize the learning courses.

Adaptive learning is based on automated mechanisms that can only be enabled by strong digital learning tools. We can distinguish two components of adaptive learning: diagnosis, and the consequences. The diagnosis provides the information—"the data"—on which the consequences and its personalization are based for the learner.