A category of technologies that use cognitive computing, natural language processing, and machine learning to enable people and machines to interact more naturally to extend and magnify human expertise and cognition.

Cognitive systems can analyze structured and unstructured data from diverse information sources. At the same time, these systems are able to take context into account and consider conflicting information, which enables them to formulate optimal solutions to questions and problems. These capabilities are ideal for optimizing the promise of adaptive learning.

Cognitive systems can be exposed to information related to each individual student. This would be information accumulated over a lifetime and presented in the form of structured as well as unstructured data. School reports and class attendance records would be examples of structured data. Class notes, essays, emails, photos of craft and other activities as well as audio files are examples of unstructured data.

Cognitive systems can synthesize all this information and develop teaching strategies and teaching materials ideally suited to each individual student. IBM has developed such a system, called Watson. Watson can take all the data about each student and infer meaning from it. It can then adjust its recommendations based on what it has learned.