Cognigraphic (cognitive + graphics) data consist of user information on cognitive and learning abilities, preferences, intelligence, style, and actual knowledge, comprising a personalized dynamic map in the form of a graph.
The term “cognigraphic data” was first used in a text describing the AIP learning and evaluation algorithm, presented as a patented technology in patent “System, method, and computer readable medium for developing proficiency of a user in a topic”. In the AIP learning and evaluation algorithm, cognigraphic data are used as a dynamic set of characteristics that are continuously updated based on user activity data. Algorithms use this cognigraphic data to personalize learning materials for a specific user profile by selecting the appropriate level, nature of content, type of content, and method of information transfer.
Cognigraphic data may include:
- Categorical indications (users’ psychological types, comprehension profile, etc.) determined through testing or through other methods;
- A data set indicating the user’s experience, development history, previously acquired knowledge and skills, and other parameters that are useful for the profiling methods and algorithms that adapt content to the learner’s characteristics.