Metaknowledge

Metaknowledge, or meta-knowledge, is knowledge about knowledge. It concerns the nature, sources, scope, and reliability of what is known, as well as awareness of what one does not know and how to obtain information or verify its validity. It can include judgments about credibility, sufficiency of evidence, and the appropriate use of different knowledge domains.

In relation to metacognition, metaknowledge is a component that focuses specifically on knowledge issues rather than cognitive processes. It can be explicit, such as declarative statements about what one knows and does not know, or tacit, embedded in judgments and decisions without conscious articulation. Metaknowledge also covers conditional aspects, such as knowing when to seek additional information or when a given approach is likely to be unreliable.

In educational settings, metaknowledge supports self-regulated learning. Learners use it to assess task demands, judge the accuracy of their knowledge, select study strategies, allocate time, and decide when to seek help. Developing metaknowledge can improve information literacy and critical thinking by promoting better evaluation of sources and evidence.

In information science and artificial intelligence, metaknowledge refers to knowledge about models, data, and uncertainty. This includes awareness of model limitations, data quality, and the reliability of conclusions. Systems may encode metaknowledge to calibrate confidence, manage risk, and improve interaction with users by transparently communicating what is known and what remains uncertain.

Measurement of metaknowledge often involves examining calibration between predicted confidence and actual outcomes, as well as metacognitive accuracy and efficiency in applying knowledge.