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Confidence-based learning


Confidence-Based Learning, CBL, measures the correctness of a learner's knowledge and confidence in that knowledge. It is designed to increase retention and minimize the effects of guessing, which can skew the results of traditional single-score assessments. It distinguishes between what individuals think and actually know.

The measurement allows creating a customized learning plan for each learner. The process, similar to quality improvement processes such as Six Sigma, continues until the learner achieves total mastery – defined as validly achieving confidence and correctness for 100% of the content twice in a row. Mastery leads to putting the knowledge into practice.

The Confidence-Based Learning Methodology is a culmination of more than 70 years of academic, commercial, and governmental research into the connection between confidence, correctness, retention, and learning. The first academic paper on the subject was written in 1932 and asserted that measuring confidence and knowledge was a better predictor of performance than measuring knowledge alone, which can be prone to guesswork.

Extensive research and technological advances ultimately led to further development of the methodology in measuring confidence and correctness.

The framework for Confidence-Based Learning Methodology is based primarily around the research of Darwin Hunt, Dieudonne LeClerq, Emir Shuford, and James E. Bruno. Significant advances in the knowledge and confidence connection were made by all of four researchers, but Bruno brought their collective work together in a methodology that made it possible for knowledge and confidence to be effectively measured.

Fundamental research that helped form the framework for CBL includes:

Hunt conducted significant research with the US Navy and focused on the dimensions of knowledge, linking confidence and correctness with retention. His process involved a two-step approach – (1) answer the question (objective measurement of correctness), and then state your confidence in your answer (subjective confidence statement). According to Hunt, research shows that the retention of newly learned material is systematically related to "how sure" people are about the correctness of their answers when they learn it.

LeClerq focused on item bank testing - the process of using a pool of questions, from which questions are drawn and randomly delivered to learners to see how well they answer questions without pattern recognition or order influencing the process. The result is higher quality knowledge and information. The outcome was a report on the quality of information/knowledge that shows where misinformation exists.

Shuford developed a measurement algorithm that focused on the determinations of the reliability of someone's knowledge and how a learners' knowledge reliability was improved or diminished based on their level of doubt or confidence in it.


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