| Summary: | Confidence-based assessment (CBA) is a technique designed to evaluate an individual’s degree of confidence or expectation regarding their response to discern their true level of knowledge. In this methodology, individuals assign confidence scores to their answers, indicating their level of certainty about the correctness of their choices. This approach enhances understanding an individual’s abilities or comprehension by distinguishing between correct responses with high confidence and those with low confidence. Consequently, evaluators gain a more comprehensive understanding of an individual’s competence by examining their cognitive processes and self-awareness. Despite its potential, there is a lack of systematic reviews focusing on enhancing CBA. This study addresses this gap by conducting a systematic literature review (SLR) on improving CBA methodologies. The present study follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, systematically analysing 11 articles published between 2019 and 2024. These articles were selected from three primary databases—Scopus, Web of Science, and ScienceDirect—and one supplementary database, Google Scholar. The review of these studies identified four major themes: sector, purpose, algorithm, and methods used. The findings of this SLR provide valuable insights into the current state of CBA research and suggest directions for future studies. In conclusion, this research offers significant benefits for scholars in the CBA field, providing a reference for enhancing the application and understanding of CBA. © Little Lion Scientific.
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