Graduating dental practitioners requires the mastery of a number of skills and a significant body of basic information. Dental education is a complex combination of didactic and physical skill learning processes. It is necessary to develop appropriate tools to measure student clinical performance to allow the provision of interventional strategies at the right time targeted at the right individuals. In this study, an approach to early intervention surveillance strategies was developed that is cost-effective, transparent, and robust based on mathematical predictions of student clinical achievements. Using a cohort of students’ clinical activity profile, a polynomial pair was developed that represents the predictive function of low and high achieving students. This polynomial pair can then be applied to students to predict their final achievement based on their current status. The polynomial methodology is adaptable to local variation such as access to clinical facilities. The early intervention surveillance strategy developed in this study provides a simple, cost-effective, predictive risk assessment system that relies on data sets already collected in most dental schools and can be completed without the need for significant human intervention. The mathematical approach allows the focusing of educational support towards students that require the assistance, thus augmenting the better use of resources.
|Journal||Journal of Dental Education|
|Publication status||Published - 2005|