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Title: Assessment of competence in dentistry : the expectations, perceptions, and predictions
Author: Vahid Roudsari, Reza
ISNI:       0000 0004 7226 3416
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2018
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Introduction: Competence has been a term subject to many interpretations over the years. This discrepancy in agreement is not due to the clash of minds but mostly the fruit of differences in expectations and legal requirements of local healthcare systems. As a result, the assessment of competence has been subject to dynamic changes with abundance of literature published to address its properties from different angles. This research project is designed to explore a number of unknowns: firstly, we aim to explore what it is meant by competence and compare it to how it is defined by the regulators. Once this is established, such expectations are to be compared to the expectations of the Educational Supervisors (ESs): the trainers who are in charge of training the newly qualified dentists. The next goal of this project is to shed light on how students perceive competence and explore the assessment methods that reflect such competencies best. Once known, these assessment methods will be explored in the national level to understand how they are implemented. The project also aims to explore if such assessment methods could be improved and finally, to examine if new assessment methods can be introduced to the field of medical and dental education with significant benefits and advantages. Methodology: A mixed-method approach was chosen, consisted of qualitative, quantitative and descriptive statistics. Results: Profile of a competent newly qualified dentist as described by the regulatory bodies, ESs and students was discussed. The most reflective assessment methods to illustrate students' competencies were identified and their use at national level explored. We looked at the bench marking of the OSCEs and where the line of competence is drawn, and finally, we developed a new mathematical model that can predict competence after observing a number of clinical encounters. Conclusion: Several conclusions and recommendations were drawn and discussed at their relevant chapter.
Supervisor: Byrne-Davis, Lucie Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Psychometric ; Assessment ; Clinical competence ; Dental education