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A Computerized Functional Skills Assessment and Training Program Targeting Technology Based Everyday Functional Skills
Published on: February 13, 2020
The Experience of Learners Taking Objective Structured Assessments of Technical Skills (OSATS) Without Task Time
Stuart M Ellis1,2, Rachel M Williams2
1Assistant Teaching Professor in Dental Education, Professional and Continuing Education, University of Cambridge, Cambridge, UK; Director, Cambridge Academy of Dental Implantology, Cambridge, UK.
Abstract:
This article reports a qualitative exploration of learners' experiences of completing an Objective Structured Assessment of Technical Skills (OSATS) examination in preclinical dental implantology in which no time limits were imposed on the assessed tasks. Data from semi-structured interviews were analysed using Reflexive Thematic Analysis to identify patterns of meaning within participants' experiences. Participants frequently perceived the preclinical OSATS as a predictor of future professional practice, with its inherent time pressures, rather than as an assessment of attainment of the preclinical programme's Intended Learning Outcomes (ILOs). Understandings of surgical competence varied, with operative speed often perceived as an indicator of technical ability. Learners experiencing higher levels of examination anxiety reported the greatest perceived benefit from removing task time limits, as this reduced the attention directed towards monitoring the remaining time. However, in the unlimited-time OSATS, this "time focus" was frequently replaced by a "peer focus", with participants expressing anxiety about being perceived by others as slower and, consequently, less competent operators. These findings highlight the importance of ensuring that learners understand the ILOs of preclinical training and recognise that OSATS are designed to assess attainment of these outcomes rather than predict future professional performance. The influence of perceived peer pressure during open-group OSATS examinations may be reduced by using partitions between learners to limit inter-learner visualisation.
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