Browsing by Author "Cilliers, Francois J."

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    A model of the pre-assessment learning effects of assessment is operational in an undergraduate clinical context
    (BioMed Central, 2012-03) Cilliers, Francois J.; Schuwirth, Lambert W. T.; Van der Vleuten, Cees P. M.
    Background No validated model exists to explain the learning effects of assessment, a problem when designing and researching assessment for learning. We recently developed a model explaining the pre-assessment learning effects of summative assessment in a theory teaching context. The challenge now is to validate this model. The purpose of this study was to explore whether the model was operational in a clinical context as a first step in this process. Methods Given the complexity of the model, we adopted a qualitative approach. Data from in-depth interviews with eighteen medical students were subject to content analysis. We utilised a code book developed previously using grounded theory. During analysis, we remained alert to data that might not conform to the coding framework and open to the possibility of deploying inductive coding. Ethical clearance and informed consent were obtained. Results The three components of the model i.e., assessment factors, mechanism factors and learning effects were all evident in the clinical context. Associations between these components could all be explained by the model. Interaction with preceptors was identified as a new subcomponent of assessment factors. The model could explain the interrelationships of the three facets of this subcomponent i.e., regular accountability, personal consequences and emotional valence of the learning environment, with previously described components of the model. Conclusions The model could be utilized to analyse and explain observations in an assessment context different to that from which it was derived. In the clinical setting, the (negative) influence of preceptors on student learning was particularly prominent. In this setting, learning effects resulted not only from the high-stakes nature of summative assessment but also from personal stakes, e.g. for esteem and agency. The results suggest that to influence student learning, consequences should accrue from assessment that are immediate, concrete and substantial. The model could have utility as a planning or diagnostic tool in practice and research settings.
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    Modelling the pre-assessment learning effects of assessment : evidence in the validity chain
    (Blackwell Publishing Ltd, 2012-10) Cilliers, Francois J.; Schuwirth, Lambert W. T.; Van der Vleuten, Cees P. M.
    OBJECTIVES We previously developed a model of the pre-assessment learning effects of consequential assessment and started to validate it. The model comprises assessment factors, mechanism factors and learning effects. The purpose of this study was to continue the validation process. For stringency, we focused on a subset of assessment factor–learning effect associations that featured least commonly in a baseline qualitative study. Our aims were to determine whether these uncommon associations were operational in a broader but similar population to that in which the model was initially derived. METHODS A cross-sectional survey of 361 senior medical students at one medical school was undertaken using a purpose-made questionnaire based on a grounded theory and comprising pairs of written situational tests. In each pair, the manifestation of an assessment factor was varied. The frequencies at which learning effects were selected were compared for each item pair, using an adjusted alpha to assign significance. The frequencies at which mechanism factors were selected were calculated. RESULTS There were significant differences in the learning effect selected between the two scenarios of an item pair for 13 of this subset of 21 uncommon associations, even when a p-value of < 0.00625 was considered to indicate significance. Three mechanism factors were operational in most scenarios: agency; response efficacy, and response value. CONCLUSIONS For a subset of uncommon associations in the model, the role of most assessment factor–learning effect associations and the mechanism factors involved were supported in a broader but similar population to that in which the model was derived. Although model validation is an ongoing process, these results move the model one step closer to the stage of usefully informing interventions. Results illustrate how factors not typically included in studies of the learning effects of assessment could confound the results of interventions aimed at using assessment to influence learning.