Enhancing student learning with case-based learning objects in a problem-based learning context: the views of social work students in Scotland and Canada

This paper summarizes the results of an evaluation of students' perspectives comparing learning from a multimedia case-based learning object with learning from text-based case studies. A secondary goal of the study was to test the reusability of the learning object in different instructional contexts. The learning object was deployed in the context of a problem-based learning approach to teaching social work students in three different courses in two different countries: Scotland (N=39) and Canada (N=57). Students completed a structured survey form including a series of statements using a five point Likert scale to quantify their views of the different case types (text-based and multimedia). Results indicate strong support for the use of multimedia case scenarios in social work education. Students felt their learning was enhanced using multimedia case studies compared to text-based case studies. A number of benefits, disadvantages and recommendations were identified that will help guide the future development, (re)use, and exchange of digitized learning resources in social work education

Fixed-Form Variational Posterior Approximation through Stochastic Linear Regression

We propose a general algorithm for approximating nonstandard Bayesian posterior distributions. The algorithm minimizes the Kullback-Leibler divergence of an approximating distribution to the intractable posterior distribution. Our method can be used to approximate any posterior distribution, provided that it is given in closed form up to the proportionality constant. The approximation can be any distribution in the exponential family or any mixture of such distributions, which means that it can be made arbitrarily precise. Several examples illustrate the speed and accuracy of our approximation method in practice

The use of literature and dramatic play as a method of preparing preschool children for hospitalization

Thesis (M.S.)--Boston Universit

A reversible infinite HMM using normalised random measures

We present a nonparametric prior over reversible Markov chains. We use completely random measures, specifically gamma processes, to construct a countably infinite graph with weighted edges. By enforcing symmetry to make the edges undirected we define a prior over random walks on graphs that results in a reversible Markov chain. The resulting prior over infinite transition matrices is closely related to the hierarchical Dirichlet process but enforces reversibility. A reinforcement scheme has recently been proposed with similar properties, but the de Finetti measure is not well characterised. We take the alternative approach of explicitly constructing the mixing measure, which allows more straightforward and efficient inference at the cost of no longer having a closed form predictive distribution. We use our process to construct a reversible infinite HMM which we apply to two real datasets, one from epigenomics and one ion channel recording.Comment: 9 pages, 6 figure

Identifying barriers and facilitators to improving prehospital care of asthma: views of ambulance clinicians

Background: In 2008/09 there were nearly 80,000 emergency hospital admissions for asthma. Current UK guidelines emphasise the importance of evidence-based prehospital assessment and treatment of asthma for improving patient outcomes and reducing hospitalisation, morbidity and mortality. National benchmarking of ambulance clinical performance indicators for asthma has revealed important unexplained variations in care across ambulance services. Little research has been undertaken to understand the reasons for poor levels of care. Objective: The aim of this study was to gather data on ambulance clinicians’ perceptions and beliefs around prevailing and best practice for management of asthma. This was used to identify the factors which prevent or enable better asthma care in ambulance services. Methods: We used a phenomenological qualitative approach, which addresses how individuals use their experiences to make sense of their world, focusing on participants’ lived experiences of care delivery for asthma. We used focus groups of ambulance clinicians to gather data on barriers and facilitators to better asthma care. Recordings and notes were taken, transcribed and then analysed using QSR NVivo 8. A coding framework was developed based on a priori concepts but with emergent themes added during the analysis. Results: Two focus groups were conducted with eight and five participants respectively. A number of preliminary themes and subthemes were identified. The study identified issues relating to clarity of ambulance guidelines, conflicts between training and guidance, misconceptions about the importance of objective assessment and over reliance on non-objective assessment. Some practitioners believed that hospital staff were not interested in prehospital peak flow assessments. Conclusion: Our findings will inform improved systems of care for asthma and the effect on indicators will be measured using time series methods. This approach could be used more widely to improve management of specific clinical conditions where quality of care is demonstrated to be suboptimal