Engaging and developing front-line clinical nurses to drive care excellence:Evaluating the Chief Nurse Excellence in Care Junior Fellowship initiative

Background Global challenges in the development of a highly skilled and motivated nursing workforce, jeopardises the delivery of high quality care. Flexible and innovative workforce solutions are required to overcome these challenges. Aims To describe the implementation and present the preliminary evaluation of a bespoke initiative called the ‘Chief Nurse Excellence in Care Junior Fellow’ designed to develop foundational clinical and academic skills of frontline junior clinical staff. Methods This initiative was developed and piloted at a large, inner-city, acute NHS Trust. The initiative involved two main components: a bespoke development programme and an improvement project that was supported by clinical and academic mentors. The initiative was evaluated using structured feedback, case studies, and data on dissemination activities. Results Six fellows completed the first cohort of the initiative that commenced in the spring 2016. Results showed positive impact on professional development relating to the acquisition of new knowledge and skills. Case studies of projects showed demonstrable impact on patient experience, outcomes and cost savings. Wider organisation and NHS impact was demonstrated through multiple dissemination activities.Conclusion This preliminary evaluation provides evidence that this initiative is a sustainable, clinically driven career development opportunity at a foundational level with demonstrable positive impact on care and staff development. Further work is underway to carry out a longitudinal structure, process and outcome evaluation with particular focus on impact

Don't feedback in anger : enhancing student experience of feedback

This research explores three iterations of the delivery of audio feedback in relation to formative assessments at the School of Law, University of Sheffield. The evidence base includes similar practice at Edge Hill University and collaboration on good practice between the two institutions. This paper will set out the context for the implementation of audio feedback, namely to help address the difficult issues experienced with feedback from non-engagement by the student in the whole feedback process, to a lack of utilization of formative feedback for 'feedforward' purposes. Qualitative comments from both students and staff experiencing this model of feedback will be drawn upon, which include references to the perceived benefits and challenges of this mode of feedback by both sets of stakeholders. This paper will then take participants through the methods addressed to engage student with feedback on formative assessments, in order to create and encourage proper 'feedforward' to summative assessments, and to provide effective, focused, consistent and constructive feedback. This paper in particular aims to show how the provision of audio feedback has the potential to greatly enhance the student learning experience, and can provide a more positive attitude generally to the giving, and receiving of feedback from both staff and students alike

Embodied CO2 analysis of a secondary school

This paper describes the process, challenges and results of a carbon profiling tool used as part of the design process at White Design Associates. The paper first explores the need amongst designers for a carbon profiling tool to enable and encourage a focus on carbon reduction, as a key element in the fight against global warming. Next it describes the methodology adopted by White Design Associates to develop a tool to be used throughout the building design process, to inform design decisions, and begin to quantify the climate change impact of the finished building. Examples from the most recent iteration of the tool, used during the construction of John Ferneley College, illustrate the development of the tool, the challenges that were faced, and the "headline" results of the analysis. It also illustrates how White Design incorporated the results into the curriculum through web updates and highlights the Carbon Stacks visualisation tool

Acquisition of a High-Speed, High Capacity Storage System to Support Scientific Computing: The Data Capacitor Final Report

Final report to the National Science Foundation on ACI-0521433.National Science Foundatio

Quantum system-bath dynamics with quantum superposition sampling and coupled generalized coherent states

Previously, we introduced two versions of the Multiconfigurational Ehrenfest (MCE) approach to high dimensional quantum dynamics. It has been shown that the first version, MCEv1, converges well to the existing benchmarks for high dimensional model systems. At the same time, it was found that the second version, MCEv2, had more difficulty converging in some regimes. As MCEv2 is particularly suited for direct dynamics, it is important to facilitate its convergence. This paper investigates an efficient method of basis set sampling, called Quantum Superposition Sampling (QSS), which dramatically improves the performance of the MCEv2 approach. QSS is tested on the spin-boson model, often used for modeling of open quantum systems. It is also shown that the quantum subsystem in the spin-boson model can be conveniently treated with the help of two level system coherent states. Generalized coherent states, which combine two level system coherent states for the description of the system and Gaussian coherent states for description of the bath, are introduced. Various forms of quantum equations of motion in the basis of generalized coherent states can be developed by analogy with known quantum dynamics equations in the basis of Gaussian coherent states; in particular, the multiconfigurational Ehrenfest method becomes a version of coupled generalized coherent states, and QSS can then be viewed as a generalization of a sampling method known for the existing coupled coherent states method which uses Gaussian coherent states

Children's use of interventions to learn causal structure

AbstractChildren between 5 and 8years of age freely intervened on a three-variable causal system, with their task being to discover whether it was a common cause structure or one of two causal chains. From 6 or 7years of age, children were able to use information from their interventions to correctly disambiguate the structure of a causal chain. We used a Bayesian model to examine children’s interventions on the system; this showed that with development children became more efficient in producing the interventions needed to disambiguate the causal structure and that the quality of interventions, as measured by their informativeness, improved developmentally. The latter measure was a significant predictor of children’s correct inferences about the causal structure. A second experiment showed that levels of performance were not reduced in a task where children did not select and carry out interventions themselves, indicating no advantage for self-directed learning. However, children’s performance was not related to intervention quality in these circumstances, suggesting that children learn in a different way when they carry out interventions themselves