WhatsApp as a support strategy for emergency nursing students during the COVID‑19 pandemic

No Abstrac

Creative strategies to support student learning through reflection

Reflective practice has become a key attribute of promoting quality teaching and learning. Learning is an active process and include reflective writing, visualising and verbalising to promote critical thinking. In our experience most often than not superficial reflective writing is used. We explored the design of opportunities for students to engage in critical reflection. Theoretical data were obtained through in-depth exploration of the literature to allow contextualisation while arguing a case. A qualitative approach was used. Judgements were not made about the measured quality of reported findings, but on the relevance of reflective strategies to support students, enhance critical reflection and transform practice. Combined with narration and dialogue, reflection can bridge the gap between theoretical ideals and realities of the practice context. Four reflective activities have been identified that could be used to engage students in critical reflection

Probabilistic Analysis of Power Network Susceptibility to GICs

As reliance on power networks has increased over the last century, the risk of damage from geomagnetically induced currents (GICs) has become a concern to utilities. The current state of the art in GIC modelling requires significant geophysical modelling and a theoretically derived network response, but has limited empirical validation. In this work, we introduce a probabilistic engineering step between the measured geomagnetic field and GICs, without needing data about the power system topology or the ground conductivity profiles. The resulting empirical ensembles are used to analyse the TVA network (south-eastern USA) in terms of peak and cumulative exposure to 5 moderate to intense geomagnetic storms. Multiple nodes are ranked according to susceptibility and the measured response of the total TVA network is further calibrated to existing extreme value models. The probabilistic engineering step presented can complement present approaches, being particularly useful for risk assessment of existing transformers and power systems.Comment: 6 pages, 7 figures, accepted for PMAPS 202