6 resultados para Practice Learning
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This session will provide you with opportunity to find out what is being achieved and explore the implications for your own practice.
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Many have called for medical students to learn how to manage complexity in healthcare. This study examines the nuances of students' challenges in coping with a complex simulation learning activity, using concepts from complexity theory, and suggests strategies to help them better understand and manage complexity.Wearing video glasses, participants took part in a simulation ward-based exercise that incorporated characteristics of complexity. Video footage was used to elicit interviews, which were transcribed. Using complexity theory as a theoretical lens, an iterative approach was taken to identify the challenges that participants faced and possible coping strategies using both interview transcripts and video footage.Students' challenges in coping with clinical complexity included being: a) unprepared for 'diving in', b) caught in an escalating system, c) captured by the patient, and d) unable to assert boundaries of acceptable practice.Many characteristics of complexity can be recreated in a ward-based simulation learning activity, affording learners an embodied and immersive experience of these complexity challenges. Possible strategies for managing complexity themes include: a) taking time to size up the system, b) attuning to what emerges, c) reducing complexity, d) boundary practices, and e) working with uncertainty. This study signals pedagogical opportunities for recognizing and dealing with complexity.
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Aims/Purpose: Protocols are evidenced-based structured guides for directing care to achieve improvements. But translating that evidence into practice is a major challenge. It is not acceptable to simply introduce the protocol and expect it to be adopted and lead to change in practice. Implementation requires effective leadership and management. This presentation describes a strategy for implementation that should promote successful adoption and lead to practice change.
Presentation description: There are many social and behavioural change models to assist and guide practice change. Choosing a model to guide implementation is important for providing a framework for action. The change process requires careful thought, from the protocol itself to the policies and politics within the ICU. In this presentation, I discuss a useful pragmatic guide called the 6SQUID (6 Steps in QUality Intervention Development). This was initially designed for public health interventions, but the model has wider applicability and has similarities with other change process models. Steps requiring consideration include examining the purpose and the need for change; the staff that will be affected and the impact on their workload; and the evidence base supporting the protocol. Subsequent steps in the process that the ICU manager should consider are the change mechanism (widespread multi-disciplinary consultation; adapting the protocol to the local ICU); and identifying how to deliver the change mechanism (educational workshops and preparing staff for the changes are imperative). Recognising the barriers to implementation and change and addressing these locally is also important. Once the protocol has been implemented, there is generally a learning curve before it becomes embedded in practice. Audit and feedback on adherence are useful strategies to monitor and sustain the changes.
Conclusion: Managing change successfully will promote a positive experience for staff. In turn, this will encourage a culture of enthusiasm for translating evidence into practice.
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Introduction
This paper outlines an innovative approach to auditing and evaluating the content of a management and leadership module for undergraduate nursing students after their final management clinical placement. Normally evaluations of teaching in a module take place at the end of a teaching module and therefore do not properly reflect the value of the teaching in relation to practical clinical experience.
Aim
This audit and evaluation sought to explore both the practical value of the teaching and learning, and also the degree to which it the teaching reflected against the NMC Standards of Education and Learning (2010 domain 3).
Methods
Having piloted the evaluative tool with an earlier cohort of nursing students, this evaluation explored both a quantitative assessment employing a Personal Response System (n =172), together with a qualitative dimension (n=116), thus delivering paper-based comments and reflections from students on the value and practicality of the module teaching theory to their final clinical management experience. The quantitative audit data were analysed for frequencies and cross tabulation and the qualitative audit data were thematically analysed.
Results
Results suggest a significant proportion of the students, appreciated the quality of the standard of teaching, but more importantly, ‘valued or highly valued’ the teaching and learning in relation to how it helped to significantly inform their management placement experience. A smaller proportion of the students underlined limitations and areas in which further improvement can be made in teaching and learning to the module.
Conclusion
Significantly positive evaluation by the students of the practical value of teaching and learning, to the theoretical management module. This has proved a useful auditing approach in assessing the theoretical teaching to student’s Level 3 clinical experience, and facilitated significant recommendations as far as developing the teaching and learning to better reflect the practice needs of nursing students
Resumo:
Traditional heuristic approaches to the Examination Timetabling Problem normally utilize a stochastic method during Optimization for the selection of the next examination to be considered for timetabling within the neighbourhood search process. This paper presents a technique whereby the stochastic method has been augmented with information from a weighted list gathered during the initial adaptive construction phase, with the purpose of intelligently directing examination selection. In addition, a Reinforcement Learning technique has been adapted to identify the most effective portions of the weighted list in terms of facilitating the greatest potential for overall solution improvement. The technique is tested against the 2007 International Timetabling Competition datasets with solutions generated within a time frame specified by the competition organizers. The results generated are better than those of the competition winner in seven of the twelve examinations, while being competitive for the remaining five examinations. This paper also shows experimentally how using reinforcement learning has improved upon our previous technique.