Evaluation of sepsis teaching for medical and dental students at a British University

Near-Peer-Teaching Revision Series During the COVID-19 Recovery Phase: An Experience From a UK Medical School

Background The COVID-19 pandemic led to a significant disruption in clinical attachments for final-year medical students which can result in gaps in clinical knowledge and lower confidence levels. We developed a targeted near-peer-teaching (NPT) revision series to bridge this gap. Method A one-week virtual revision series was developed by the postgraduate doctors (PD and AT) and supervised by the final year written paper lead (NS) as per curriculum requirements. The series focused on eight key common clinical presentations. It was delivered via Leicester Medical School's virtual platform by PD and AT a week before the finals. Multiple-choice surveys were sent out prior to the commencement of the series to gauge participation and baseline confidence. Surveys were also sent out before and after each session evaluating teaching, confidence levels, and improvement points. Results This NPT experience was the first comprehensive revision series during the COVID-19 recovery phase. Between 30 and 120 students attended each session. From the pre-series survey (n=63), almost all students indicated that their clinical attachments had been affected by the pandemic and that they (100%) would be interested in participating in the NPT series. From the post-session surveys, 93% of students reported that the session enhanced their confidence in recognizing and managing the clinical presentation, and 100% considered the quality of teaching to be good to excellent. From the post-series survey, a significant improvement was seen in confidence based on the Likert scale (from a combined 35% to 83%, pre, and post-series, respectively). Conclusion The series evaluation demonstrates that students found it a valuable experience and benefited from the social and cognitive congruence afforded by near-peer teachers. Furthermore, the results support the continued use and development of a virtual pre-exam revision series within the medical school curriculum as an adjunct to normal teaching.

Evaluation Method of Public Physical Training Quality Based on Global Topology Optimization Deep Learning Model

In the quality evaluation of public sports training, the selected indicators are not comprehensive, resulting in some errors in the results of quality evaluation. Therefore, this paper designs a public sports training quality evaluation method based on the deep learning model of global topology optimization. Determine the basic principles of public sports training quality evaluation, determine the human coordinate points of public sports training by determining the basic section and basic axis of human training, and extract the data of public sports training quality evaluation. On this basis, quantify the public sports training quality evaluation index, construct the evaluation matrix, calculate the weight of the evaluation index, and determine the importance of the public sports training quality evaluation index. Preprocess the public sports training quality evaluation index set, search the optimal fitness value in the global topology optimization depth learning model, introduce the global topology optimization depth learning model, input the evaluation index and output the evaluation quality results, and realize the quality evaluation of public sports training. The experimental results show that the evaluation method in this paper can improve the accuracy of the evaluation results and is feasible.