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We consider the problem of assessing the changing performance levels of individual students as they go through online courses. This student performance modeling problem is a critical step for building adaptive online teaching systems. Specifically, we conduct a study of how to utilize various types and large amounts of log data from earlier students to train accurate machine learning models that predict the performance of future students. This study is the first to use four very large sets of student data made available recently from four distinct intelligent tutoring systems. Our results include a new machine learning approach that defines a new state of the art for logistic regression based student performance modeling, improving over earlier methods in several ways: First, we achieve improved accuracy of student modeling by introducing new features that can be easily computed from conventional question-response logs (e.g., features such as the pattern in the student's most recent answers). Second, we take advantage of features of the student history that go beyond question-response pairs (e.g., features such as which video segments the student watched, or skipped) as well as background information about prerequisite structure in the curriculum. Third, we train multiple specialized student performance models for different aspects of the curriculum (e.g., specializing in early versus later segments of the student history), then combine these specialized models to create a group prediction of the student performance. Taken together, these innovations yield an average AUC score across these four datasets of 0.808 compared to the previous best logistic regression approach score of 0.767, and also outperforming state-of-the-art deep neural net approaches. Importantly, we observe consistent improvements from each of our three methodological innovations, in each diverse dataset, suggesting that our methods are of general utility and likely to produce improvements for other online tutoring systems as well.

Background: No studies have evaluated the unique potential of nurse‐led silver diamine fluoride (SDF) application for children to bridge the gap in interprofessional collaboration. Aim: To investigate the attitudes, beliefs and perceptions of nurses regarding nurse‐led SDF application at the well‐child visit and identify possible barriers and make recommendations. Design: Mixed methods design involving a questionnaire and semi‐structured individual interviews were conducted. Results: All eligible nurses (n = 110) completed the questionnaire, and 16 were interviewed. Questionnaire responses highlighted that nurses were not confident in providing oral health services (score: <3 of 5) beyond oral hygiene advice (score: ≥3.9 of 5) but believed that they should be providing these services for individuals with difficulty accessing care. Interviews reflected that most nurses viewed oral health care as an important part of paediatric health but were limited by knowledge, time and manpower. Most were willing to expand their job scope to include SDF application with formal education and training, competency assessments and approaches to counter time limitations. Conclusion: Where nurses are already providing basic oral healthcare, nurse‐led SDF application could be the next step. Findings suggest that systemic changes should include strategies to empower and motivate nurses to apply SDF at the well‐child visit. [ABSTRACT FROM AUTHOR]

Introduction: In paediatric practice, healthcare professionals are required to connect with the child and interact at his/her level. However, it can be very difficult for medical students to put themselves in the shoes of the young child, to empathize and understand how a child actually feels while being treated. The Teddy Bear Hospital (TBH) can serve as a platform for medical students to learn how to communicate and empathise with children. Additionally, virtual reality (VR) can be used to portray a child’s viewpoint. This study aims to assess how TBH and VR can improve learning outcomes for medical students. Methods: A cohort study was conducted on 20 first-year medical students taking part in TBH sessions. The medical students did a Pre-, Post- and 1-year Post-intervention Jefferson Scale of Empathy to assess their empathy levels. They also completed a 1- year Post-intervention quantitative and qualitative survey on their experience. Results: There was a significant increase in Jefferson score compared to Pre-intervention (116.95 ± 8.19) for both Postintervention (121.65 ± 11.03) and 1-year Post-intervention (123.31 ± 8.86). More than 80% believed that participating in TBH improved their confidence and ability to interact with children, while 50% felt that VR scenarios helped prepare them for the TBH. Thematic analysis of qualitative responses described (1) Personal development, (2) Insights into interacting with children, and (3) Structure and curriculum. Conclusion: TBH improved empathy and communication with children among pre-clinical medical students and the use of VR can be used to augment sessions. [ABSTRACT FROM AUTHOR]

The emergence of multidrug resistance (MDR) in Proteus mirabilis clinical isolates is a growing public health concern and has serious implications for wildlife. What is the role of wildlife has been become one of the hot issues in disseminating antimicrobial resistance. Here, 54 P. mirabilis isolates from 12 different species were identified. Among them, 25 isolates were determined to be MDR by profile of antimicrobial susceptibility; 10 MDR P. mirabilis isolates were subjected to comparative genomic analysis by whole genome sequencing. Comprehensive analysis showed that chromosome of P. mirabilis isolates mainly carries multidrug‐resistance complex elements harboring resistance to carbapenem genes blaOXA‐1, blaNDM‐1, and blaTEM‐1. Class I integron is the insertion hotspot of IS26; it can be inserted into type I integron at different sites, thus forming a variety of multiple drug resistance decision sites. At the same time, Tn21, Tn7, and SXT/R391 mobile elements cause widespread spread of these drug resistance genes. In conclusion, P. mirabilis isolates from wildlife showed higher resistance to commonly used clinic drugs comparing to those from human. Therefore, wild animals carrying MDR clinical isolates should be paid attention to by the public health. [ABSTRACT FROM AUTHOR]