55 research outputs found

    Research Day 2023 Program

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    Effective teacher professional development: new theory and a meta-analytic test

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    Multiple meta-analyses have now documented small positive effects of teacher professional development (PD) on pupil test scores. However, the field lacks any validated explanatory account of what differentiates more from less effective in-service training. As a result, researchers have little in the way of advice for those tasked with designing or commissioning better PD. We set out to remedy this by developing a new theory of effective PD based on combinations of causally active components targeted at developing teachers’ insights, goals, techniques, and practice. We test two important implications of the theory using a systematic review and meta-analysis of 104 randomised controlled trials, finding qualified support for our framework. While further research is required to test and refine the theory, we argue that it presents an important step forward in being able to offer actionable advice to those responsible for improving teacher PD

    Serious Games and Mixed Reality Applications for Healthcare

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    Virtual reality (VR) and augmented reality (AR) have long histories in the healthcare sector, offering the opportunity to develop a wide range of tools and applications aimed at improving the quality of care and efficiency of services for professionals and patients alike. The best-known examples of VR–AR applications in the healthcare domain include surgical planning and medical training by means of simulation technologies. Techniques used in surgical simulation have also been applied to cognitive and motor rehabilitation, pain management, and patient and professional education. Serious games are ones in which the main goal is not entertainment, but a crucial purpose, ranging from the acquisition of knowledge to interactive training.These games are attracting growing attention in healthcare because of their several benefits: motivation, interactivity, adaptation to user competence level, flexibility in time, repeatability, and continuous feedback. Recently, healthcare has also become one of the biggest adopters of mixed reality (MR), which merges real and virtual content to generate novel environments, where physical and digital objects not only coexist, but are also capable of interacting with each other in real time, encompassing both VR and AR applications.This Special Issue aims to gather and publish original scientific contributions exploring opportunities and addressing challenges in both the theoretical and applied aspects of VR–AR and MR applications in healthcare

    Recent Advances in Minimally Invasive Surgery

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    Minimally invasive surgery has become a common term in visceral as well as gynecologic surgery. It has almost evolved into its own surgical speciality over the past 20 years. Today, being firmly established in every subspeciality of visceral surgery, it is now no longer a distinct skillset, but a fixed part of the armamentarium of surgical options available. In every indication, the advantages of a minimally invasive approach include reduced intraoperative blood loss, less postoperative pain, and shorter rehabilitation times, as well as a marked reduction of overall and surgical postoperative morbidity. In the advent of modern oncologic treatment algorithms, these effects not only lower the immediate impact that an operation has on the patient, but also become important key steps in reducing the side-effects of surgery. Thus, they enable surgery to become a module in modern multi-disciplinary cancer treatment, which blends into multimodular treatment options at different times and prolongs and widens the possibilities available to cancer patients. In this quickly changing environment, the requirement to learn and refine not only open surgical but also different minimally invasive techniques on high levels deeply impact modern surgical training pathways. The use of modern elearning tools and new and praxis-based surgical training possibilities have been readily integrated into modern surgical education,which persists throughout the whole surgical career of modern gynecologic and visceral surgery specialists

    Assessing and teaching radiotherapy contouring

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    Advanced radiotherapy techniques such as image-guided adaptive brachytherapy for cervical cancer improve local tumour control and reduce treatment toxicity. This benefit is critically dependent on radiotherapy targeting or “contouring” by oncologists. Numerous studies have shown considerable inter-observer contouring variation across all tumour sites, often measured in centimetres, suggesting that current methods of teaching contouring are ineffective. Moreover, assessing contouring competency is currently a subjective, time-consuming and onerous process. The aim of this programme of research is to investigate the assessment and teaching of radiotherapy contouring within an educational design research framework. The thesis reviews the limitations and challenges of current strategies to improve radiotherapy contouring and how insights from the educational literature such as cognitive load theory, deliberate practice theory, and best practices in assessment and feedback can inform and improve contouring assessment and teaching. Real-world data from two studies of online assessment and education for radiotherapy contouring, within an international clinical trial of advanced radiotherapy techniques for locally advanced cervical cancer, were analysed to substantiate the limitations of current approaches within a clinical trial setting. The thesis describes a novel low-fidelity radiotherapy contouring simulation tool developed to address some of the issues identified in the clinical studies. A detailed useability study was carried out in a small group of oncologists, which also yielded interesting insights into their clinical reasoning and self-regulation processes. The simulation was then used in three pilot studies of different types of learners (trainees and experts) and programmes (one-off workshops and longitudinal programmes) to explore its acceptability, useability and effectiveness. The thesis concludes by discussing possible approaches for the next iteration of software development and educational research, which could lead to meaningful change in the teaching and assessment of radiotherapy contouring

    A Graduatte Level Immersive-Simulattion Program for Teaching and Assessing Fundamental Skills in Entry Level Clinical Perfusionists.

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    Background: The clinical perfusionist is a member of the open-heart-surgery team and responsible for operating the life support equipment that replaces the function of the patient\u27s heart and lungs and arrests and restarts the patient\u27s heart in the course of a Cardiopulmonary Bypass (CPB) procedure. In the perfusionists scope of practice, the consequence of unskilled actions, inaccurate understanding or delayed decision making may result in significant patient morbidity or even death. Historically, perfusion students have learned and practiced their skills within a clinical preceptorship program in which an experienced clinician allows the novice student to operate the life support equipment under their direct supervision and consultation. While there is clinical evidence from numerous surgical specialties which establishes that learning curve associated errors have a negative effect on patient outcomes, this has not been researched for clinical perfusionists. Despite this evidence gap, the professions leaders have been instrumental in driving educational innovation and the development of medical simulation models that may reduce the patient\u27s exposure to learning curve associated morbidity by developing competence with high-risk clinical skills prior to patient contact. The purpose of this research is to develop, validate and apply novel medical simulation techniques and technologies to the preparation of entry level clinical perfusionists and demonstrate pre-clinical competence with the fundamental perfusion skills.Methods and Results: To inform the development of a skills curriculum we conducted two national surveys using online survey tools. Through these surveys we validated a list of fundamental skills, and the deconstructed sub-elements involved in the conduct of these skills. Additionally, we identified the typical ranges of physiologic and technical parameters that clinicians maintain during clinical procedures. With this foundational benchmark data we validated the performance of a simulated patient to establish that the patient surrogate generates data that is substantially similar to the physiologic and technical data that a perfusionist would manage during a live clinical procedure. This validated simulation technology was then incorporated into a high-fidelity simulation suite and applied to an innovative immersive curriculum which included hands on repetitive practice, live and video supported self, peer and expert observation and feedback as well as a battery of high-stakes assessments. The validity and fidelity of the simulated experience was established through analysis of over 800 opinions generated over 10 years by novice and expert perfusionists after performing simulated cases. Finally, the efficacy of the simulation curriculum was assessed by comparing our simulation trained students to a national pool of their peers from other schools and expert clinicians. Through this process we generated the first measurements of the typical learning curve for the fundamental skills of CPB, the first estimates of error rates for students navigating the learning curve and the first benchmark measures of competent performance in a simulated environment. This data establishes that students learning in traditional clinical training programs conduct three-fold more errors than experts and will have approximately 99 high-risk patient encounters prior to developing competence with fundamental skills. By comparison, simulation trained students demonstrated competence with fundamental skills that was similar to the experts with almost no high-risk patient encounters. Discussion: The implications to patient safety are clearly implied. These studies establish that there is a high level of agreement among clinicians regarding the skills that are necessary to operate perfusion equipment and that realistic simulation environments can be designed and applied to the development of student\u27s fundamental perfusion skills without exposing patients to the threat of students learning curve associated errors. This data may catalyze a larger national dialog regarding Entrustable Professional Activities for perfusionists and influence national accreditation standards for educational programs

    Objective and automated assessment of surgical technical skills with IoT systems: A systematic literature review

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    The assessment of surgical technical skills to be acquired by novice surgeons has been traditionally done by an expert surgeon and is therefore of a subjective nature. Nevertheless, the recent advances on IoT, the possibility of incorporating sensors into objects and environments in order to collect large amounts of data, and the progress on machine learning are facilitating a more objective and automated assessment of surgical technical skills. This paper presents a systematic literature review of papers published after 2013 discussing the objective and automated assessment of surgical technical skills. 101 out of an initial list of 537 papers were analyzed to identify: 1) the sensors used; 2) the data collected by these sensors and the relationship between these data, surgical technical skills and surgeons' levels of expertise; 3) the statistical methods and algorithms used to process these data; and 4) the feedback provided based on the outputs of these statistical methods and algorithms. Particularly, 1) mechanical and electromagnetic sensors are widely used for tool tracking, while inertial measurement units are widely used for body tracking; 2) path length, number of sub-movements, smoothness, fixation, saccade and total time are the main indicators obtained from raw data and serve to assess surgical technical skills such as economy, efficiency, hand tremor, or mind control, and distinguish between two or three levels of expertise (novice/intermediate/advanced surgeons); 3) SVM (Support Vector Machines) and Neural Networks are the preferred statistical methods and algorithms for processing the data collected, while new opportunities are opened up to combine various algorithms and use deep learning; and 4) feedback is provided by matching performance indicators and a lexicon of words and visualizations, although there is considerable room for research in the context of feedback and visualizations, taking, for example, ideas from learning analytics.This work was supported in part by the FEDER/Ministerio de Ciencia, InnovaciĂłn y Universidades;Agencia Estatal de InvestigaciĂłn, through the Smartlet Project under Grant TIN2017-85179-C3-1-R, and in part by the Madrid Regional Government through the e-Madrid-CM Project under Grant S2018/TCS-4307, a project which is co-funded by the European Structural Funds (FSE and FEDER). Partial support has also been received from the European Commission through Erasmus + Capacity Building in the Field of Higher Education projects, more specifically through projects LALA (586120-EPP-1-2017-1-ES-EPPKA2-CBHE-JP), InnovaT (598758-EPP-1-2018-1-AT-EPPKA2-CBHE-JP), and PROF-XXI (609767-EPP-1-2019-1-ES-EPPKA2-CBHE-JP)

    Understanding User Cognition: From Spatial Ability to Code Writing and Review

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    Understanding how developers carry out different computer science activities with objective measures can help to improve productivity and guide the use and development of supporting tools in software engineering. In this thesis, we present three research components using three different objective measures including neuroimaging (functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRS)) and eye tracking. We evaluate on over 140 human subjects to explore multiple computing activities, including data structure manipulations, code writing and code review. This thesis presents a systematic framework and shows that it is possible to conduct studies that acquire objective data in a natural setting to provide an understanding of users' underlying cognitive processes in software engineering tasks. We also provide basic principles and guidelines to adapt multiple psycho-physiological measures to software engineering.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169678/1/yhhy_1.pd
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