955 resultados para Medical student
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"ORIGO Stepping Stones gives mathematics teachers the best of both worlds by delivering lessons and teacher guides on a digital platform blended with the more traditional printed student journals." -- Publisher website
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In Chapter 10, Adam and Dougherty describe the application of medical image processing to the assessment and treatment of spinal deformity, with a focus on the surgical treatment of idiopathic scoliosis. The natural history of spinal deformity and current approaches to surgical and non-surgical treatment are briefly described, followed by an overview of current clinically used imaging modalities. The key metrics currently used to assess the severity and progression of spinal deformities from medical images are presented, followed by a discussion of the errors and uncertainties involved in manual measurements. This provides the context for an analysis of automated and semi-automated image processing approaches to measure spinal curve shape and severity in two and three dimensions.
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Mixture models are a flexible tool for unsupervised clustering that have found popularity in a vast array of research areas. In studies of medicine, the use of mixtures holds the potential to greatly enhance our understanding of patient responses through the identification of clinically meaningful clusters that, given the complexity of many data sources, may otherwise by intangible. Furthermore, when developed in the Bayesian framework, mixture models provide a natural means for capturing and propagating uncertainty in different aspects of a clustering solution, arguably resulting in richer analyses of the population under study. This thesis aims to investigate the use of Bayesian mixture models in analysing varied and detailed sources of patient information collected in the study of complex disease. The first aim of this thesis is to showcase the flexibility of mixture models in modelling markedly different types of data. In particular, we examine three common variants on the mixture model, namely, finite mixtures, Dirichlet Process mixtures and hidden Markov models. Beyond the development and application of these models to different sources of data, this thesis also focuses on modelling different aspects relating to uncertainty in clustering. Examples of clustering uncertainty considered are uncertainty in a patient’s true cluster membership and accounting for uncertainty in the true number of clusters present. Finally, this thesis aims to address and propose solutions to the task of comparing clustering solutions, whether this be comparing patients or observations assigned to different subgroups or comparing clustering solutions over multiple datasets. To address these aims, we consider a case study in Parkinson’s disease (PD), a complex and commonly diagnosed neurodegenerative disorder. In particular, two commonly collected sources of patient information are considered. The first source of data are on symptoms associated with PD, recorded using the Unified Parkinson’s Disease Rating Scale (UPDRS) and constitutes the first half of this thesis. The second half of this thesis is dedicated to the analysis of microelectrode recordings collected during Deep Brain Stimulation (DBS), a popular palliative treatment for advanced PD. Analysis of this second source of data centers on the problems of unsupervised detection and sorting of action potentials or "spikes" in recordings of multiple cell activity, providing valuable information on real time neural activity in the brain.
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This paper examines discussions of Generation Y within higher education discourse, arguing the sector’s use of the term to describe students is misguided for three reasons. First, portraying students as belonging to Generation Y homogenises people undertaking higher education as young, middle-class and technologically literate. Second, speaking of Generation Y students allows constructivism to be reinvented as a ‘new’ learning and teaching philosophy. Third, the Generation Y university student has become a central figure in concerns about technology’s role in learning and teaching. While the notion of the ‘Generation Y student’ creates the illusion that higher education institutions understand their constituents, ultimately, it is of little value in explaining young adults’ educational experiences.
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Diminished student interest in science, technology, engineering and mathematics (STEM) is recognised by educators, researchers and public policy makers as a concerning global trend. Inviting stakeholders like scientists and industry specialists to discuss their work is one means schools use to facilitate student engagement in the sciences. However, these visits generally comprise one-off sessions with minimal relevance to students’ particular and ongoing learning needs. This case study investigated coteaching and cogenerative dialoguing with parents in teaching a Year-8 multidisciplinary unit with science and technology foci. Two parents cotaught alongside the resident teacher and researcher over eight months. This paper concentrates on one parent, a medical scientist by profession. Data sources included video and audio recordings of cogenerative dialogues and classroom interactions, student work samples and journal entries. Data were interrogated using the sociological constructs of fields and capitals and the dialectic of structure|agency. The findings reveal how (a) the parent’s science and technology knowledge was tailored to the students’ needs initially and continually and (b) student-generated data indicated enhanced engagement in science and technology. The research speaks to schools and governments about enhancing STEM education by furthering collaborative relationships with relevant stakeholders.
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For more than a decade research in the field of context aware computing has aimed to find ways to exploit situational information that can be detected by mobile computing and sensor technologies. The goal is to provide people with new and improved applications, enhanced functionality and better use experience (Dey, 2001). Early applications focused on representing or computing on physical parameters, such as showing your location and the location of people or things around you. Such applications might show where the next bus is, which of your friends is in the vicinity and so on. With the advent of social networking software and microblogging sites such as Facebook and Twitter, recommender systems and so on context-aware computing is moving towards mining the social web in order to provide better representations and understanding of context, including social context. In this paper we begin by recapping different theoretical framings of context. We then discuss the problem of context- aware computing from a design perspective.
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The ‘Dream Circle’ is a space designed by and operated through Indigenous educator footprints as a safe space for the school’s deadly jarjums (Indigenous children). The ‘Dream Circle’ uses a kinnected methodology drawing on the rich vein of Murri cultural knowledges and Torres Strait Islander supports within the local community to provide a safe and supportive circle. The ‘Dream Circle’ operates on a school site in the Logan area as an after school homework and cultural studies class. The ‘Dream Circle’ embodies practices and ritualises processes which ensure cultural safety and integrity. In this way the ‘Dream Circle’ balances the measures that Sarra (2005) purports are the stronger, smarter realities needed for positive change in Indigenous education.
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The dynamic interplay between existing learning frameworks: people, pedagogy, learning spaces and technology is challenging the traditional lecture. A paradigm is emerging from the correlation of change amongst these elements, offering new possibilities for improving the quality of the learning experience. For many universities, the design of physical learning spaces has been the focal point for blending technology and flexible learning spaces to promote learning and teaching. As the pace of technological change intensifies, affording new opportunities for engaging learners, pedagogical practice in higher education is not comparatively evolving. The resulting disparity is an opportunity for the reconsideration of pedagogical practice for increased student engagement in physical learning spaces as an opportunity for active learning. This interplay between students, staff and technology is challenging the value for students in attending physical learning spaces such as the traditional lecture. Why should students attend for classes devoted to content delivery when streaming and web technologies afford more flexible learning opportunities? Should we still lecture? Reconsideration of pedagogy is driving learning design at Queensland University of Technology, seeking new approaches affording increased student engagement via active learning experiences within large lectures. This paper provides an overview and an evaluation of one of these initiatives, Open Web Lecture (OWL), an experimental web based student response application developed by Queensland University of Technology. OWL seamlessly integrates a virtual learning environment within physical learning spaces, fostering active learning opportunities. This paper will evaluate the pilot of this initiative through consideration of effectiveness in increasing student engagement through the affordance of web enabled active learning opportunities in physical learning spaces.
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The dynamic interplay between existing learning frameworks: people, pedagogy, learning spaces and technology is challenging the traditional lecture. A paradigm is emerging from the correlation of change amongst these elements, offering new possibilities for improving the quality of the learning experience. For many universities, the design of physical learning spaces has been the focal point for blending technology and flexible learning spaces to promote learning and teaching. As the pace of technological change intensifies, affording new opportunities for engaging learners, pedagogical practice in higher education is not comparatively evolving. The resulting disparity is an opportunity for the reconsideration of pedagogical practice for increased student engagement in physical learning spaces as an opportunity for active learning. This interplay between students, staff and technology is challenging the value for students in attending physical learning spaces such as the traditional lecture. Why should students attend for classes devoted to content delivery when streaming and web technologies afford more flexible learning opportunities? Should we still lecture? Reconsideration of pedagogy is driving learning design at Queensland University of Technology, seeking new approaches affording increased student engagement via active learning experiences within large lectures. This paper provides an overview and an evaluation of one of these initiatives, Open Web Lecture (OWL), an experimental web based student response application developed by Queensland University of Technology. OWL seamlessly integrates a virtual learning environment within physical learning spaces, fostering active learning opportunities. This paper will evaluate the pilot of this initiative through consideration of effectiveness in increasing student engagement through the affordance of web enabled active learning opportunities in physical learning spaces.
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Objective: We explore how accurately and quickly nurses can identify melodic medical equipment alarms when no mnemonics are used, when alarms may overlap, and when concurrent tasks are performed. Background: The international standard IEC 60601-1-8 (International Electrotechnical Commission, 2005) has proposed simple melodies to distinguish seven alarm sources. Previous studies with nonmedical participants reveal poor learning of melodic alarms and persistent confusions between some of them. The effects of domain expertise, concurrent tasks, and alarm overlaps are unknown. Method: Fourteen intensive care and general medical unit nurses learned the melodic alarms without mnemonics in two sessions on separate days. In the second half of Day 2 the nurses identified single alarms or pairs of alarms played in sequential, partially overlapping, or nearly completely overlapping configurations. For half the experimental blocks nurses performed a concurrent mental arithmetic task. Results: Nurses' learning was poor and was no better than the learning of nonnurses in a previous study. Nurses showed the previously noted confusions between alarms. Overlapping alarms were exceptionally difficult to identify. The concurrent task affected response time but not accuracy. Conclusion: Because of a failure of auditory stream segregation, the melodic alarms cannot be discriminated when they overlap. Directives to sequence the sounding of alarms in medical electrical equipment must be strictly adhered to, or the alarms must redesigned to support better auditory streaming. Application: Actual or potential uses of this research include the implementation of IEC 60601-1-8 alarms in medical electrical equipment.
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Melodic alarms proposed in the IEC 60601-1-8 standard for medical electrical equipment were tested for learnability and discriminability. Thirty-three non-anaesthetist participants learned the alarms over two sessions of practice, with or without mnemonics suggested in the standard. Fewer than 30% of participants could identify the alarms with 100% accuracy at the end of practice. Confusions persisted between pairs of alarms, especially if mnemonics were used during learning (p = 0.011). Participants responded faster (p < 0.00001) and more accurately (p = 0.002) to medium priority alarms than to high priority alarms, even though they rated the high priority alarms as sounding more urgent (p < 0.00001). Participants with at least 1 year of formal musical training identified the alarms more accurately (p = 0.0002) than musically untrained participants, and found the task easier overall (p < 0.00001). More intensive studies of the IEC 60601-1-8 alarms are needed for their effectiveness to be determined.