689 resultados para Game-based learning model


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Climate change has already altered the distribution of marine fishes. Future predictions of fish distributions and catches based on bioclimate envelope models are available, but to date they have not considered interspecific interactions. We address this by combining the species-based Dynamic Bioclimate Envelope Model (DBEM) with a size-based trophic model. The new approach provides spatially and temporally resolved predictions of changes in species' size, abundance and catch potential that account for the effects of ecological interactions. Predicted latitudinal shifts are, on average, reduced by 20% when species interactions are incorporated, compared to DBEM predictions, with pelagic species showing the greatest reductions. Goodness-of-fit of biomass data from fish stock assessments in the North Atlantic between 1991 and 2003 is improved slightly by including species interactions. The differences between predictions from the two models may be relatively modest because, at the North Atlantic basin scale, (i) predators and competitors may respond to climate change together; (ii) existing parameterization of the DBEM might implicitly incorporate trophic interactions; and/or (iii) trophic interactions might not be the main driver of responses to climate. Future analyses using ecologically explicit models and data will improve understanding of the effects of inter-specific interactions on responses to climate change, and better inform managers about plausible ecological and fishery consequences of a changing environment.

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This study presents a fully coupled temperature–displacement finite element modelling of the injection stretch-blow moulding (ISBM) process of polyethylene terephthalate (PET) bottles using ABAQUS with a view to optimising the process conditions. A physically-based material model (Buckley model) was used to predict the mechanical behaviour of PET at temperatures slightly above its glass transition temperature. A model incorporating heat transfer between the stretch rod, the preform and the mould was built using axisymmetric solid elements. Extensive finite element analyses were carried out to predict the deformation, the distribution and history of strain and temperature during ISBM of a 20 g–330 ml bottle, which was made in an in situ test on a Sidel SB06 machine. Comparisons of numerical results with the measurements demonstrate that the model can satisfactorily model the sidewall thickness and material distributions. It is also shown that significant non-linear differentials exist in temperature and strain in both bottle thickness and length directions during the process. This justifies the employment of a volume approach to accurately predict the final mechanical properties of the bottles governed by the orientation and crystallinity which are highly temperature and strain dependent.

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Aim. This paper is a report of a study to test the proposed factor structure of the Index of Sources of Stress in Nursing Students. Background. Research across many countries has identified a number of sources of distress in nursing students but little attempt has been made to understand and measure sources of eustress or those stressors likely to enhance performance and well-being. The Index of Sources of Stress in Nursing Students was developed to do this. Exploratory factor analysis suggested a three-factor structure, the factors being labelled: learning and teaching; placement-related and course organization. It is important, however, to subject the instrument to confirmatory factor analysis as a further test of construct validity. Method. A convenience sample of final year nursing students (n = 176) was surveyed in one university in Northern Ireland in 2007. The Index of Sources of Stress in Nursing Students, which measures sources of stress likely to contribute to distress and eustress, was completed electronically. The LISREL programme was used to carry out the confirmatory factor analysis and test the factor structure suggested in the exploratory analysis. Findings. The proposed factor structure for the items measuring ‘Uplifts’ proved to be a good fit to the data and the proposed factor structure for the items measuring ‘Hassles’ showed adequate fit. Conclusion. In nursing programmes adopting the academic model and combining university-based learning with placement experience, this instrument can be used to help identify the sources of stress or course demands that students rate as distressing and those that help them to achieve. The validity of the ISSN could be further evaluated in other education settings.

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This paper reports laboratory experiments designed to study the impact of public information about past departure rates on congestion levels and travel costs. Our design is based on a discrete version of Arnott et al.'s (1990) bottleneck model. In all treatments, congestion occurs and the observed travel costs are quite similar to the predicted ones. Subjects' capacity to coordinate is not affected by the availability of public information on past departure rates, by the number of drivers or by the relative cost of delay. This seemingly absence of treatment effects is confirmed by our finding that a parameter-free reinforcement learning model best characterises individual behaviour.

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Increased complexity and interconnectivity of Supervisory Control and Data Acquisition (SCADA) systems in Smart Grids potentially means greater susceptibility to malicious attackers. SCADA systems with legacy communication infrastructure have inherent cyber-security vulnerabilities as these systems were originally designed with little consideration of cyber threats. In order to improve cyber-security of SCADA networks, this paper presents a rule-based Intrusion Detection System (IDS) using a Deep Packet Inspection (DPI) method, which includes signature-based and model-based approaches tailored for SCADA systems. The proposed signature-based rules can accurately detect several known suspicious or malicious attacks. In addition, model-based detection is proposed as a complementary method to detect unknown attacks. Finally, proposed intrusion detection approaches for SCADA networks are implemented and verified using a ruled based method.

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Increased complexity and interconnectivity of Supervisory Control and Data Acquisition (SCADA) systems in Smart Grids potentially means greater susceptibility to malicious attackers. SCADA systems with legacy communication infrastructure have inherent cyber-security vulnerabilities as these systems were originally designed with little consideration of cyber threats. In order to improve cyber-security of SCADA networks, this paper presents a rule-based Intrusion Detection System (IDS) using a Deep Packet Inspection (DPI) method, which includes signature-based and model-based approaches tailored for SCADA systems. The proposed signature-based rules can accurately detect several known suspicious or malicious attacks. In addition, model-based detection is proposed as a complementary method to detect unknown attacks. Finally, proposed intrusion detection approaches for SCADA networks are implemented and verified via Snort rules.

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Mental illness is common amongst young people living in residential care, many of whom are reluctant to avail of therapeutic help. The potential value of computer games as therapeutic tools for these young people has received very little attention, despite indications of their potential for promoting engagement in therapeutic work and improving mental health outcomes. This study aimed to fill this research gap through the development, introduction, and preliminary evaluation of a therapeutic intervention in group care settings. The intervention incorporated a commercially available computer game (The SIMS Life Stories™) and emotion regulation skill coaching. Qualified residential social workers were trained to deliver it to young people in three children's homes in Northern Ireland, where therapeutic approaches to social work had been introduced. The research was framed as an exploratory case study which aimed to determine the acceptability and potential therapeutic value of this intervention. The evidence suggests that computer-game based interventions of this type may have value as therapeutic tools in group care settings and deserve further development and empirical investigation to determine their effectiveness in improving mental health outcomes.

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We introduce a task-based programming model and runtime system that exploit the observation that not all parts of a program are equally significant for the accuracy of the end-result, in order to trade off the quality of program outputs for increased energy-efficiency. This is done in a structured and flexible way, allowing for easy exploitation of different points in the quality/energy space, without adversely affecting application performance. The runtime system can apply a number of different policies to decide whether it will execute less-significant tasks accurately or approximately.

The experimental evaluation indicates that our system can achieve an energy reduction of up to 83% compared with a fully accurate execution and up to 35% compared with an approximate version employing loop perforation. At the same time, our approach always results in graceful quality degradation.

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This paper presents a new approach to single-channel speech enhancement involving both noise and channel distortion (i.e., convolutional noise). The approach is based on finding longest matching segments (LMS) from a corpus of clean, wideband speech. The approach adds three novel developments to our previous LMS research. First, we address the problem of channel distortion as well as additive noise. Second, we present an improved method for modeling noise. Third, we present an iterative algorithm for improved speech estimates. In experiments using speech recognition as a test with the Aurora 4 database, the use of our enhancement approach as a preprocessor for feature extraction significantly improved the performance of a baseline recognition system. In another comparison against conventional enhancement algorithms, both the PESQ and the segmental SNR ratings of the LMS algorithm were superior to the other methods for noisy speech enhancement. Index Terms: corpus-based speech model, longest matching segment, speech enhancement, speech recognition

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Service user and carer involvement (SUCI) in social work education in England is required by the profession’s regulator, the Health and Care Professions Council. However, a recent study of 83 HEIs in England reported that despite considerable progress in SUCI, there is no evidence that the learning derived from it is being transferred to social work practice. In this article we describe a study that examines the question: ‘What impact does SUCI have on the skills, knowledge and values of student social workers at the point of qualification and beyond?’ Students at universities in England and Northern Ireland completed online questionnaires and participated in focus groups, spanning a period immediately pre-qualification and between six to nine months post-qualification. From our findings, we identify four categories that influence the impact of service user involvement on students’ learning: student factors; service user and carer factors; programme factors; and practice factors; each comprises of a number of sub-categories. We propose that the model developed can be used by social work educators, service user and carer contributors and practitioners to maximise the impact of SUCI. We argue that our findings also have implications for employment-based learning routes and post-qualifying education.

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In this study, we introduce an original distance definition for graphs, called the Markov-inverse-F measure (MiF). This measure enables the integration of classical graph theory indices with new knowledge pertaining to structural feature extraction from semantic networks. MiF improves the conventional Jaccard and/or Simpson indices, and reconciles both the geodesic information (random walk) and co-occurrence adjustment (degree balance and distribution). We measure the effectiveness of graph-based coefficients through the application of linguistic graph information for a neural activity recorded during conceptual processing in the human brain. Specifically, the MiF distance is computed between each of the nouns used in a previous neural experiment and each of the in-between words in a subgraph derived from the Edinburgh Word Association Thesaurus of English. From the MiF-based information matrix, a machine learning model can accurately obtain a scalar parameter that specifies the degree to which each voxel in (the MRI image of) the brain is activated by each word or each principal component of the intermediate semantic features. Furthermore, correlating the voxel information with the MiF-based principal components, a new computational neurolinguistics model with a network connectivity paradigm is created. This allows two dimensions of context space to be incorporated with both semantic and neural distributional representations.

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Background: Peer tutoring has been described as “people from similar social groupings who are not professional teachers helping each other to learn and learning themselves by teaching”. Peer tutoring is well accepted as a source of support in many medical curricula, where participation and learning involve a process of socialisation.
Peer tutoring can ease the transition of the junior students from the university class environment to the hospital workplace. In this paper, we apply the Experienced Based Learning (ExBL) model to explore medical students’ perceptions of their experience of taking part in a newly established peer tutoring program at a hospital based
clinical school.
Methods: In 2014, all students at Sydney Medical School – Central, located at Royal Prince Alfred Hospital were invited to voluntarily participate in the peer tutoring program. Year 3 students (n = 46) were invited to act as tutors for Year 1 students (n = 50), and Year 4 students (n = 60) were invited to act as tutors for Year 2 students (n = 51). Similarly, the ‘tutees’ were invited to take part on a voluntary basis. Students were invited to attend focus groups, which were held at the end of the program. Framework analysis was used to code and categorise data into themes.
Results: In total, 108/207 (52 %) students participated in the program. A total of 42/106 (40 %) of Year 3 and 4 students took part as tutors; and of 66/101 (65 %) of Year 1 and 2 students took part as tutees. Five focus groups were held, with 50/108 (46 %) of students voluntarily participating. Senior students (tutors) valued the opportunity to practice and improve their medical knowledge and teaching skills. Junior students (tutees) valued the opportunity for additional practice and patient interaction, within a relaxed, small group learning environment.
Conclusion: Students perceived the peer tutoring program as affording opportunities not otherwise available within the curriculum. The peer teaching program provided a framework within the medical curriculum for senior students to practice and improve their medical knowledge and teaching skills. Concurrently, junior students were provided with a valuable learning experience that they reported as being qualitatively different to traditional teaching by faculty.

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A 3D intralaminar continuum damage mechanics based material model, combining damage mode interaction and material nonlinearity, was developed to predict the damage response of composite structures undergoing crush loading. This model captures the structural response without the need for calibration of experimentally determined material parameters. When used in the design of energy absorbing composite structures, it can reduce the dependence on physical testing. This paper validates this model against experimental data obtained from the literature and in-house testing. Results show that the model can predict the force response of the crushed composite structures with good accuracy. The simulated energy absorption in each test case was within 12% of the experimental value. Post-crush deformation and the damage morphologies, such as ply splitting, splaying and breakage, were also accurately reproduced. This study establishes the capability of this damage model for predicting the responses of composite structures under crushing loads.

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For those working in the humanitarian sector, achieving positive outcomes for postdisaster communities through reconstruction projects is a pressing concern. In the wake of recent natural disasters, NGOs have become increasingly involved in the permanent reconstruction of affected communities. They have encountered significant barriers as they implement reconstruction programmes and this paper argues that it is important to address the visible lack of innovation that is partially to blame. The theoretical bedrock of a current research project will be used as the starting point for this argument, the overall goal of which is to design a competency-based framework model that can be used by NGOs in post-disaster reconstruction projects. Drawing on established theories of management, a unique perspective has been developed from which a competency-based reconstruction theory emerges. This theoretical framework brings together 3 distinct fields; Disaster Management, Strategic Management and Project Management, each vital
to the success of the model. The objectives of this paper are a) to investigate the role of NGOs in post-disaster reconstruction and establish the current standard of practice b) to determine the extent to which NGOs have the opportunity to contribute to sustainable community development through reconstruction c) to outline the main factors of a theoretical framework first proposed by Von Meding et al. 2009 and d) to identify the innovative measures that can be taken by NGOs to achieve more positive outcomes in their interventions. It is important that NGOs involved in post-disaster reconstruction become familiar with concepts and strategies such as those contained in this paper. Competency-based organizational change on the basis of this theory has the potential to help define the standard of best practice to which future NGO projects might align themselves.

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A integração das novas tecnologias de informação e comunicação no contexto educativo proporcionou a emergência de novos cenários de ensino e aprendizagem onde o EaD online é parte integrante. Esta realidade, recentemente implementada na Universidade Eduardo Mondlane (UEM), demanda que os professores estejam preparados com conhecimentos e competências para atuarem com sucesso no EaD online. O maior desafio que surge é como tornar o professor presencial num professor online efetivo pelo facto de muitos deles desenvolverem atitudes de resistência em relação ao EaD, permanecendo ligados às formas tradicionais de ensino. O objetivo deste estudo é conceber, implementar e avaliar um modelo de desenvolvimento profissional dos professores para o EaD, da UEM, por recurso às novas TIC que possibilite a aquisição de competências pedagógicas e tecnológicas para ensinarem em ambientes de ensino e aprendizagem online e integrarem as novas TIC no ensino presencial. Como metodologia, trata-se de um estudo de caso qualitativo, com a unidade de análise “O desenvolvimento profissional do professor para o EaD”, baseado no paradigma interpretativo, com uma vertente de investigação-ação. O estudo foi realizado na UEM, Moçambique, onde foram analisadas duas ações de formação, na modalidade de blended learning com recurso a uma plataforma LMS denominada Aulanet, e envolveu 16 professores de diferentes áreas disciplinares. Os dados foram recolhidos através de inquéritos por questionário e entrevista, do diário e de documentos eletrónicos como mensagens de fórum de debate, de chat, de correio interno e do skype. A técnica de análise de conteúdo foi utilizada para o tratamento de dados qualitativos, com suporte do Nvivo8, e os dados quantitativos recorreram ao Excel. Os resultados do estudo mostraram que a inserção dos professores num ambiente virtual permitiu mudarem de atitudes em relação ao EaD e às TIC, adoptarem estratégias pedagógicas para lidar com certos aspetos do ensino online e aprenderem a utilizar as ferramentas do EaD de modo apropriado.