384 resultados para 319.237
Thinking like Disney: Supporting the Disney method using ambient feedback based on group performance
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The Disney method is a collaborative creativity technique that uses three roles - dreamer, realist and critic - to facilitate the consideration of different perspectives on a topic. Especially for novices it is important to obtain guidance in applying this method. One way is providing groups with a trained moderator. However, feedback about the group’s behavior might interrupt the flow of the idea finding process. We built and evaluated a system that provides ambient feedback to a group about the distribution of their statements among the three roles. Our preliminary field study indicates that groups supported by the system contribute more and roles are used in a more balanced way while the visualization does not disrupt the group work.
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In [8] the authors developed a logical system based on the definition of a new non-classical connective ⊗ capturing the notion of reparative obligation. The system proved to be appropriate for handling well-known contrary-to-duty paradoxes but no model-theoretic semantics was presented. In this paper we fill the gap and define a suitable possible-world semantics for the system for which we can prove soundness and completeness. The semantics is a preference-based non-normal one extending and generalizing semantics for classical modal logics.
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Non-monotonic reasoning typically deals with three kinds of knowledge. Facts are meant to describe immutable statements of the environment. Rules define relationships among elements. Lastly, an ordering among the rules, in the form of a superiority relation, establishes the relative strength of rules. To revise a non-monotonic theory, we can change either one of these three elements. We prove that the problem of revising a non-monotonic theory by only changing the superiority relation is a NP-complete problem.
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The current research began from the starting point that what we are grappling with when we are dealing with violent extremists by and large is essentially ‘normal people’. What follows in this third major section of this research paper is the theoretical and conceptual search for making researchable the following question: ‘How do you assess someone who is normal?’
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Reconstructing 3D motion data is highly under-constrained due to several common sources of data loss during measurement, such as projection, occlusion, or miscorrespondence. We present a statistical model of 3D motion data, based on the Kronecker structure of the spatiotemporal covariance of natural motion, as a prior on 3D motion. This prior is expressed as a matrix normal distribution, composed of separable and compact row and column covariances. We relate the marginals of the distribution to the shape, trajectory, and shape-trajectory models of prior art. When the marginal shape distribution is not available from training data, we show how placing a hierarchical prior over shapes results in a convex MAP solution in terms of the trace-norm. The matrix normal distribution, fit to a single sequence, outperforms state-of-the-art methods at reconstructing 3D motion data in the presence of significant data loss, while providing covariance estimates of the imputed points.
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This volume captures the innovative, theory-based, and grounded work being done by established scholars who are interrogating how teacher education can prepare teachers to work in challenging and diverse high-poverty settings. It offers articles from the US, Australia, Canada, the UK and Chile by some of the most significant scholars in the field. Internationally, research suggests that effective teachers for high poverty schools require deep theoretical understanding as well as the capacity to function across three well-substantiated areas: deep content knowledge, well-tuned pedagogical skills, and demonstrated attributes that prove their understanding and commitment to social justice. Schools in low socioeconomic communities need quality teachers most, however, they are often staffed by the least experienced and least prepared teachers. The chapters in this volume examine how pre-service teachers are taught to understand the social contexts of education. Drawing on the individual expertise of the authors, the topics covered include unpacking poverty for pre-service teachers, issues related to urban schooling as well as remote and regional area schooling.
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This introduction to the book Teacher Education for High Poverty Schools provides an international snapshot of important advances in both theory and practice related to the preparation of teachers for high poverty schools. This collection brings together some of the most significant researchers in the field of teacher education for high poverty schools and it is our hope that the book serves as testament to a diverse range of successful attempts to address key aspects within teacher education. Representing the US, Canada, Australia, Chile, South Africa and the UK, this collection profiles an assortment of theory, ideas and approaches from a range of countries.
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This chapter aims to provide a comprehensive understanding of the theory, regulations and practice of corporate social responsibility (CSR) assurance in China. Built on stakeholder and related theories, it employs a demand-and-supply analytical framework to illustrate the development and current status of China’s CSR assurance market. It finds that government agencies, stock exchanges, accounting standard setters and industrial associations have collectively shaped the current regulatory framework on CSR reporting and assurance in China. Regarding demand, differences in the social and legal environments across such a large country influence the regional development of CSR assurance. Industries under intensive CSR regulations and/or social reporting pressure—for example, the finance, aviation and mining industries—more actively achieve CSR report assurance. Regarding supply, the CSR assurance market in China is shared by accounting firms and professional certification bodies. Different assurance standards adopted by the two streams of assurance providers have different foci, potentially leading to different assurance coverage and emphases.
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Welcome to this special edition of the Journal of Learning Design which focuses on legal education and curriculum renewal in law. At the outset ,we would like to thank the editors of the Journal, Margaret Lloyd and Nan Bahr for agreeing to host this special edition. The special edition is timely as legal education in Australia is enjoying a lively period of renewal.
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• As part of the 3E program, we conducted a systematic literature review and gathered consensus from 23 practising Australian rheumatologists to develop guidelines for early identification of ankylosing spondylitis and specialist referral. • In three rounds of break-out sessions followed by discussion and voting, the specialist panel addressed three questions related to diagnosis of ankylosing spondylitis: In individuals with back pain, what are the early clinical features that suggest ankylosing spondylitis? How useful is imaging in identifying early ankylosing spondylitis? Based on which clinical features should a general practitioner refer a patient to a rheumatologist for further evaluation? • The panel agreed on six recommendations related to the three questions: 1a. Early clinical features to suggest ankylosing spondylitis include inflammatory back pain and age at symptom onset < 45 years. 1b. The absence of symptomatic response to an appropriate course of non-steroidal anti-inflammatory drugs makes the diagnosis of ankylosing spondylitis less likely. 1c. Raised inflammatory markers are supportive, but their absence does not rule out the diagnosis of ankylosing spondylitis. 2a. Despite low sensitivity to detect changes of early ankylosing spondylitis, plain radiographs of the pelvis and spine are appropriate initial imaging techniques. 2b. Magnetic resonance imaging is a useful imaging modality for detecting early changes of ankylosing spondylitis. 3. Individuals with inflammatory back pain should be referred to a rheumatologist for further evaluation. • Effective dissemination and implementation of these recommendations are important to standardise the approach to early diagnosis of ankylosing spondylitis.
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It is well known that different arguments appeal to different people. We all process information in ways that are adapted to be consistent with our underlying ideologies. These ideologies can sometimes be framed in terms of particular axes or dimensions, which makes it possible to represent some aspects of an ideology as a region in the kind of vector space that is typical of many generalised quantum models. Such models can then be used to explain and predict, in broad strokes, whether a particular argument or proposal is likely to appeal to an individual with a particular ideology. The choice of suitable arguments to bring about desired actions is traditionally part of the art or science of rhetoric, and today's highly polarised society means that this skill is becoming more important than ever. This paper presents a basic model for understanding how different goals will appeal to people with different ideologies, and thus how different rhetorical positions can be adopted to promote the same desired outcome. As an example, we consider different narratives and hence actions with respect to the environment and climate change, an important but currently highly controversial topic.
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Much of the work currently occurring in the field of Quantum Interaction (QI) relies upon Projective Measurement. This is perhaps not optimal, cognitive states are not nearly as well behaved as standard quantum mechanical systems; they exhibit violations of repeatability, and the operators that we use to describe measurements do not appear to be naturally orthogonal in cognitive systems. Here we attempt to map the formalism of Positive Operator Valued Measure (POVM) theory into the domain of semantic memory, showing how it might be used to construct Bell-type inequalities.
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When a puzzle game is created, its design parameters must be chosen to allow solvable and interesting challenges to be created for the player. We investigate the use of random sampling as a computationally inexpensive means of automated game analysis, to evaluate the BoxOff family of puzzle games. This analysis reveals useful insights into the game, such as the surprising fact that almost 100% of randomly generated challenges have a solution, but less than 10% will be solved using strictly random play, validating the inventor’s design choices. We show the 1D game to be trivial and the 3D game to be viable.