39 research outputs found

    Assessments Related to the Physical, Affective and Cognitive Domains of Physical Literacy Amongst Children Aged 7–11.9 Years: A Systematic Review

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    Background Over the past decade, there has been increased interest amongst researchers, practitioners and policymakers in physical literacy for children and young people and the assessment of the concept within physical education (PE). This systematic review aimed to identify tools to assess physical literacy and its physical, cognitive and affective domains within children aged 7–11.9 years, and to examine the measurement properties, feasibility and elements of physical literacy assessed within each tool. Methods Six databases (EBSCO host platform, MEDLINE, PsycINFO, Scopus, Education Research Complete, SPORTDiscus) were searched up to 10th September 2020. Studies were included if they sampled children aged between 7 and 11.9 years, employed field-based assessments of physical literacy and/or related affective, physical or cognitive domains, reported measurement properties (quantitative) or theoretical development (qualitative), and were published in English in peer-reviewed journals. The methodological quality and measurement properties of studies and assessment tools were appraised using the COnsensus-based Standards for the selection of health Measurement INstruments risk of bias checklist. The feasibility of each assessment was considered using a utility matrix and elements of physical literacy element were recorded using a descriptive checklist. Results The search strategy resulted in a total of 11467 initial results. After full text screening, 11 studies (3 assessments) related to explicit physical literacy assessments. Forty-four studies (32 assessments) were relevant to the affective domain, 31 studies (15 assessments) were relevant to the physical domain and 2 studies (2 assessments) were included within the cognitive domain. Methodological quality and reporting of measurement properties within the included studies were mixed. The Canadian Assessment of Physical Literacy-2 and the Passport For Life had evidence of acceptable measurement properties from studies of very good methodological quality and assessed a wide range of physical literacy elements. Feasibility results indicated that many tools would be suitable for a primary PE setting, though some require a level of expertise to administer and score that would require training. Conclusions This review has identified a number of existing assessments that could be useful in a physical literacy assessment approach within PE and provides further information to empower researchers and practitioners to make informed decisions when selecting the most appropriate assessment for their needs, purpose and context. The review indicates that researchers and tool developers should aim to improve the methodological quality and reporting of measurement properties of assessments to better inform the field. Trial registration PROSPERO: CRD4201706221

    Uncertain<t>: A first-order type for uncertain data. In

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    Abstract Sampled data from sensors, the web, and people is inherently probabilistic. Because programming languages use discrete types (floats, integers, and booleans), applications, ranging from GPS navigation to web search to polling, express and reason about uncertainty in idiosyncratic ways. This mismatch causes three problems. (1) Using an estimate as a fact introduces errors (walking through walls). (2) Computation on estimates compounds errors (walking at 59 mph). (3) Inference asks questions incorrectly when the data can only answer probabilistic question (e.g., "are you speeding?" versus "are you speeding with high probability"). This paper introduces the uncertain type (Uncertain T ), an abstraction that expresses, propagates, and exposes uncertainty to solve these problems. We present its semantics and a recipe for (a) identifying distributions, (b) computing, (c) inferring, and (d) leveraging domain knowledge in uncertain data. Because Uncertain T computations express an algebra over probabilities, Bayesian statistics ease inference over disparate information (physics, calendars, and maps). Uncertain T leverages statistics, learning algorithms, and domain expertise for experts and abstracts them for nonexpert developers. We demonstrate Uncertain T on two applications. The result is improved correctness, productivity, and expressiveness for probabilistic data

    The model is not enough: Understanding energy consumption in mobile devices

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    Although battery life has always constrained embedded and mobile hardware developers, the rise of smart phones and tablets has foisted energy as a fundamental constraint onto software developers. Whereas on the desktop, software developers mostl

    Detuned grating multi-section-RW-DFB-lasers for high speed optical signal processing

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    InGaAsP multisection-DFB-lasers with detuned gratings have been fabricated. Self-pulsation in the 40GHz range and the locking to data signals is demonstrated. Even higher self pulsation frequencies can be obtained based on the new concept
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