29,054 research outputs found

    ‘A double-edged sword. This is powerful but it could be used destructively’: Perspectives of early career education researchers on learning analytics

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    Learning analytics has been increasingly outlined as a powerful tool for measuring, analysing, and predicting learning experiences and behaviours. The rising use of learning analytics means that many educational researchers now require new ranges of technical analytical skills to contribute to an increasingly data-heavy field. However, it has been argued that educational data scientists are a ‘scarce breed’ (Buckingham Shum et al., 2013) and that more resources are needed to support the next generation of early career researchers in the education field. At the same time, little is known about how early career education researchers feel towards learning analytics and whether it is important to their current and future research practices. Using a thematic analysis of a participatory learning analytics workshop discussions with 25 early career education researchers, we outline in this article their ambitions, challenges and anxieties towards learning analytics. In doing so, we have provided a roadmap for how the learning analytics field might evolve and practical implications for supporting early career researchers’ development

    Study design and protocol for a mixed methods evaluation of an intervention to reduce and break up sitting time in primary school classrooms in the UK: the CLASS PAL (Physically Active Learning) Programme

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    Introduction: Children engage in a high volume of sitting in school, particularly in the classroom. A number of strategies, such as physically active lessons (termed movement integration (MI)), have been developed to integrate physical activity into this learning environment; however, no single approach is likely to meet the needs of all pupils and teachers. This protocol outlines an implementation study of a primary school-based MI intervention: CLASS PAL (Physically Active Learning) programme. This study aims to (A) determine the degree of implementation of CLASS PAL, (B) identify processes by which teachers and schools implement CLASS PAL and (C) investigate individual (pupil and teacher) level and school-level characteristics associated with implementation of CLASS PAL. Methods and analysis: The intervention will provide teachers with a professional development workshop and a bespoke teaching resources website. The study will use a single group before-and-after design, strengthened by multiple interim measurements. Six state-funded primary schools will be recruited within Leicestershire, UK. Evaluation data will be collected prior to implementation and at four discrete time points during implementation: At measurement 0 (October 2016), school, teacher and pupil characteristics will be collected. At measurements 0 and 3 (June-July 2017), accelerometry, cognitive functioning, self-reported sitting and classroom engagement data will be collected. At measurements 1(December 2016-March 2017) and 3, teacher interviews (also at measurement 4; September-October 2017) and pupil focus groups will be conducted, and at measurements 1 and 2 (April-May 2017), classroom observations. Implementation will be captured through website analytics and ongoing teacher completed logs. Ethics and dissemination: Ethical approval was obtained through the Loughborough University Human Participants Ethics Sub-Committee (Reference number: R16-P115). Findings will be disseminated via practitioner and/or research journals and to relevant regional and national stakeholders through print and online media and dissemination event(s)

    The Evidence Hub: harnessing the collective intelligence of communities to build evidence-based knowledge

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    Conventional document and discussion websites provide users with no help in assessing the quality or quantity of evidence behind any given idea. Besides, the very meaning of what evidence is may not be unequivocally defined within a community, and may require deep understanding, common ground and debate. An Evidence Hub is a tool to pool the community collective intelligence on what is evidence for an idea. It provides an infrastructure for debating and building evidence-based knowledge and practice. An Evidence Hub is best thought of as a filter onto other websites — a map that distills the most important issues, ideas and evidence from the noise by making clear why ideas and web resources may be worth further investigation. This paper describes the Evidence Hub concept and rationale, the breath of user engagement and the evolution of specific features, derived from our work with different community groups in the healthcare and educational sector
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