175,894 research outputs found

    Urban Data in the primary classroom: bringing data literacy to the UK curriculum

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    As data becomes established as part of everyday life, the ability for the average citizen to have some level of data literacy is increasingly important. This paper describes an approach to teaching data skills in schools using real life, complex, urban data sets collected as part of a smart city project. The approach is founded on the premise that young learners have the ability to work with complex data sets if they are supported in the right way and if the tasks are grounded in a real life context. Narrative principles are used to frame the task, to assist interpretation and tell stories from data and to structure queries of datasets. An inquiry-based methodology organises the activities. This paper describes the initial trial in a UK primary school in which twelve students aged 9-10 years learnt about home energy consumption and the generation of solar energy from home solar PV, by interpreting existing visualisations of smart meter data and data obtained from aerial survey. Additional trials are scheduled with older learners which will evaluate learners on more challenging data handling tasks. The trials are informing the development of the Urban Data School, a web-based platform designed to support teaching data skills in schools in order to improve data literacy among school leavers

    The Australian science curriculum

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    The Australian Science Curriculum has appeared at a time when there is widespread concern for the quality of science teaching and learning in Australia and the engagement of students in learning science, leading to calls for significant reform. The new curriculum thus carries the hopes of reform-minded scientists and educators for a change in the way science in schools can support teaching practices that engage students in quality learning. This analysis will examine whether it is an adequate vehicle for doing this. Will it live up to our expectations?<br /

    Creating an Understanding of Data Literacy for a Data-driven Society

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    Society has become increasingly reliant on data, making it necessary to ensure that all citizens are equipped with the skills needed to be data literate. We argue that the foundations for a data literate society begin by acquiring key data literacy competences in school. However, as yet there is no clear definition of what these should be. This paper explores the different perspectives currently offered on both data and statistical literacy and then critically examines to what extent these address the data literacy needs of citizens in today’s society. We survey existing approaches to teaching data literacy in schools, to identify how data literacy is interpreted in practice. Based on these analyses, we propose a definition of data literacy that is focused on employing an inquiry-based approach to using data to understand real world phenomena. The contribution of this paper is the creation of a common foundation for teaching and learning data literacy skills

    Harnessing Technology: new modes of technology-enhanced learning: opportunities and challenges

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    A report commissioned by Becta to explore the potential impact on education, staff and learners of new modes of technology enhanced learning, envisaged as becoming available in subsequent years. A generative framework, developed by the researchers is described, which was used as an analytical tool to relate the possibilities of the technology described to learning and teaching activities. This report is part of the curriculum and pedagogy strand of Becta's programme of managed research in support of the development of Harnessing Technology: Next Generation Learning 2008-14. A system-wide strategy for technology in education and skills. Between April 2008 and March 2009, the project carried out research, in three iterative phases, into the future of learning with technology. The research has drawn from, and aims to inform, all UK education sectors

    Connecting teachers and students with science and scientists: The science learning hub

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    National and international data is raising concerns about levels of student interest and engagement in science in school and student retention into tertiary study. For today’s students the Internet plays an important role as a source of information and means for communication with peers. This paper reports on a Ministry of Research Technology and Science funded initiative, managed through The University of Waikato, that aims to make New Zealand science research more accessible to New Zealand teachers and students. The New Zealand Science Learning Hub [SLH] illustrates how effective collaboration between research organisations, industries, science educators and teachers has enabled the development of a resource which is dynamic, up-to-date and relevant and that can be used to inform the teaching of science in New Zealand schools. The Science Learning Hub provides teachers with information about current research, which is related to concepts currently taught in year 5-10 classes (8-14 year olds). The site has content arranged in contexts for example, Icy ecosystems, Hidden taonga, Nanoscience, You me and UV, Future fuels, and The see through body. Each context includes text and images describing NZ research, video material such as interviews with scientists and sequences depicting scientists at work, teaching and learning materials, and links to science education literature. A feature is a “connections tool” which allows teachers and students to trace their journey through each context. Initial research indicates that teachers appreciate that this range of information is accessible in one place and has been quality assured. Students are keen to engage with an actively explore the range of media within the SLH contexts

    Science in the New Zealand Curriculum e-in-science

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    This milestone report explores some innovative possibilities for e-in-science practice to enhance teacher capability and increase student engagement and achievement. In particular, this report gives insights into how e-learning might be harnessed to help create a future-oriented science education programme. “Innovative” practices are considered to be those that integrate (or could integrate) digital technologies in science education in ways that are not yet commonplace. “Future-oriented education” refers to the type of education that students in the “knowledge age” are going to need. While it is not yet clear exactly what this type of education might look like, it is clear that it will be different from the current system. One framework used to differentiate between these kinds of education is the evolution of education from Education 1.0 to Education 2.0 and 3.0 (Keats & Schmidt, 2007). Education 1.0, like Web 1.0, is considered to be largely a one-way process. Students “get” knowledge from their teachers or other information sources. Education 2.0, as defined by Keats and Schmidt, happens when Web 2.0 technologies are used to enhance traditional approaches to education. New interactive media, such as blogs, social bookmarking, etc. are used, but the process of education itself does not differ significantly from Education 1.0. Education 3.0, by contrast, is characterised by rich, cross-institutional, cross-cultural educational opportunities. The learners themselves play a key role as creators of knowledge artefacts, and distinctions between artefacts, people and processes become blurred, as do distinctions of space and time. Across these three “generations”, the teacher’s role changes from one of knowledge source (Education 1.0) to guide and knowledge source (Education 2.0) to orchestrator of collaborative knowledge creation (Education 3.0). The nature of the learner’s participation in the learning also changes from being largely passive to becoming increasingly active: the learner co-creates resources and opportunities and has a strong sense of ownership of his or her own education. In addition, the participation by communities outside the traditional education system increases. Building from this framework, we offer our own “framework for future-oriented science education” (see Figure 1). In this framework, we present two continua: one reflects the nature of student participation (from minimal to transformative) and the other reflects the nature of community participation (also from minimal to transformative). Both continua stretch from minimal to transformative participation. Minimal participation reflects little or no input by the student/community into the direction of the learning—what is learned, how it is learned and how what is learned will be assessed. Transformative participation, in contrast, represents education where the student or community drives the direction of the learning, including making decisions about content, learning approaches and assessment
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