117,187 research outputs found

    A Scientist's Guide to Achieving Broader Impacts through K-12 STEM Collaboration.

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    The National Science Foundation and other funding agencies are increasingly requiring broader impacts in grant applications to encourage US scientists to contribute to science education and society. Concurrently, national science education standards are using more inquiry-based learning (IBL) to increase students' capacity for abstract, conceptual thinking applicable to real-world problems. Scientists are particularly well suited to engage in broader impacts via science inquiry outreach, because scientific research is inherently an inquiry-based process. We provide a practical guide to help scientists overcome obstacles that inhibit their engagement in K-12 IBL outreach and to attain the accrued benefits. Strategies to overcome these challenges include scaling outreach projects to the time available, building collaborations in which scientists' research overlaps with curriculum, employing backward planning to target specific learning objectives, encouraging scientists to share their passion, as well as their expertise with students, and transforming institutional incentives to support scientists engaging in educational outreach

    University Students Promoting Science in the Community

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    Project SEARCH (Science Education and Research for Children) has brought these undergraduate students here today. It is an outreach program designed to bring the science resources of a large research university to classrooms and community centers. For the past 9 years, SEARCH students have spent 4 hours each week doing hands-on-science experiments, dissecting frogs, demonstrating microscopes, lecturing about the planets, playing computer games, exploring the World Wide Web, and creating Web pages.published or submitted for publicationis peer reviewe

    Project- and Group-Based Learning of Junior Writing in Biology

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    Writing in Biology, part of the Junior Writing Program, is inherently a project-based learning course. After a Science, Technology, Engineering, and Mathematics Teacher Education Collaborative (STEMTEC) workshop, the course was thoroughly revised. Each of six projects was modified to increase student-active and group participation. Base groups with a balanced experience constitution are established using voluntary ordering and random assignment. A walk-around during the initial meeting serves to establish bonding within the base groups. Random groups are used within exercises to stimulate student interaction and familiarity with ad hoc group cooperation. Digital images of, and by, students are used to encourage student interaction and name recognition. A website with the entire course plan is available at an archival site to complement and help elucidate the course

    A Data Science Course for Undergraduates: Thinking with Data

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    Data science is an emerging interdisciplinary field that combines elements of mathematics, statistics, computer science, and knowledge in a particular application domain for the purpose of extracting meaningful information from the increasingly sophisticated array of data available in many settings. These data tend to be non-traditional, in the sense that they are often live, large, complex, and/or messy. A first course in statistics at the undergraduate level typically introduces students with a variety of techniques to analyze small, neat, and clean data sets. However, whether they pursue more formal training in statistics or not, many of these students will end up working with data that is considerably more complex, and will need facility with statistical computing techniques. More importantly, these students require a framework for thinking structurally about data. We describe an undergraduate course in a liberal arts environment that provides students with the tools necessary to apply data science. The course emphasizes modern, practical, and useful skills that cover the full data analysis spectrum, from asking an interesting question to acquiring, managing, manipulating, processing, querying, analyzing, and visualizing data, as well communicating findings in written, graphical, and oral forms.Comment: 21 pages total including supplementary material

    The research teaching nexus in the computing disciplines: a comparative survey

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    Many institutions make claims in strategy documents and official publications that students will receive an education which is research-led, research-informed, or guided by the scholarship of teaching and learning. Academics who teach regularly experience at first-hand the sometimes conflicting demands of research, teaching and supporting learning. Curricula guidelines are unlikely to help in developing any sophisticated understanding of ways in which research and teaching can be symbiotically applied, since such guidelines most typically deal with the content rather than the educational process experienced by our undergraduates. For these reasons an academic’s understanding of the research teaching nexus is more likely to be informed by their own workaday experience of designing and delivering educational experiences than from an analysis of the students’ perspective. If academics in the computing disciplines are to effectively deliver on their institutional missions to be scholarly, research-led or research-informed in their educational approaches, a clearer understanding of the possible meanings and implications of these terms in the context of the typical computing curricula would be of assistance. This paper presents and analyses the results of a survey conducted at two Universities which sought to identify how far their undergraduate curriculum was informed by research. This data is presented alongside qualitative data gathered from academics which explores their attitudes towards, and understanding of, the various terms commonly used to describe a research-informed approach to education in the computing disciplines
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