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A theoretical model of nonscience majors' motivation to learn science was tested by surveying 369 students in a large‐enrollment college science course that satisfies a core curriculum requirement. Based on a social‐cognitive framework, motivation to learn science was conceptualized as having both cognitive and affective influences that foster science achievement. Structural equation modeling was used to examine the hypothesized relationships among the variables. The students' motivation, as measured by the Science Motivation Questionnaire (SMQ), had a strong direct influence on their achievement, as measured by their science grade point average. The students' motivation was influenced by their belief in the relevance of science to their careers. This belief was slightly stronger in women than men. Essays by the students and interviews with them provided insight into their motivation. The model suggests that instructors should strategically connect science concepts to the careers of nonscience majors through such means as case studies to increase motivation and achievement. © 2006 Wiley Periodicals, Inc. J Res Sci Teach 44: 1088–1107, 2007  相似文献   
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  • Digitizing cultural heritage, humanities, content is currently being undertaken with institutional or government support but there are opportunities for greater library collaboration.
  • Using a crowdfunding model to support the creation of digitized collections empowers librarians but also challenges them to think like investors and publishers.
  • The described model creates an open access collection for the benefit of all scholars and also provides additional benefits for the participating libraries.
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We digitized three years of Dutch election manifestos annotated by the Dutch political scientist Isaac Lipschits. We used these data to train a classifier that can automatically label new, unseen election manifestos with themes. Having the manifestos in a uniform XML format with all paragraphs annotated with their themes has advantages for both electronic publishing of the data and diachronic comparative data analysis. The data that we created will be disclosed to the public through a search interface. This means that it will be possible to query the data and filter them on themes and parties. We optimized the Lipschits classifier on the task of classifying election manifestos using models trained on earlier years. We built a classifier that is suited for classifying election manifestos from 2002 onwards using the data from the 1980s and 1990s. We evaluated the results by having a domain expert manually assess a sample of the classified data. We found that our automatic classifier obtains the same precision as a human classifier on unseen data. Its recall could be improved by extending the set of themes with newly emerged themes. Thus when using old political texts to classify new texts, work is needed to link and expand the set of themes to newer topics.  相似文献   
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Supplemental reading instruction provides a way to improve the reading outcomes of students at risk for reading difficulties and to meet the challenges produced by increases in student diversity in today’s classrooms. The research–based intervention described in this article includes intensive, explicit, and systematic reading instruction in five areas: fluency, phonemic awareness, instructional–level reading with an emphasis on comprehension, word analysis, and spelling. This intervention was effective in improving the reading skills of low SES, second–grade English monolingual and English–language learners.  相似文献   
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A new set of standards to guide professional development in assessment among student affairs professionals and faculty members is poised to revolutionize how educators learn to conduct this essential work.  相似文献   
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