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561.
O P Costa Leonardo Christine Chung-Wei Lin Debora Grossi Bevilaqua Marisa Cota Mancini Anne K Swisher Chad Cook Dan Vaughn Mark R Elkins Umer Sheikh Ann Moore Gwendolen Jull Rebecca L Craik Christopher G Maher Rinaldo Roberto de Jesus Guirro Amélia Pasqual Marques Michele Harms Dina Brooks Guy G Simoneau John Henry Strupstad 《Cardiopulmonary Physical Therapy Journal》2013,24(1):4-6
562.
Guy Cook 《通化师范学院学报》2009,(4)
There is a popular view that academic theory about language teaching has a disempowering effect upon language teachers,and cannot engage with the realities of the classroom.The view has been expressed in many different quarters,and in many different ways.No less a theorist than Noam Chomsky, 相似文献
563.
Latent Semantic Indexing (LSI) is a popular information retrieval model for concept-based searching. As with many vector space IR models, LSI requires an existing term-document association structure such as a term-by-document matrix. The term-by-document matrix, constructed during document parsing, can only capture weighted vocabulary occurrence patterns in the documents. However, for many knowledge domains there are pre-existing semantic structures that could be used to organize and categorize information. The goals of this study are (i) to demonstrate how such semantic structures can be automatically incorporated into the LSI vector space model, and (ii) to measure the effect of these structures on query matching performance. The new approach, referred to as Knowledge-Enhanced LSI, is applied to documents in the OHSUMED medical abstracts collection using the semantic structures provided by the UMLS Semantic Network and MeSH. Results based on precision-recall data (11-point average precision values) indicate that a MeSH-enhanced search index is capable of delivering noticeable incremental performance gain (as much as 35%) over the original LSI for modest constraints on precision. This performance gain is achieved by replacing the original query with the MeSH heading extracted from the query text via regular expression matches. 相似文献
564.
Our research project was guided by the assumption that students who learn to understand phenomena in everyday terms prior to being taught scientific language will develop improved understanding of new concepts. We used web‐based software to teach students using a “content‐first” approach that allowed students to transition from everyday understanding of phenomena to the use of scientific language. This study involved 49 minority students who were randomly assigned into two groups for analysis: a treatment group (taught with everyday language prior to using scientific language) and a control group (taught with scientific language). Using a pre–post‐test control group design, we assessed students' conceptual and linguistic understanding of photosynthesis. The results of this study indicated that students taught with the “content‐first” approach developed significantly improved understanding when compared to students taught in traditional ways. © 2008 Wiley Periodicals, Inc. J Res Sci Teach 45: 529–553, 2008 相似文献
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