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Aspects of 'relevance' in the alignment of curriculum with educational standards

机译:课程与教育标准保持一致时的“相关性”方面

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With over 60,000 US K-12 science and mathematics education standards and a rapid proliferation of Web-enabled curriculum, retrieving curriculum that aligns with the standards to which teachers must teach is a key objective for educational digital libraries. However, previous studies of such alignment use single-dimensional and binary measures of the alignment concept. As a consequence, they suffer from low inter-rater reliability (IRR), with experts agreeing about alignments only some 20-40% of the time. We present the results of an experiment in which the alignment variable was operationalized using the Saracevic model of relevance 'clues' taken from the everyday practice of K-12 teaching. Results show high IRR across all clues with IRR on several specific alignment dimensions significantly higher than on overall alignment. In addition, a model of overall alignment is derived and estimated. The structure and explanatory power of the model as well as the relationships between alignment clues differ significantly between alignments of curriculum found by users themselves and curriculum found by others. These results illustrate the usefulness of clue-based relevance measures for information retrieval and have important consequences for both the formulation of automated retrieval mechanisms and the construction of a gold standard or benchmark set of standard-curriculum alignments.
机译:拥有超过60,000个美国K-12科学和数学教育标准,以及基于Web的课程的迅速普及,检索符合教师必须教授的标准的课程是教育数字图书馆的主要目标。但是,先前对这种对准的研究使用对准概念的一维和二元测量。结果,它们遭受评估者之间可靠性低(IRR)的困扰,专家们只在大约20%至40%的时间内同意对齐。我们提供了一个实验结果,其中使用从K-12教学的日常练习中获得的相关“线索”的Saracevic模型对比对变量进行了运算。结果显示,在所有线索上的IRR都很高,在多个特定比对尺寸上的IRR显着高于整体比对。另外,导出并估计整体对准的模型。该模型的结构和解释力以及对齐线索之间的关系在用户自己找到的课程与其他人找到的课程的对齐之间存在很大差异。这些结果说明了基于线索的相关性度量对于信息检索的有用性,并且对自动检索机制的制定以及金标准或标准课程路线的基准集的构建都具有重要意义。

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