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Are Automatically Identified Reading Strategies Reliable Predictors of Comprehension?

机译:自动识别的阅读策略是否是理解力的可靠预测指标?

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In order to build coherent textual representations, readers use cognitive procedures and processes referred to as reading strategies; these specific procedures can be elicited through self-explanations in order to improve understanding. In addition, when faced with comprehension difficulties, learners can invoke regulation processes, also part of reading strategies, for facilitating the understanding of a text. Starting from these observations, several automated techniques have been developed in order to support learners in terms of efficiency and focus on the actual comprehension of the learning material. Our aim is to go one step further and determine how automatically identified reading strategies employed by pupils with age between 8 and 11 years can be related to their overall level of understanding. Multiple classifiers based on Support Vector Machines are built using the strategies' identification heuristics in order to create an integrated model capable of predicting the learner's comprehension level.
机译:为了建立连贯的文本表示形式,读者使用认知程序和过程(称为阅读策略);这些特定的过程可以通过自我解释得出,以增进理解。此外,面对理解困难时,学习者可以调用调节过程(也是阅读策略的一部分)来促进对文本的理解。从这些观察结果出发,已经开发了几种自动化技术,以在效率方面为学习者提供支持,并专注于对学习材料的实际理解。我们的目标是更进一步,确定年龄在8至11岁之间的学生所采用的自动识别阅读策略如何与他们的整体理解水平相关。使用策略的识别启发法构建基于支持向量机的多个分类器,以创建能够预测学习者理解水平的集成模型。

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