文章基本信息

标题：Knowledge Extraction from Metacognitive Reading Strategies Data Using Induction Trees
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作者：Christopher Taylor ; Arun Kulkarni ; Kouider Mokhtar 等
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2016
卷号：7
期号：6
DOI：10.14569/IJACSA.2016.070634
出版社：Science and Information Society (SAI)
摘要：The assessment of students’ metacognitive knowledge and skills about reading is critical in determining their ability to read academic texts and do so with comprehension. In this paper, we used induction trees to extract metacognitive knowledge about reading from a reading strategies dataset obtained from a group of 1636 undergraduate college students. Using a C4.5 algorithm, we constructed decision trees, which helped us classify participants into three groups based on their metacognitive strategy awareness levels consisting of global, problem-solving and support reading strategies. We extracted rules from these decision trees, and in order to evaluate accuracy of the extracted rules, we built a fuzzy inference system (FIS) with the extracted rules as a rule base and classified the test dataset with the FIS. The extracted rules are evaluated using measures such as the overall efficiency and Kappa coefficient
关键词：thesai; IJACSA; thesai.org; journal; IJACSA papers; Metacognitive Reading Strategies; Classification; Induction Tree; Rule Extraction; Fuzzy Inference System