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Full-Text Articles in Computer Sciences
Knowledge Extraction From Metacognitive Reading Strategies Data Using Induction Trees, Christopher Taylor, Arun D. Kulkarni, Kouider Mokhtari
Knowledge Extraction From Metacognitive Reading Strategies Data Using Induction Trees, Christopher Taylor, Arun D. Kulkarni, Kouider Mokhtari
Kouider Mokhtari
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, …
Assessing Metacognitive Skills Using Adaptive Neural Networks, Anderson Justin, Kouider Mokhtari, Arun Kulkarni
Assessing Metacognitive Skills Using Adaptive Neural Networks, Anderson Justin, Kouider Mokhtari, Arun Kulkarni
Kouider Mokhtari
The assessment of student's levels of metacognitive knowledge and skills is critical in determining their ability to effectively perform complex cognitive tasks such as solving mathematics or reading comprehension problems. In this paper, we use an adaptive multiplayer perceptron model to categorize participants based on their metacognitive awareness and perceived use of reading strategies while reading. Eight hundred and sixty-five middle school students participated in the study. All participants completed a 30-item instrument- the Metacognitive Awareness-of-Reading Strategies Inventory (MARSI). We used adaptive multi-layer perceptron models to classify participants into three groups based on their metacognitive strategy awareness levels using thirteen …