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Automatic Classification for Cognitive Engagement in Online Discussion Forums: Text Mining and Machine Learning Approach

For effective learning, students must set learning objectives and adopt the ad hoc cognitive behavior to achieve them. Our research work aims to ensure good scaffolding by offering tutors the opportunity to observe learners’ cognitive behaviors, especially their cognitive engagement. In this respect...

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Detalles Bibliográficos
Autores principales: Hayati, Hind, Khalidi Idrissi, Mohammed, Bennani, Samir
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334702/
http://dx.doi.org/10.1007/978-3-030-52240-7_21
Descripción
Sumario:For effective learning, students must set learning objectives and adopt the ad hoc cognitive behavior to achieve them. Our research work aims to ensure good scaffolding by offering tutors the opportunity to observe learners’ cognitive behaviors, especially their cognitive engagement. In this respect, we propose in the present work an automatic system for classifying learners according to their levels of cognitive engagement. To this end, we focus on the analysis of social interactions within online discussion forums. Hence, the proposed system has two main steps: 1/Learners’ vector construction and 2/SVM-based classifier. The results show the efficiency of the proposed system with an accuracy = 0.9 and a cohen’s K = 0.89.