Developing argumentation processing agents for computer-supported collaborative learning

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摘要

In this study, an intelligent argumentation processing agent for computer-supported cooperative learning is proposed. Learners are first assigned to heterogeneous groups based on their learning styles questionnaire given right before the beginning of learning activities on the e-learning platform. The proposed argumentation processing agent then scrutinizes each learner’s learning portfolio on e-learning platform and automatically issues feedback messages in case devious argument or abnormal behavior that is unfitted to the learners’ learning style is detected. The Moodle (http://moodle.org), an open source software e-learning platform, is used to establish the cooperative learning environment for this study. The experimental results revealed that the learners benefited by the argumentation activity with the assistance of the proposed learning style aware argumentation processing agent.

论文关键词:Argumentation,Conversation analysis,Text mining,Exception maximum (EM),Assessment,e-Learning,Learning style

论文评审过程:Available online 9 February 2008.

论文官网地址:https://doi.org/10.1016/j.eswa.2008.01.036