Design and Implementation of an Intelligent Online Argumentation Assessment System

Autor: Chun-Hua Chen, 陳俊華
Rok vydání: 2009
Druh dokumentu: 學位論文 ; thesis
Popis: 97
Recent researches indicated that students’ ability to construct evidence based explanations in classrooms through scientific inquiry is critical to successful science education. Structured argumentation support environments have been built and used in scientific discourse in the literature. To the best our knowledge, no research work in the literature addressed the issue of automatically assessing the student’s argumentation quality. The teaching load of the teacher that uses the online argumentation support environments is not alleviated. In this work, an intelligent argumentation assessment system based on machine learning techniques for computer supported cooperative learning is proposed. Learners’ arguments on discussion board were examined by using argument element sequence to detect whether the learners address the expected discussion issues and to determine the argumentation level achieved by the learner’s argument. 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. A feedback rule construction mechanism is used to issue feedback messages to the learners in case the argumentation assessment system detects that the learners go in the biased direction or stay idle for a while. The Moodle, an open source software e-learning platform, is used to establish the cooperative learning environment for this study. The experimental results exhibit that the proposed work is effective in classifying each student’s argumentation level and assisting the students in learning the core concepts taught at a natural science course on the elementary school level.
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