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Application of Rough Set, GSM and MSM to Analyze Learning Outcome—An Example of Introduction to Education 被引量:1
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作者 Hui-Chung Ho Woody Jann-Der Fann +4 位作者 Hsiu-Jye Chiang Phung-Tuyen Nguyen Duc-Hieu Pham Phuoc-Hai Nguyen masatake nagai 《Journal of Intelligent Learning Systems and Applications》 2016年第1期23-38,共16页
Introduction to education is one of the basic courses in teacher education professional education, it covers a wide range of subjects. Thus, in order to practice the management teaching goals, the interdisciplinary de... Introduction to education is one of the basic courses in teacher education professional education, it covers a wide range of subjects. Thus, in order to practice the management teaching goals, the interdisciplinary developed mathematical tools are applied for the study. The participants of this study are students in course of introduction to education, and the research instruments applied are rough set, grey structural modeling (GSM), and matrix based-structural modeling (MSM). The purposes of this paper are: 1) To logically analyze educational datasets to practice the scientific traits in education;2) To benefit from directed hierarchical analysis to identify and propose action planning;3) To construct core-oriented educational structure as the criterion-reference for one-lesson-multiple-design and to provide the whole scope and visualized analysis with GSM and MSM. 展开更多
关键词 Introduction to Education Rough Set GSM MSM One-Lesson-Multiple-Design
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Analysis of Students’ Misconception Based on Rough Set Theory
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作者 Tian-Wei Sheu Tzu-Liang Chen +3 位作者 Ching-Pin Tsai Jian-Wei Tzeng Cing-Ping Deng masatake nagai 《Journal of Intelligent Learning Systems and Applications》 2013年第2期67-83,共17页
The study analyzed students’ misconception based on rough set theory and combined with interpretive structural model (ISM) to compare students’ degree of two classes. The study then has provided an effective diagnos... The study analyzed students’ misconception based on rough set theory and combined with interpretive structural model (ISM) to compare students’ degree of two classes. The study then has provided an effective diagnostic assessment tool for teachers. The participants were 30 fourth grade students in Central Taiwan, and the exam tools were produced by teachers for math exams. The study has proposed three methods to get common misconception of the students in class. These methods are “Deleting conditional attributes”, “Using Boolean logic to calculate discernable matrix”, and “Calculating significance of conditional attributes.” The results showed that students of Class A had common misconceptions but students of Class B had not common misconception. In addition, the remedial decision-making for these two classes of students is pointed out. While remedial decision-making of two classes corresponded to structural graph of concepts, it can be found the overall performance of the Class B was higher than Class A. 展开更多
关键词 MISCONCEPTION ROUGH Set Theory Interpretive STRUCTURAL Model DIAGNOSTIC Assessment STRUCTURAL GRAPH
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