Volume 8 Number 5 (May 2013)
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JCP 2013 Vol.8(5): 1255-1266 ISSN: 1796-203X
doi: 10.4304/jcp.8.5.1255-1266

Study on the Conception of Learning Problems of Students by Combining the Misconception Domain and Structural Analysis Methods

Tian-Wei Sheu, Tzu-Liang Chen, Jian-Wei Tzeng, Ching-Pin Tsai, and Masatake Nagai
Graduate Institute of Educational Measurement and Statistics, National Taichung University of Education, Taichung, Taiwan

Abstract—The purpose of this paper was to analyze the structure of difficult concepts learning within the classroom. The sample of the study was 18 fourth grade students in Central Taiwan, and the exam tools were produced by teachers for math exams. In this paper, a combination of the Rasch Model GSP chart analysis theory, the misconception domain, the Interpretive Structural Modeling (ISM) and Grey Structural Model (GSM) was used. The results are as follows: (1) Based on the change in students’ average grade and the difficulty between problems of Rasch Line = 0.5, the effect of the remedial teaching will be known. (2) Through the GSM structural graphs, the misconception domain structure of students can be identified. (3) The problemconcept relationship of misconception domain can reveal the structure of misconceptions through the GSM structural graph. This structure is capable of identifying the learning sequence of the difficult concepts. (4) Upon comparing the GSM structural graph of misconception domain before and after remedial teaching, it became clear which concepts made learning more effective, and which concepts needed to be developed more. (5) The research method for a small amount of people and problems can still systematic point out the structure of concepts which need in this class.

Index Terms—Rasch Model GSP chart, Misconception Domain, ISM, GSM, the structure of conceptions

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Cite: Tian-Wei Sheu, Tzu-Liang Chen, Jian-Wei Tzeng, Ching-Pin Tsai, and Masatake Nagai, " Study on the Conception of Learning Problems of Students by Combining the Misconception Domain and Structural Analysis Methods," Journal of Computers vol. 8, no. 5, pp. 1255-1266, 2013.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat,etc
E-mail: jcp@iap.org
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