The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS
Transactions ID Number: 89-810
Full Name: Yuan-Horng Lin
Position: Please, select:
Age: ON
Sex: Male
Address: 5F-3 26 Shanxi 2nd St., Taichung City
Country: TAIWAN
Tel: +886-4-22183515
Tel prefix:
Fax: +886-4-22938698
E-mail address: lyh@mail.ntcu.edu.tw
Other E-mails: lyh@ms3.ntcu.edu.tw
Title of the Paper: Integration of Item Hierarchy and Concept Tree based on Clustering Approach with Application in Statistics Learning
Authors as they appear in the Paper: Yuan-Horng Lin
Email addresses of all the authors: lyh@mail.ntcu.edu.tw
Number of paper pages: 11
Abstract: Item hierarchy and concept tree provide references for cognition diagnosis and remedial instruction. Therefore, integration of data analysis on item hierarchy and concept tree should be important. The purpose of this study is to provide an integrated methodology of item hierarchy and concept tree analysis. Besides, fuzzy clustering is adopted to classify sample so that homogeneity appear in the same cluster and adaptive instruction will be more feasible. Polytomous item relational structure (PIRS) is the foundation of item hierarchy analysis. Interpretive structural modeling (ISM) combined with calculation of ordering coefficient is to construct concept tree. Source data sets of PIRS and ISM are based on response data matrix and item-attribute matrix respectively. In this study, the empirical test data is the statistics assessment of university students. The results show that the integration of PIRS and ISM based on fuzzy clustering are useful for cognition diagnos!
is and adaptive instruction. Finally, further suggestions and recommendations based on findings are discussed.
Keywords: cognition diagnosis, concept tree, fuzzy clustering, ISM, item hierarchy, PIRS
EXTENSION of the file: .pdf
Special (Invited) Session: Clustering Approach to Polytomous IRS with Application in Statistics Learning for University Student
Organizer of the Session: 637-336
How Did you learn about congress: Jeng-Ming Yih ( yih@mail.ntcu.edu.tw ) , Berlin Wu ( berlin@nccu.edu.tw) , Sen-Chi Yu (rhine@mail.ntcu.edu.tw ), Wen-Liang Hung (wlhung@mail.nhcue.edu.tw)
IP ADDRESS: 114.41.127.170
