DocumentCode
2134296
Title
Data Mining for Design Curriculum Development and Personalized Training Scheme
Author
Lifang Yang ; Yanping Fu ; Yong Wang ; Wenjiao Ding ; Shengfeng Qin
Author_Institution
Dept. of Ind. Design, Harbin Inst. of Technol., Harbin, China
fYear
2009
fDate
20-22 Sept. 2009
Firstpage
1
Lastpage
4
Abstract
There exit many problems in current industrial design teaching and learning for Chinese higher education. The aims and objectives of our research are to provide personalized training scheme for students through improving current curriculum. For the aim, the questionnaires are made to get information about design innovation and design innovative personal. Through data mining and PCA (principle component analysis) for the questionnaires, the innovation training archives is established on classifying different personality with respect to creativity and innovation. The questionnaires mainly contain innovation design factors, design course modules, design course activities, and design capabilities. Through design information mining, old curriculum problems are found and improved curriculum is designed. By the innovation training archives, personalized training scheme is to provide for the students to recommend relevant learning scheme.
Keywords
data mining; educational courses; principal component analysis; Chinese higher education; data mining; design capabilities; design course activities; design course modules; design curriculum development; industrial design learning; industrial design teaching; innovation design factors; personalized training scheme; principle component analysis; Curriculum development; Data mining; Education; Educational institutions; Educational products; Educational technology; Industrial training; Mining industry; Principal component analysis; Technological innovation;
fLanguage
English
Publisher
ieee
Conference_Titel
Management and Service Science, 2009. MASS '09. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-4638-4
Electronic_ISBN
978-1-4244-4639-1
Type
conf
DOI
10.1109/ICMSS.2009.5303309
Filename
5303309
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