Item Dynamic Incremental Reduction Algorithm of Item Response System with Decision Item Based on Rough Set Theory

• Main Authors: Chou Shih-chung, 周世忠
• Other Authors: Liu Xiang-chuan
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/69931009534510039194

碩士 === 亞洲大學 === 資訊工程學系碩士在職專班 === 99 === Rough Set Theory is a new mathematical tool which deals with vagueness and uncertainty. Compared with other traditional theories, rough set theory does not need any data or extra informational hypotheses. In 2008, Liu Xiang-chuan first indicated that Item Response System based on Rough Set Theory can be applied to item reduction of test in a small class. The attribute reduction theory based on Item Dynamic Incremental Reduction Algorithm of Item Response System issued by Liu Xiang-chuan, Jian Mao-fa, Xu Tian-wei and Chou Shih-chung in 2010 went further to proposed that Attribute Incremental Dynamic Reduction Algorithm which combines conditional attribute and decisional attribute can be transformed and applied to Item Response System. This research has used Matlab language to write a program and employs Item Dynamic Incremental Reduction Algorithm of Item Response System with Decisional Item to amplify conditional item discriminating matrix into common discriminating matrix, which can take into consideration both conditional items and decisional items and at the same time adequately classifies the dynamically increased conditional items only when they qualify as decisional items. The results are stated as follows: 1. Design the application program of ‘Item Dynamic Incremental Reduction Algorithm of Item Response System with Decisional Item’. 2. Help the teachers preceding the retrieval teaching by using the program above to define the incremented items and judge them as necessary or not. 3. Help to establish the bank of duplicated or fundamental items used in tests in a small class.