Data mining in topology education: Rough set data analysis

被引：0

作者：

Narli, Serkan ^{[1
]}

Ozelik, Z. Ahmet ^{[2
]}

机构：

[1] Dokuz Eylul Univ, Fac Educ, Dept Primary Math Educ, Izmir, Turkey

[2] Dokuz Eylul Univ, Fac Sci, Dept Math Educ, Izmir, Turkey

来源：

INTERNATIONAL JOURNAL OF THE PHYSICAL SCIENCES | 2010年 / 5卷 / 09期

关键词：

Artificial Intelligence; rough sets; educational data mining; topology;

D O I：

暂无

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

This study explores rough sets, which provide mathematical description for uncertain concepts that can not be defined clearly by traditional logic. The study further examines data mining, which helps to discover meaningful information from large data sets by incorporating it with rough set theory. An investigation in topology instruction was undertaken to exemplify the usability of rough set theory in qualitative data analysis. The study provides an example of educational application of data mining in a topology course.

引用

页码：1428 / 1437

页数：10

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