Mining Learning Paths for Assessment of Online Learning Behavior

• Main Authors: Wen-Hsiang Tu, 涂文祥
• Other Authors: Shang-Hsien Hsieh
• Format: Others
• Language: zh-TW
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/69848224761203573833

碩士 === 國立臺灣大學 === 土木工程學研究所 === 91 === Learners’on-line learning paths are useful information for teachers to understand learners’learning behaviors. The information can then be used to help improving course arrangement and assessing students’ learning. In this research, the data mining technology is employed to process online learning records and find out leaning paths. Using a set of real learning records as an example, a data mining approach is proposed to filter out unimportant records then find out learning paths. Three kinds of learning paths, including growth of learning paths, difference of learning paths, and relationship between learning paths, are proposed and discussed in this thesis for assessment of online learning behavior. Keywords: learning behavior, data mining, learning path.