The correlation analysis of learners' characteristics

• Main Authors: Chiu, ShangYun, 邱上勻
• Other Authors: Lin, YuTzu
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/93764795487159599157

碩士 === 國立暨南國際大學 === 資訊工程學系 === 99 === With the rapid development of information and network technology, web-based learning becomes a new trend of learning. In the on-line learning environment, adaptability is an important issue for the purpose of providing suitable functions or content for different learners for effective learning. However, most on-line learning systems collect only general personal attributes from the input form, but not include learning characteristics, which cannot provide sufficient information for adaptive learning. In order to mine the learning characteristics of students from general user information, this study provide a correlation analysis of various characteristics of learners for understanding the relationships between different user information, so that useful learning characteristics can be found through general personal attributes. The learner characteristics considered in this work include blood types, constellations, sex, assessment results, assessment answering types, and learning styles. For sequential scalar data, many existing correlation metrics can be applied to analysis them. However, some data contain non-sequential elements or vectors. Therefore, we propose a correlation analysis mechanism to understand relationships between non-sequential or vector data. The features are classified by the Self Organizing Map at first, and then the correlations are estimated by discussing the between-group and within-group distribution based on histogram-based analysis, feature ratio analysis, and principal component analysis. At last, the produced correlation analysis results are visualized to provide teachers with a correlation map for improving their teaching.