Applying Learning Portfolios and Thinking Styles to Adaptive Remedial Learning

• Main Authors: CHEN CHIEN-MING, 陳建銘
• Other Authors: Bin-Shyan Jong
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/97519015956097432785

碩士 === 中原大學 === 資訊工程研究所 === 95 === Online learning is different from the instruction provided in traditional classroom lecturing where the teachers and students cannot have actual contact. Thus, the teachers can have little control over the students’ learning situations. However, the teachers can observe the students’ learning activities by analyzing their online learning portfolios, understand students’ learning activities further, and then provide remedial instruction to students who have bad learning situations. Online learning portfolios are complex row data, it will cost much time for observation. So, this study uses data mining algorithm to analyze students’ online learning portfolios,and provide effective information to teachers. This study uses cluster analysis to categorized students with similar learning behaviors into the same group. This study aims at sending adaptive warning messages according to different students’ learning activities, demonstrates the relation between warning message and learning performance. This study used ANOVA evaluation to analyze the relation of students’ learning activities、learning performance and adaptive warning message. Obtaining students’ learning model by observing student’s learning activities, thinking styles and adaptive warning message. The correlations between these factors are also considered. This study implements learning portfolio diagnostic system to handle complex online learning portfolios.Thus, the students’ learning situations can be revealed by the aids of the online learning portfolio diagnostic system. Therefore, the system provides teachers interface to import additional students and curricular information, such as curricular schedule roll call data. By using this system, teachers can observe students’ learning activities and variations, and further find the relations of learning activities and learning performance .