Relations between Student Online Learning Behavior and Academic Achievement in Higher Education: A Learning Analytics Approach

被引：20

作者：

Jo, Il-Hyun ^{[1
]}

Yu, Taeho ^{[2
]}

Lee, Hyeyun ^{[1
]}

Kin, Yeonjoo ^{[1
]}

机构：

[1] Ewha Womans Univ, Dept Educ Technol, Seoul, South Korea

[2] Purdue Univ, W Lafayette, IN 47907 USA

来源：

EMERGING ISSUES IN SMART LEARNING | 2015年

关键词：

Learning analytics; Educational technology; higher education; E-learning; COLLEGE;

D O I：

10.1007/978-3-662-44188-6_38

中图分类号：

G40 [教育学];

学科分类号：

040101 ; 120403 ;

摘要：

The purpose of fins study is to suggest more meaningful components for learning analytics in order to help learners to improve their learning achievement continuously through an educational technology approach. 41 undergraduate students in a women's university in South Korea participated in this study. The seven-predictor model was able to account for 99.3% of the variance in the final grade, F-(8,F- (32)) = 547.424, p < .001, R-2 = .993. Total login frequency in LMS, (ir)regularity of learning interval in LMS, and total assignments and assessment composites had a significant (p < .05) correlation with final grades. However, total studying time in LMS (ss=.038, t=.868, p > .05), interactions with content (ss=-.004, t=-.240, p > .05), interactions with peers (ss=.015, t=.766, p > .05), and interactions with instructor (ss=.009, t=.354, p > .05) did not predict final grades. The results provide a rationale for the treatment for student time management effort.

引用

页码：275 / 287

页数：13

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