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http://dx.doi.org/10.22156/CS4SMB.2018.8.4.247

The Analysis of Academic Achievement based on Spatio-Temporal Data Relate to e-Learning Patterns of University e-Learning Learners  

Lee, Hae-Deum (Educational Development Institute, Mokwon University)
Nam, Min-Woo (Educational Development Institute, Mokwon University)
Publication Information
Journal of Convergence for Information Technology / v.8, no.4, 2018 , pp. 247-253 More about this Journal
Abstract
This study was designed to analyze the difference in attendance and academic achievement based on spatio-temporal data relate to e-Learning patterns of university e-Learning learners. This study collected e-Learning data from 68 e-Learning classes, 13,611 learners during 3 years. Collected data were analyzed by t-test and two-way ANOVA. Major study findings were as follows. Firstly, e-Learning learners in school received higher than those of learners outside school both in attendance and academic achievement, while that academic achievement showed statistical significance. Secondly, the attendance and academic achievement by the day was in the order of e-Learning learners mainly in the morning, those in the afternoon and those at night, in addition there was statistical significance. Lastly e-Learning learners in the weekdays appeared higher than those of learners in the weekends both in attendance and academic achievement, also both of them showed statistical significance.
Keywords
e-Learning; e-Learning spatio-temporal data; e-Learning patterns; attendance; academic achievement;
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Times Cited By KSCI : 3  (Citation Analysis)
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1 S. R. Hwang(2016). Impact of Learner's Learning Behavior on Achievement: The Moderating Effect of Learning Motivation. Graduate School of Ewha Womans University.
2 D. H. Ahn. (2017). Moderating Effect of Learning styles on the relationship of quality and satisfaction of e-Learning context. Journal of Digital Convergence, 15(12), 35-45.   DOI
3 H. D. Lee. (2016). University e-Learning Students' Pattern Classification and Analysis of Academic Achievement Based on Behavioral Data Related to Learning. Graduate School of konkuk University.
4 M. S. Kang, J. I. Kim & I. W. Park. (2009). The Examination of the Variables related to the Students' e-learning Participation that Have an Effect on Learning Achievement in e-learning Environment of Cyber University. Journal of Internet Computing and Services, 10(5), 135-143
5 S. Y. Park, M. W. Nam & S. B. Cha(2012). University students, behavioral intention to use mobile learning : Evaluating the technology acceptance model. British journal of Education Technology, 43(4).
6 B. H. Moo. (2007). Analysis of Login and Learning Hour in Cyber Classes of Undergraduate Students. Journal of the Korea society of computer and information, 12(5), 171-177.
7 S. Y. Park & Y. S. Song. (2008). Analysis of e-learning time logs of university students. The Korean Society for Training and Development, 16, 53-67.
8 S. Y. Kwon. (2009). The Analysis of differences of learners participation, procrastination, learning time and achievement by adult learners adherence of learning time schedule in e-Learning environments. Journal of learning-Centered curriculum and Instruction, 9(3), 61-86.
9 I. H. Jo & J. H. Kim. (2013). Investigation of Statistically Significant Period for Achievement Prediction Model in e-Learning. Journal of Educational Technology, 29(2), 285-306.   DOI
10 C. K. Seong. (2011). Effect of the Students' e-learning Participation and Access Frequency and Access times on Learning Achievement in Blended-learning Environment. Journal of Society of Communication Design, (35), 90-98.
11 I. H. Jo & Y. M. Kim. (2013). Impact of Learner's Time Management Strategies on Achievement in an e-learning Environment: A Learning Analytics Approach. The Journal of Educational Information and Media, 19(1), 83-107.
12 H. G. Park. (2015). Analyzing the e-Learning Trend and Achievement by Attendance Source of Students. Graduate School of Keimyung University.
13 S. U. Kwon & S. J. Yun. (2010). A Study on the Influential Factors of Intention to Continued Use of e-Learning. Journal of Information Technology Applications & Management, 17(1), 35-54
14 H. Y. Lee. (2015). Development of prediction models based on the clustered online learners' behavioral patterns in university e-Learning environment. Graduate School of Ewha Womans University.
15 C. H. Ahn, S. K. Joung, S. G. Kim & I. H. Choi. (2016). "The Analysis of E-learning Learners Characteristics for Improving Teaching and Learning in Online". The journal of Korean instituteof information technology, 14(4), 187-194   DOI
16 M. K. Park & M. S. Park. (2017). "Effects of psychological empowerment on achievement in team based learning: Mediating effect of co-regulation", Journal of Digital Convergence, 15(10), .367-376.   DOI