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Analysis of Factors Influencing LMS Extracted Data using Learning Analysis on the Total Score of Learners


Affiliations
1 Kookmin University, Korea, Republic of
2 Kyunghee Cyber University, Korea, Republic of
3 Hanyang University, Korea, Republic of
 

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The development of information and communication technology has led to change in today's modern society with various names, such as knowledge, information society, internationalization society, and especially, the development of distance education without time and space restrictions. With the development of distance education, problems of dropouts and incompleteness of learners who are constantly in trouble are emerging as and they must be solved. Therefore, in this study, log data (regularity of learning start interval, total number of learnings and total learning time) and personal background data (courses experience, education experience, gender and age) accumulated in the web through learning management system (LMS) in a distant education environment. The purpose of this study is to analyze the effect of age and educational experience on the total scores that determine completion (more than 60 points) and incompleteness (less than 60 points). The study was carried out with data from 1,130 learners of distance learning centers, which were conducted for a total of 16 weeks. Data was extracted and analyzed based on learning analysis, and the results were as follows: First, among the log data, it was found that the total learning time and number of learning had significant effects on the total score. As the number of access to the LMS increased, the learning time and total score increased. Second, among personal background data, age was found to have a significant effect on the total score. It was concluded that the probability of completing the study, i.e, the probability of completing the study, increases as age increases, so the purpose of learning becomes more apparent. The data used in this study was used when a learner started signing up for LMS for learning and collected the consent in advance with the consent of the personal information agreement.

Keywords

Learning Analytics, Lifelong Distance Education, LMS (Learning Management System), Log data, Personal Background data.
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  • Analysis of Factors Influencing LMS Extracted Data using Learning Analysis on the Total Score of Learners

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Authors

Jong-Teak Seo
Kookmin University, Korea, Republic of
Young-Gi Kim
Kyunghee Cyber University, Korea, Republic of
Ra-Chel Ju
Hanyang University, Korea, Republic of

Abstract


The development of information and communication technology has led to change in today's modern society with various names, such as knowledge, information society, internationalization society, and especially, the development of distance education without time and space restrictions. With the development of distance education, problems of dropouts and incompleteness of learners who are constantly in trouble are emerging as and they must be solved. Therefore, in this study, log data (regularity of learning start interval, total number of learnings and total learning time) and personal background data (courses experience, education experience, gender and age) accumulated in the web through learning management system (LMS) in a distant education environment. The purpose of this study is to analyze the effect of age and educational experience on the total scores that determine completion (more than 60 points) and incompleteness (less than 60 points). The study was carried out with data from 1,130 learners of distance learning centers, which were conducted for a total of 16 weeks. Data was extracted and analyzed based on learning analysis, and the results were as follows: First, among the log data, it was found that the total learning time and number of learning had significant effects on the total score. As the number of access to the LMS increased, the learning time and total score increased. Second, among personal background data, age was found to have a significant effect on the total score. It was concluded that the probability of completing the study, i.e, the probability of completing the study, increases as age increases, so the purpose of learning becomes more apparent. The data used in this study was used when a learner started signing up for LMS for learning and collected the consent in advance with the consent of the personal information agreement.

Keywords


Learning Analytics, Lifelong Distance Education, LMS (Learning Management System), Log data, Personal Background data.

References





DOI: https://doi.org/10.16920/jeet%2F2021%2Fv34i3%2F155396