Constructing Proxy Variables to Measure Adult Learners' Time Management Strategies in LMS
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| Title: | Constructing Proxy Variables to Measure Adult Learners' Time Management Strategies in LMS |
|---|---|
| Language: | English |
| Authors: | Jo, Il-Hyun, Kim, Dongho, Yoon, Meehyun |
| Source: | Educational Technology & Society. 2015 18(3):214-225. |
| Availability: | International Forum of Educational Technology & Society. Athabasca University, School of Computing & Information Systems, 1 University Drive, Athabasca, AB T9S 3A3, Canada. Tel: 780-675-6812; Fax: 780-675-6973; Web site: http://www.ifets.info |
| Peer Reviewed: | Y |
| Page Count: | 12 |
| Publication Date: | 2015 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Adult Education |
| Descriptors: | Foreign Countries, Time Management, Adult Students, Integrated Learning Systems, Online Courses, Predictor Variables, Multiple Regression Analysis, Correlation, Educational Research, Data Analysis, Adult Education, Measures (Individuals) |
| Geographic Terms: | South Korea |
| ISSN: | 1436-4522 |
| Abstract: | This study describes the process of constructing proxy variables from recorded log data within a Learning Management System (LMS), which represents adult learners' time management strategies in an online course. Based on previous research, three variables of total login time, login frequency, and regularity of login interval were selected as candidates from the data set, along with a guideline for manipulating the log data. According to the results of multiple regression analysis, which was conducted to determine whether the suggested variables actually predict learning performance, (ir)regularity of the login interval was correlative with and predictive of learning performance. As indicated in the previous research, the regularity of learning is a strong indicator for explaining learners' consistent endeavors and awareness of learning. This study, which was primarily based on theoretical evidence, demonstrated the possibility of using learning analytics to address a learner's specific competence in an online learning environment. Implications for the learning analytics field seeking a pedagogical theory-driven approach are discussed. |
| Abstractor: | As Provided |
| Number of References: | 48 |
| Entry Date: | 2015 |
| Access URL: | https://www.ifets.info/ |
| Accession Number: | EJ1070037 |
| Database: | ERIC |
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