Nguyen, Quan; Rienties, Bart and Toetenel, Lisette
(2017).
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| DOI (Digital Object Identifier) Link: | https://doi.org/10.1145/3027385.3027409 |
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| Google Scholar: | Look up in Google Scholar |
Abstract
Substantial progress has been made in understanding how teachers design for learning. However, there remains a paucity of evidence of the actual students' response towards leaning designs. Learning analytics has the power to provide just-in-time support, especially when predictive analytics is married with the way teachers have designed their course, or so-called a learning design. This study investigates how learning designs are configured over time and their impact on student activities by analyzing longitudinal data of 38 modules with a total of 43,099 registered students over 30 weeks at the Open University UK, using social network analysis and panel data analysis. Our analysis unpacked dynamic configurations of learning designs between modules over time, which allows teachers to reflect on their practice in order to anticipate problems and make informed interventions. Furthermore, by controlling for the heterogeneity between modules, our results indicated that learning designs were able to explain up to 60% of the variability in student online activities, which reinforced the importance of pedagogical context in learning analytics.
| Item Type: | Conference or Workshop Item |
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| Copyright Holders: | 2017 ACM |
| ISBN: | 1-4503-4870-X, 978-1-4503-4870-6 |
| Keywords: | Learning analytics; learning design; social network analysis; longitudinal; panel data analysis |
| Academic Unit/School: | Faculty of Wellbeing, Education and Language Studies (WELS) Learning and Teaching Innovation (LTI) > Institute of Educational Technology (IET) Learning and Teaching Innovation (LTI) |
| Item ID: | 48838 |
| Depositing User: | Quan Nguyen |
| Date Deposited: | 17 Mar 2017 10:32 |
| Last Modified: | 01 May 2019 20:45 |
| URI: | http://oro.open.ac.uk/id/eprint/48838 |
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