Abstract—The wide-spread adoption of Learning Management System (LMS) technology has fundamentally changed the environment for today’s teaching and learning. The LMS has generated a new set of data that could possibly serve as proxy measures of learners’ engagement online. LMS data sets can be mined and analyzed to provide meaningful measures of learners’ online engagement to support and enhance teaching and learning practices. In particular, this research focuses on the digital traces of LMS data to establish and validate meaningful proxies of online engagement. With the vast data sets available over a LMS, it is timely to identify a methodical approach to extract and transform data features in a modus that is useful for analysis. Hence, the purpose of this study is twofold: (1) to establish a common set of metrics (immediacy, frequency, interval and recency) to codify and quantify learners’ online engagement in the LMS; and (2) to validate, using data mining techniques, these metrics of online engagement patterns in relation to the learners’ academic performance.
 

Index Terms—Learning management system, online engagement

Cite: Sylvia Chong and Adam Wong, "Proxy Variables of Online Engagement on the Learning Management System," International Journal of Learning and Teaching, Vol. 5, No. 4, pp. 296-300, December 2019. doi: 10.18178/ijlt.5.4.296-300