Predicting Student Satisfaction and Outcomes in Online Courses Using Learning Activity Indicators

Kenneth David Strang
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Kenneth David Strang: School of Business and Economics, State University of New York, Plattsburgh, NY, USA & APPC Research Australia, Australia

International Journal of Web-Based Learning and Teaching Technologies (IJWLTT), 2017, vol. 12, issue 1, 32-50

Abstract: The premise for this study was that learner interaction in an online web-based course could be assessed in relation to academic performance, or in other words, e-learning. Although some studies reveal that learner interaction with online content is related to student academic performance, it remains unproven whether this is casual, or even if there may be a significant correlation. Thus, this study seeks to measure if there is a directional and then a casual relationship between student online academic performance, engagement analytics and other online activity factors. A unique aspect of this study is that data is collected from Moodle engagement analytics as well as from the activity logs. Student academic performance is measured based on the grade achieved from an assessment designed to map to the course learning objectives.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jwltt0:v:12:y:2017:i:1:p:32-50

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International Journal of Web-Based Learning and Teaching Technologies (IJWLTT) is currently edited by Mahesh S. Raisinghani

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