A review of predictive factors of student success in and satisfaction with online learning
By Heather Kauffman. 2015
479 citations recorded by the source corpus.
Students perceive online courses differently than traditional courses. Negative perceptions can lead to unfavourable learning outcomes including decreased motivation and persistence. Throughout this review, a broad range of factors that affect performance and satisfaction within the online learning environment for adult learners will be examined including learning outcomes, instructional design and learner characteristics, followed by suggestions for further research, and concluding with implications for online learning pertinent to administrators, instructors, course designers and students. Online learning may not be appropriate for every student. Identifying particular characteristics that contribute to online success versus failure may aid in predicting possible learning outcomes and save students from enrolling in online courses if this type of learning environment is not appropriate for them. Furthermore, knowing these learner attributes may assist faculty in designing quality online courses to meet students’ needs. Adequate instructional methods, support, course structure and design can facilitate student performance and satisfaction. Keywords: online learning; learner characteristics; instructional design; online learning outcomes (Published: 27 August 2015) Responsible Editor: Meg O’Reilly, Southern Cross University, Australia Citation: Research in Learning Technology 2015, 23 : 26507 - http://dx.doi.org/10.3402/rlt.v23.26507
Subfields: Computer Science Applications, Education
View Paper: https://www.semanticscholar.org/paper/877100f21f680883ab3ae712b550e06d44377933
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In Computer Science Applications
In Education
Citations in the corpus
- Development of a new model on utilizing online learning platforms to improve students’ academic achievements and satisfaction (2020, background): “Nevertheless, learners differ in their previous background and experience, along with their education techniques, which clearly influence their online courses results besides their achievement (Kauffman, 2015).”
- A structural equation model of predictors of online learners’ engagement and satisfaction (2019, background): “In the current literature base, student satisfaction is one of the main predictors of the quality of online courses (Eom & Ashill, 2016; Kauffman, 2015; Moore & Kearsley, 2005; Roach & Lemasters, 2006; Yukselturk & Yildirim, 2008).”