A Structural Equation Model of Predictors for Effective Online Learning

By R. B. Marks, Stanley D. Sibley, J. Ben Arbaugh. 2005

514 citations recorded by the source corpus.

Subfields: Communication, Education, Social Psychology

View Paper: https://www.semanticscholar.org/paper/1b6253eca2404e511b0da57e95960172d044c83d

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Citations in the corpus

Enhancing Knowledge Transfer in Classroom Versus Online Settings: The Interplay Among Instructor, Student, Content, and Context (2009, background): “Existing research suggests that women learn more effectively in Internet learning environments than men and find these learning environments more enjoyable, although empirical results have not been universally consistent (Arbaugh & Rau, 2007; Cybinski & Selvanathan, 2005; Marks et al., 2005).”
Research in online and blended learning in the business disciplines: Key findings and possible future directions (2009, background): “Some studies have found that learner–learner interaction is the stronger predictor (Arbaugh, 2002; Peltier et al., 2003), and others have found that learner–instructor interaction is the stronger predictor (Arbaugh & Rau, 2007; Marks et al., 2005).”
The impact of learning design on student behaviour, satisfaction and performance: A cross-institutional comparison across 151 modules (2016, background): “…analytics data that are known to influence the students' learning experience, such as the level of the course (Calvert, 2014), the specific discipline (Rienties et al., 2012), the year of implementation, size of the class or module (Arbaugh, 2014; Arbaugh & Duray, 2002; Marks et al., 2005).”
Does the Community of Inquiry Framework Predict Outcomes in Online MBA Courses (2007, background): “Second, although the study helps to answer recent calls for multi-discipline, multi-semester studies in online management education (Marks et al., 2005) it is based upon the findings at a single institution.”
Students’ characteristics, self-regulated learning, technology self-efficacy, and course outcomes in online learning (2013, background): “On the other hand, Marks et al. (2005), Yukselturk and Bulut (2007), and Yukselturk (2009) reported that age, gender, educational level, and previous number of online courses taken do not statistically signi ﬁ cantly predict the current online course satisfaction or students ’ achievement.”
Determinants of Students’ Perceived Learning Outcome and Satisfaction in Online Learning during the Pandemic of COVID19 (2020, background): “Construct Item Mean SD Cronbach’s Alpha Interaction Interaction1 2.57 1.04 .944 Interaction2 Interaction3 Student Motivation Stu_Mot1 2.88 1.12 .901 Stu_Mot2 Stu_Mot3 Stu_Mot4 Course Structure Course_str1 2.97 1.23 .908 Course_str2 Course_str3 Instructor Facilitation/knowledge Ins_Fac1 3.18 1.43 .88”
Investigating factors that influence social presence and learning outcomes in distance higher education (2011, background): “…receive timely feedback and encouraging motivation, feel to share their personal stories and matters, feel valued of their contributions and are provided positive guidance for the pursuit of their successful learning ( [Bangert, 2004] , [Marks et al., 2005] , [Rovai, 2007] and [Stacey, 2002]).”
Factors Affecting Perceived Learning, Satisfaction, and Quality in the Online MBA: A Structural Equation Modeling Approach (2015, methodology): “While factors other than those related to these aspects can certainly affect student outcomes, for example, Marks, Sibley, and Arbaugh (2005) showed that the advantages of flexibility and convenience influence perceptions of online learning, these types of factors do not differentiate particular…”
Instructor–Learner Interaction in Online Courses: The relative perceived importance of particular instructor actions on performance and satisfaction (2007, background): “Instructor–learner interactions may be those that most immediately come to mind, and they have been found to be the most important ones with regard to student perceptions of learning (Marks, Sibley, & Arbaugh, 2005 ).”
Exploring the factors affecting MOOC retention: A survey study (2016, background): “Interestingly Marks et al. (2005) quote Mason (1991) as ﬁ nding that instructors play a major role in directing online discussions.”
In search for the most informative data for feedback generation: Learning analytics in a data-rich context (2015, background): “In other words, in line with previous research (Author A, 2013a; Marks et al., 2005; Richardson, 2012) prior education seems to be a useful factor to include in learning analytics modelling.”