Building and testing a framework of interactive and indirect predictors of student satisfaction would help us understand how to improve student online learning experience. The current study proposed that external predictors such as poor technological, environmental, and pedagogical factors would be internalized as negative psychological traits and…

This study investigated the structural relationships among online learners' teaching, social, and cognitive presence, engagement, and satisfaction. Data were collected from graduate students enrolled in an online graduate program at a large midwestern public university through online surveys. Structural equation modeling (SEM) was used to analyze…

The purpose of this study was to examine the underlying mechanism between goal orientations and academic expectation for online learners. We simultaneously studied the structural relationships among 2×2 achievement goal orientations, self-regulated learning (SRL) strategies, supportive online learning behaviors, and expected academic outcome in…

MOOCs are characterized as being courses to which a large number of students enroll, but only a small fraction completes them. An understanding of students' engagement construct is essential to minimize dropout rates. This research is of a quantitative design and exploratory in nature and investigates the interaction between contextual factors…

As online class offerings continue to proliferate and more students take at least one online class in college, more research is needed to explore factors that impact students' perceptions of their online classes. Past research has found a positive relationship between students' computer self-efficacy and their satisfaction with online learning,…

The Community of Inquiry (CoI) framework posits that a collaborative online teaching and learning process can be achieved through three interdependent dimensions of presence: cognitive presence, social presence, and teaching presence. Emotion is considered an important factor in successful online learning. This study explored non-traditional…

The purpose of this study was to investigate a predictive model of online learners' learning outcomes through machine learning. To create a model, we observed students' motivation, learning tendencies, online learning-motivated attention, and supportive learning behaviors along with final test scores. A total of 225 college students who were…

Higher education for the 21st century continues to promote discoveries in the field through learning analytics (LA). The problem is that the rapid embrace of of LA diverts educators' attention from clearly identifying requirements and implications of using LA in higher education. LA is a promising emerging field, yet higher education stakeholders…

This study explored the interaction between student characteristics and the online environment in predicting course performance and subsequent college persistence among students in a large urban U.S. university system. Multilevel modeling, propensity score matching, and the KHB decomposition method were used. The most consistent pattern observed…