In this study, structural equation modeling is applied to examine the determinants of students' satisfaction and their perceived learning outcomes in the context of university online courses. Independent variables included in the study are course structure, instructor feedback, self-motivation, learning style, interaction, and instructor facilitation as potential determinants of online learning. A total of 397 valid unduplicated responses from students who have completed at least one online course at a university in the Midwest were used to examine the structural model. The results indicated that all of the antecedent variables significantly affect students' satisfaction. Of the six antecedent variables hypothesized to affect the perceived learning outcomes, only instructor feedback and learning style are significant. The structural model results also reveal that user satisfaction is a significant predictor of learning outcomes. The findings suggest online education can be a superior mode of instruction if it is targeted to learners with specific learning styles (visual and read/write learning styles) and with timely, meaningful instructor feedback of various types.

A stream of research over the past decade that identifies predictors of e‐learning success suggests that there are several critical success factors (CSFs) that must be managed effectively to fully realize promise for e‐learning. Grounded in constructivist learning theories, this study advances previous work on CSFs in university online education. Structural equation modeling is applied to examine the determinants of students’ satisfaction and their perceived learning outcomes in the context of university online courses. The independent variables of motivation (intrinsic and extrinsic), student self‐regulation, dialogue (instructor‐student, and student‐student), instructor, and course design are examined as potential determinants of online learning outcomes. A total of 372 responses from students who have completed at least one online course at a university in the Midwestern United States were used to examine the structural model. Findings indicate that instructor‐student dialogue, student‐student dialogue, instructor, and course design significantly affect students’ satisfaction and learning outcomes. However, both extrinsic student motivation and student self‐regulation have no significant relationship with user satisfaction and learning outcomes. Finally, intrinsic student motivation affects learning outcomes but not user satisfaction. The findings suggest that course design, instructor, and dialogue are the strongest predictors of user satisfaction and learning outcomes.

The past several decades of e-learning empirical research have advanced our understanding of the effective management of critical success factors (CSFs) of e-learning. Meanwhile, the proliferation of measures of dependent and independent variables has been overelaborated. We argue that a significant reduction in dependent and independent variables and their measures is necessary for building an e-learning success model, and such a model should incorporate the interdependent (not independent) process nature of e-learning success. We applied structural equation modeling to empirically validate a comprehensive model of e-learning success at the university level. Our research advances existing literature on CSFs of e-learning and provides a basis for comparing existing research results as well as guiding future empirical research to build robust e-learning theories. A total of 372 valid unduplicated responses from students who have completed at least one online course at a university in the Midwestern United States were used to examine the structural model. Findings indicated that the e-learning success model satisfactorily explains and predicts the interdependency of six CSFs of e-learning systems (course design quality, instructor, motivation, student-student dialog, student-instructor dialog, and self-regulated learning) and perceived learning outcomes.

Complementary to the increasing popularity of the Internet and WWW, electronic commerce (e‐commerce) has become a fast emerging industry and a significant global economic force. The online retail stores need to attract more visitors and convert them into the customers who actually purchase the products or services. To achieve this goal, these stores need to endeavor to enhance customers’ satisfaction to maintain positive relationships with customers. Satisfied customers have a higher chance of purchasing merchandise from the same store and remaining loyal customers. This study investigates the features that possibly influence the perceived satisfaction of online retail shopping among university students using 27 questionnaire items. The study findings imply that the online retailers may need to put emphasis on specifying how they guarantee on‐time delivery and risk‐free, hassle‐free return clearly on their Web pages. They should follow what they promise as much as possible to improve shoppers’ satisfaction. Clearly specified policies or explanations will perhaps make customers more satisfied and trust site more.

PurposeThe majority of e‐learning empirical research studies have focused on the two research streams: outcome comparison studies with classroom‐based learning and studies examining potential predictors of e‐learning success. The determinants of e‐learning success include interactions, instructor support and mentoring, information delivery technology, course content, self‐motivation, learning styles, and course structure. Most of these empirical studies failed to include the technological dimension as an antecedent of effectiveness of e‐learning systems. The purpose of this paper is to empirically test the effects of e‐learning management systems (LMS), self‐efficacy and self‐regulated learning on learner satisfaction and system effectiveness.Design/methodology/approachThis research model is an extension of the information systems success model of DeLone and McLean and the virtual learning environment effectiveness model of Piccoli et al. The research model was tested using the structural equation modelling‐based Partial Least Squares (PLS) methodology.FindingsFirst, use of e‐LMS is not positively related to systems quality, information quality, self‐managed learning, and user satisfaction. Second, the findings strongly support the previous works of Rai, et al., Livari, and Freeze, et al. These three studies found strong positive relationships between information quality and user‐satisfaction and between systems quality and user‐satisfaction in a voluntary or mandatory use context. Third, perceived user satisfaction with e‐LMS is a very strong predictor of system effectiveness. This is in accordance with the findings and conclusions discussed in the literature on student satisfaction (Freeze et al., Eom et al., Rai et al., Livari). Of the four factors hypothesized to affect user satisfaction with e‐LMS, only two (systems quality and information quality) are supported at p<0.01.Practical implicationsThis paper provides empirical evidence to support that e‐learner satisfaction is an important predictor of e‐LMS effectiveness and that systems quality and information quality have significant direct impacts on the perceived satisfaction of e‐learners with e‐LMS.Originality/valueThis study provides new empirical evidence that e‐learners' self‐regulated learning behavior may not lead to a higher level of e‐learners' satisfaction with e‐LMS, but it may lead to a higher level of satisfaction with web‐based courses.