Abstract: Online learning constitutes the most popular distance‑learning method, with flexibility, accessibility, visibility, manageability and availability as its core features. However, current research indicates that its efficacy is not consistent acro ss all learners. This study aimed to modify and extend the factors of the Technology Acceptance Model (TAM) to examine perceived satisfaction of an Arabic sample in online learning. The integrated factors in the modified model includes: deep level (lea rning styles), surface level (gender), and cognitive (online self‑efficacy) factors. Learning styles were chosen as a central factor. Hence, the online course was purposefully developed to support one pole in each dimension of Felder and Silverman Le arning Styles Model (FSLSM) in order to reveal the pedagogical implications of learning styles on learner satisfaction. A total of 70 learners participated voluntarily in the research. At the end of the online course, they were requested to fill in two questionnaires: the Index of Learning Styles (ILS) and a standard questionnaire. The psychometric properties of the latter were firstly analysed to validate the instrument. Then, Partial Least Squares Structural Equation Modelling (PLS‑SEM) was conduc ted to examine the proposed hypotheses. The model achieves an acceptable fit and explains 44.8% of variance. Perceived usefulness represented the best predictor, whereas online self‑efficacy and perceived ease of use failed to show a direct impact on perc eived satisfaction. Furthermore, neither learning styles nor gender diversity had direct influence on the dependent factors. Accordingly, the research suggested that other variables may have to be integrated to enhance the power of the model.

The metrics of self efficacy and self assessment were surveyed and analysed in order to examine the effectiveness of note taking instruction on emotional aspects of participants during a blended learning course. The changes of emotional aspects due to student's individual characteristics were also analysed. Participants were surveyed twice during the course, using the metrics mentioned above, and their emotional and cognitive changes were evaluated. The number of valid participants was 54. Scores of metrics between the two surveys were compared. Though most scores for self‑efficacy and self assessment decreased, this suggests that participants recognised their actual learning situation well. The relationship between the metrics and student's characteristics was examined. To illustrate participant's emotional and cognitive changes, causal analysis was introduced. The relationships between scores for self‑efficacy and self evaluation in the two surveys were analysed and compared. Also, the impact of improvements in note‑taking skills on changes in self‑efficacy and self‑evaluation were examined using causal analyses. These results show that note‑taking activities significantly stimulated the level of self‑efficacy and self‑assessment when the lecturer's instructions were able to improve note‑taking skills factor scores during the course.

As countless regional, national, and international accrediting bodies continue to employ student engagement measures as mechanisms for quality assurance, universities become more intent on achieving this important gauge of student success. Specifically, the growth in enrollment in distance learning programs adds a unique level of complexity leading researchers to search for ways to increase engagement in the online course environment. Organizations continue to value teamwork and many instructors have incorporated group work into their online courses to teach students this important skill. The present study examines the impact of student engagement on group satisfaction. Furthermore, this research places student engagement at the center of a structural equation model to determine both predictors and outcomes of this important element of student learning. Specifically, this analysis examines whether students’ perceptions of computer self‑efficacy impact student engagement and group satisfaction in online business courses. Our findings indicate that computer self‑efficacy leads to student engagement and, further, that student engagement influences group satisfaction. Importantly, the relationship between student engagement and group satisfaction is mediated by group expectations. Discussions of findings can be utilized to understand the factors that lead to student engagement and its outcomes in online courses.