The Sustainability of a Community of Inquiry in Online Course Satisfaction in Virtual Learning Environments in Higher Education

Abstract

Teaching and learning online is quite challenging. Both require an additional capacity and effort to withstand ongoing engagement in a virtual learning environment. Nonetheless, there have been cases of dissatisfaction with virtual learning environments due to the lack of engagement and poor interaction between the instructor, students, and content, which may affect how students learn online. This study presents a cross-sectional survey that was designed to re-examine the theoretical model of the Community of Inquiry (CoI), and to examine the structure of course satisfaction using SmartPLS 3.3.8 for multivariate statistical analysis. The CoI and the course satisfaction instruments were adapted in this study. The reflections of the CoI are then assumed to form type II second-order constructs to determine their effect on student satisfaction with the course. The findings revealed that teaching, social, and cognitive presence in the CoI have a significant influence on students’ satisfaction with the courses that they are enrolled in. These results provide a direction for further research on the CoI in online learning by extending a framework that incorporates online learners as one of the essential stakeholders in education. Therefore, the results presented here are only applicable to certain courses, and it would be meaningful to investigate academic achievement and motivation, and to compare them between specific courses or subjects to find out which courses have lower or higher levels of presence.

Impact of ICT Usage on Employee Performance among Medium Manufacturing Enterprises (MMEs): Mediating Role of Employee Engagement and Knowledge Sharing

“…The results revealed that the data did not have a multivariate normal distribution: Mardia's multivariate skewness (β = 14.1634, p< 0.01) and Mardia's multivariate kurtosis (β = 98.0053, p< 0.01) indicated that the data did not follow a multivariate normal distribution. Hence, SmartPLS was chosen as the software for variance-based Structural Equation Modelling(SEM) that uses non-parametric multivariate analysis (Nasir & Ngah, 2022). This study used a two-stage approach, as proposed by experts (Anderson & Gerbing, 1998;Ngah et al, 2021), to examine the measurement and structural models (testing the hypothesized relationships).…”

“…The first step of the study is to determine convergent validity. The convergent validity will determine which items measure each concept and how well they correlate to that concept (Nasir & Ngah, 2022;Podsakoff et al, 2003). Hair et al (2017) proposed that the loading and AVE must be ≥ 0.5, and the composite reliability (CR) should be ≥ 0.7 to assure convergent validity (Hair et al, 2013;Ngah et al, 2021).…”

“…All of the direct and indirect hypotheses were supported. It is essential to check that the study is free of multi-collinearity issues before conducting additional analysis (Nasir & Ngah, 2022). The study's multi-collinearity is not severe, as shown by the VIF values in Table 7, which are all lower than 3.3 (Diamantopoulos & Siguaw, 2006).…”

The influence of self- and co-regulation on the community of inquiry for collaborative online learning: an ODeL context

“…The community of inquiry (CoI) framework developed by Garrison et al (2000) consists of three presencesteaching, cognitive and social presencerequired for effective collaborative online learning. The framework has been widely established to enhance critical thinking, participation and engagement in online learning (Nasir and Ngah, 2022). However, students still experience challenges with online engagement, regulation, self-directed learning and a lack of interaction and motivation (Ilduganova et al, 2021;Nasir and Ngah, 2022), resulting in increased dropout rates (Figueroa-Canas and Sancho-Vinuesa, 2020;Khalid and Quick, 2016;Narayanasamy and Elçi, 2020).…”

What can multimodal data tell us about online synchronous training: Learning outcomes and engagement of in-service teachers

“…The COVID-19 pandemic has strongly boosted the development of online learning, which, however, does not prove very effective because the students are poorly motivated and engaged due to untimely feedback, lax supervision, and other factors (Nasir and Ngah, 2022). At the same time, teachers are facing great challenges in their professional development as the transition from traditional education to online learning will cause in them mental changes in relation to their identity as educators and their ideas about education (Wang et al, 2010;Teräs, 2014;Richardson and Alsup, 2015).…”