Interaction and Engagement in Online Education: Impacts of Student Characteristics and Perceptions

Abstract

Online learning has become a common method for providing learning at different levels of education. It uses a new form of technology in the field of education to improve classroom activities, overcome the limitations of traditional learning methods, and attract more learners around the world. Online learning has facilitated learning in many ways. It has made it more flexible and available than previous methods. Web-based learning provides students with more opportunities than traditional pedagogical learning to obtain information, gain increased access to different learning resources, and collaborate with others. In spite of the above mentioned benefits and the rapid growth of online education, being successful and persistence with this system is one of the important aspects of online learning settings, and it relies on a variety of factors. Investigating the reasons why students drop out of online education courses or programmes and the contributing factors is essential. One of the greatest issues in online learning systems, contributing to the failure of online education and student dropout, is a lack of interaction. In learning, interaction between students themselves, with the course content, and course instructors is important for conveying information, enhancing teaching quality, giving directions, and many more functions. Different factors that contribute to the online interaction and engagement of students have been explored in the literature. Generally, they are categorised in this study as individual and behavioural factors, and course design and administrative factors. Although previous studies have discussed factors influencing student online interaction and engagement, there is a lack of research investigating the dynamics of these relationships and discussing the impact of a comprehensive set of factors on student online interaction at the same time. This study seeks to fill this gap by employing causal loop diagrams (CLDs) to uncover the interrelationships between these contributing factors. Therefore, a rich qualitative data set was collected from an online course, and a thematic analysis was conducted. The results from the analysis of qualitative data generate a comprehensive CLD to propose a big picture of factors that impact on students’ online interaction and engagement and their causal relationships. Another aim of this research is to propose a conceptual framework that determines the factors contributing to the success of online learning systems. Individual behavioural traits, which are termed “students’ personal characteristics” and “students’ perceived course characteristics”, are investigated through a quantitative research approach. The first category involves a student’s self-regulated learning, communication competencies, and attitude toward online education, and the second category includes a student’s sense of presence, sense of identity, and sense of purpose regarding online interaction. A quantitative research approach was employed and the data for this research were collected by survey from 246 students from an Australian university doing online courses. Partial least squares (PLS) was then used as a method to test the research model and hypotheses. The results reveal that personal characteristics of self-regulated learning and communication competencies have a positive significant effect on students’ online engagement, and attitude towards online learning also has a significant impact on learners’ online interactions. The findings also show that perceived course characteristics, including a sense of identity, presence, and purpose, significantly influence students’ online interaction and engagement. The proposed model is used to determine the factors that may impact on a student’s online interaction and engagement in online learning courses. This research focuses on the experience of higher education entities applying online learning in their educational systems. The results of this study could be of potential benefit for both students and course instructors and provide a clearer and better understanding of how universities and higher education providers are responding to the emergence of online learning innovations. Another potential contribution of this research would be in confirming the ability to replicate the integrated research model of this study into other research contexts. It may provide a methodological contribution to the literature and proposes instruments that can improve online interaction and engagement in online learning systems.