Investigating the Drivers of Student Interaction and Engagement in Online Courses : A Study of State-ofthe-art

Online learning has become a widespread method for providing learning at different levels of education. It has facilitated the learning in many ways and made it more flexible and available by providing learners with more opportunities to learn information, further access to different learning resources, and collaboration rather than face-to-face learning. In spite of these benefits and rapid growth of online education, success and persistence in such courses is one the important aspects of online learning research and it relies on different factors. Therefore investigating the reasons of students’ dropout of an online education course or program and its contributing factors is essential in this area. One of the most barriers in online learning system is lack of interactions. In learning, interaction between students themselves, with the course content, and course instructors is important for conveying information, enhancing teaching quality, give directions, and many more functions. The aim of this research is to review the literature to propose a clearer picture of studies have been conducted regarding online interaction and factors that impact it in online education systems.


Introduction
One of the essential elements of online learning is student interaction that substantially influencing effective learning by exchanging ideas and intellectual stimulation (Wanstreet, 2009).Past studies suggested that interaction in online education and interactivity in course has a direct impact on level of student satisfaction (Durrington, Berryhill, & Swafford, 2006) and student achievement and learning outcomes (Bernard et al., 2009).Moore (Moore, 1989) proposed three ways of interaction: interac-tion with the content, interaction with instructor, and interaction with other students.He argued that student-content interaction is "the process of intellectually interacting with the content that results in changes in the learner's understanding, the learner's perspective, or the cognitive structures of the learner's mind" (Moore, 1989, p. 2) when learners have access to course materials via the Internet and contain video, text, audio, and/or graphic images.
Learner-instructor interaction is very important to nurture students' interest to the course contents and stimulating their motivation of learning.Instructor can have a considerable contribution in students' understanding of course concepts and clarify their misunderstanding through different strategies.Learner-learner interaction is the last type of interaction that happen among students individually or in a group that may focuses on building knowledge and developing specific skills (Moore, 1989).In traditional face-to-face learning system that was mainly a teacher-centric style, students interact with instructors directly by F2F interaction.Distance education and online learning environments caused a big shift in learning decentralization and provided more online learners.Nowadays e-learning technologies have brought about many fundamental changes in learning styles and focuses more on students "by enabling multiple interactions among all the different agents involved -learners, instructors and course designers, tutors, contents, interfaces, administrative staff, code, environments, etc." (Agudo-Peregrina, Iglesias-Pradas, Conde-González, & Hernández-García, 2014, p. 542).
Despite all the merits mentioned in last section for online learning, there are major concerns with it that needs to be brought to light.One of the biggest drawbacks of online learning is the lack of physical presence and interaction, particularly for students of special learning style like those that learn via tactile or kinaesthetic modality and used to move, touch and being active when learning.Learning through online classes and not having physical presence on campus make students suffer from lack of social interaction, belonging, and adequate support and guidelines for their study as they are supposed to do their assignment and exams on their own.According to Sims (1999), interaction in electronic learning processes has many educational functions, related to learner control over system responses, adaptation to user's input, allowing for participation and communication and helping to provide meaningful learning (Sims, 1999).
Given the importance of interaction in online learning, the objective of this study is to have a deeper insight to the literature to extract and explore different factors that contribute to the student online interaction.It aims to provide a better understanding of the impact of various characteristics and elements on doing interaction and engagement of students in an online learning environment.To do so, this study provides a literature review on online interaction in education.It proposes a classifi cation for the main fac-It proposes a classification for the main factors impact students' online interaction and also highlights some of their applications by learners and instructors to improve online interaction in online learning settings.In section 2, the research methodology, the review steps and criteria are discussed and study process is explained.Section 3 contains the results of analysing the selected data set and proposes the factors' categorization.Section 4 discusses the importance of implementing these results for both researchers and university course design departments.And finally the study ends with a conclusion in section 5.

Research Methodology
This systematic literature review was conducted on studies done regarding online interaction in online learning in higher education entities to identify what factors influencing online interaction and engagement of students.As mentioned before, a systematic literature review as a research methodology aims to address research questions by elaborating and interpreting existing research and propose a big picture of the area.The steps of the review are planning, conducting and reporting the review.Next steps are carried out to meet these purposes.

Study Selection Process and Criteria
A comprehensive study has been done in this literature review.There are no excluding or including criteria about sources and we searched in different databases such as: "Google Scholar", "Taylor & Francis", "Elsevier", "Wiley", "Editlib", "Springer", "Eric", and etc. that the exact details of each database and the number of research we have found in them are indicated in Fig. 1.It shows that Taylor & Francis" has constituted the most percentage of the total, 24% and then "Elsevier" is the second databases by 13%.Research terms includes: "online interaction and engagement in education", "online interaction and engagement in learning", "factors influencing online interaction", and "online interaction parameters".Then to present a state-ofthe-art analysis of recent studies about online interaction and engagement, the review has been focused on research done after 2000.Another excluding criteria is applied regarding research has been done on higher education entities including colleges and universities.

Study Process
Reviewing studies that have been carried out after 2000 and using the above mentioned search terms, the total number of studies found was about 362.Afterward, the titles of the papers were considered and those that are not related to the area were excluded, this resulted in 156 studies remaining.In next step, the studies were reduced to 74 once their abstracts were studied carefully.Finally after reading the full remain studies, I have come out with 66 research to be included in this literature review.Fig. 2 indicates the study process and the final set of papers and a summary of their research objectives are in appendix A.

Initial creening studies 362
Studies after title exclusion 156

Studies after abstract exclusion 74
Studies after full paper exclusion Investigating the Drivers of Student Interaction and Engagement in Online Courses ... 273

Research trend and Geographical Locations
This review has verified factors that impacts on online interaction and engagement in online education systems.The outcomes of this review regarding research trends and frequency in different geographical locations are displayed in figures bellow.

Type of Participants and Research Methodology
This literature review is conducted on higher education organisations.We have classified the participants of the reviewed research to five main categories university graduate, undergraduate and postgraduate, college graduate and undergraduate students.Fig. 5 shows the bar chart of these categories and the number of studies for each one.It can be implied that most of the studies have been conducted on university undergraduate students.Different research approaches and methodologies have been employed in reviewed literature.Some studies applied quantitative methods, which is an objective and systematic process where numerical data are used to obtain information about the research objectives.As Fig. 6 shows, it dominants the other methods and contains 61% of the total percentage.Some authors have selected qualitative approach to find out underlying reasons, opinions, and motivations and provide a deeper insight into the issues or help to develop ideas or hypotheses for potential quantitative research, which is 14%.The last approach applied in the reviewed studies is mixed-method that means their research contains both quantitative and qualitative methodology and it contains 25% of the total amount.As Fig. 6 shows, most of past studies used quantitative research methodology.For instance, authors in (Kang & Im, 2013) have investigated factors in learner-instructor interaction that can predict the learner's outcomes in the online learning environment.Agudo et.al. have defined three system-independent classifications of interactions and evaluated the relation of their components with academic performance across two different learning modalities: virtual learning environment (VLE) supported face-to-face (F2F) and online learning (Agudo-Peregrina et al., 2014).
Pure qualitative research method is adopted the lowest amount of previous studies of literature.Some examples such research are: Wang in (M.-j.Wang, 2010) has conducted research to find out students' online utterances and offline interactions, to determine the extent of collaborative learning among students, Sargeant et.al. have explored instructor roles in enhancing online learning through interpersonal interaction (Sargeant et al., 2006).
Mixed method that contains both quantitative and qualitative methodology are used in some authors' research such as F. Ke and D. Kwak (Ke & Kwak, 2013) that claims online learning interaction participation, perception, and learning satisfaction would be consistent across varied age and ethnicity groups.Also authors in (Nor, Hamat, & Embi, 2012) have attempted to realize how the students interact and collaborate in the process of online learning topics that had previously been discussed in a faceto-face mode.Other samples of these research are: different aspects of the online courses impact the way students enter into discussions online, and consequently, what they have opportunities to learn (McCrory, Putnam, & Jansen, 2008), how instructors and students perceive the importance of online interaction and which instructional techniques enhance those interactions (Su, Bonk, Magjuka, Liu, & Lee, 2005), Focusing on e-connectivity, instructor presence and positive communication in online courses (Cheng & Suan).Appendix B contains more details about all investigated studies in literature of this review.

Students' Positive Outcomes
Past research has shown that online interaction and engagement have a large impact on different student positive outcomes such as student satisfaction and motivation (Kuo, Walker, & Schroder, 2010;Kuo, Walker, Belland, et al., 2014;Moallem, Pastore, & Martin, 2013;Shank & Doughty, 2002), active learning (Kuo et al., 2010), learning outcomes, prospects, and performance (Beatty, 2002;Daradoumis et al., 2003;Heinemann, 2007;Kang & Im, 2013;Kuo et al., 2010;Okonta, 2010;Tatar, Gray, & Fusco, 2002).Some researchers introduced new ways to improve online interaction and engagement within online courses.For instance, Kang, M. and T. Im (2013) tried to identify what factors in online interaction can predict the learner's outcomes.They have concluded that "factors related to instructional interaction predicted perceived learning achievement and satisfaction better than factors related to social interaction.However, it was revealed that social interaction such as social intimacy could negatively affect perceived learning achievement and satisfaction" (Kang & Im, 2013) (p.292).Abrami, P. C., et al. (2011) discuss about different types of online interactions and suggest how these results may foster instructional improvement.They also highlight several evidence-based approaches that may be useful in the next generation of distance and online learning (Abrami, Bernard, Bures, Borokhovski, & Tamim, 2011;Bing & Ping, 2008;Brooks et al., 2004).
On the other hand, there are some studies that experienced failure in adopting some techniques for stimulating online interaction and engagements.To give an example Okon- To give an example Okon-Okonta (Beatty, 2002;Okonta, 2010)(2010) investigated the effect of parallel use of Facebook and Twitter for increasing online interaction among the college undergraduate students and the results indicated that there was interaction between learners and other learners but it was minimally used in their courses and academic purposes (Okonta, 2010).Belinda Carrick-Simpson and Christine Armatas from Deakin University, Australia, explore the factors that influence online interaction and better engagement because the results of their study has proven that designing online learning activities with opportunities for interactivity is not sufficient to engage students' interest (Carrick-Simpson & Armatas, 2003).
Fig. 7 displays all positive outcome factors extracted from literature and its subcategories.There are three main factors categories including 1-psychological factors, 2-learning factors, and 3-behavioural factors.The first one contains variables such as student motivation, student self-regulation, student appreciation, and student problem solving.The second category includes learning outcome/performance, student learning style, learning quality, learning effectiveness, academic achievement, and student success.The last one comprises student interaction, student collaboration, student engagement, student attrition, and student perception.

Factors Impacting on Online Interaction
As mentioned before, there are several factors contributing to online interaction and engagement improvement and development.The main contribution of this review is to identify and classify these factors.This literature review proposes four main groups for these influencing factors: 1 -Student's Individual characteristics, 2 -Student's Behavioural factors, 3 -Course design factors, and 4 -Administrative factors.Fig. 7 shows the details of classifications and all contributing factors categories.
Individual characteristics can be identified as having originated with a particular person or source with a high degree of certainty.In this study they refer to traits that are instinctively institutionalized in each individual.The characteristics that have extracted from the literature has been done in the area of online interaction and engagement in higher education entities include student expectation, self-expression, interest, cognitive abilities, leadership, self-efficacy, creative thinking, confidence, learning flexibility, and knowledge sharing (Hao, 2006;Ke & Kwak, 2013;Kuo, Walker, Belland, et al., 2014).Behavioural factors are traits that are done by an individual.The behavioural factors that are identified so far in literature, which effect online interaction and engagement are social intimacy, attitude, readiness, interaction, content understanding, group functioning, collaboration, cooperation, and participation (Kaymak & Horzum, 2013;Sher, 2009).
Course design factors are explained as factors in relation to instructing and developing course materials and contents and refer to the traits that are directly contributed to presenting a course.Those that are found in literature that impact online interaction and engagement in online learning are course clarity, task design, and academic integrity (Bubas et al., 2010;Lamy & Hassan, 2003;Swan, 2002;Torun, 2013).Administrative factors are pointed out to parameters that are related to administration of the course such as active discussion, feedback, technical support, academic support, and pedagogical support (Mohamad, Yusof, & Aris, 2014;Nor et al., 2012;Swanson, 2010).
According to the literature regarding course design and administrative factors, various parameters have been considered such as focusing on e-connectivity and instructor presence (Swanson, 2010) which used a mixed method of a qualitative study with a quantitative component in the affective domain emphasizing on e-connectivity, instructor presence, and positive communication.Instructors' role and content to enhance online learning through interpersonal interactions is other interest of researchers of this area in this area (Cheng & Suan).Authors in (Lamy & Hassan, 2003) presented the relationship between changing task designs and learner behaviour in online course and their results showed that task type is the main predictor of the volume of reflective interaction.
In terms of individual and behavioural traits, there are some research conducted in regard with students characteristics that have an impact on their online interactions.Some examples of them are: the effect of interactions and Internet self-efficacy on student satisfaction (Kuo, Walker, Belland, et al., 2014), students' readiness levels of the online learning (Kaymak & Horzum, 2013), interaction behaviours of different collaborative group types (Daradoumis et al., 2003), age and ethnicity of students (Ke & Kwak, 2013), learners' learning styles (Hao, 2006), cultural diversity (Bing & Ping, 2008), students' attitude toward distance and online learning (Brooks et al., 2004) and etc.

Discussion
Moving to the new millennium and with the emergence of the Internet, it provides the opportunity to stimulate participation and interaction within a technologically mainstream and cost-effective learning environment.Beside various interactive opportunities that are available in the online environment, this improvement can achieve in the light of the fact that high levels of interaction have positive effects on the learning experience (Chen & Chen, 2007;J. Richardson, Tunwall, & Carnevale, 2000;Sher, 2009;Wilson, 2007).Failure to adequate consideration to the relational dynamics in OLEs may incur feelings of isolation in online courses, decrease students' satisfaction, deficient learning outcome and performance, and high attrition rate.Given the current condition, online interaction is one of the most important components of online learning setting, therefore, it is needed to explore and elaborate different parameters and factors that contributing to higher and more effective interaction.
This review study represents significant findings for research and practice.The potential implications of categorizing contributing students' interaction factors for the potential implications for instructors, university faculties, students and learners, course designers and conveners is that it provides a big picture of several factors that are influencing learners online interaction and engagement.Therefore, they can take into account these factors when designing an online course to promote and cultivate the online interaction to attain better student academic performance and satisfaction.In addition to having several practical implications, it could help researchers, particularly new researchers, to inform about these factors in a very convenient way.
Moreover, getting to know that what specific students' individual, behavioural, course design, and administrative factors could participate in improving and enhancing students' online interaction and engagement, they can achieve better result and outcome of online learning by manipulating and controlling these traits.For instance, if learners' attitude toward OLEs is one of these factors that have a positive impact online interaction, educational expertise and instructors will be able to increase online interaction in their courses by working in this specification and try to give accurate and aggregate perspectives to learners.On top of that, the students can be aware of these characteristics and try to improve them.Additionally, investigating these aspects will enrich the literature and provide a clearer realization of different elements that could help interaction improvement in online learning systems and could assist researchers to contribute a better understanding of these fields and give directions to them to form the future of their research, as well as identifying gaps in the body of knowledge in this area.

Conclusion
The emergence of technology has made a huge shift in educational systems and created a variety of opportunities and facilities for todays' learners and has been expanded by the development of the Internet worldwide.Online learning is a new way of learning that is employed nowadays with many educational providers throughout the world particularly in higher education entities.However, there are some barriers and obstacles with this way of learning which lack of interaction is the most important of them.To fulfill this objective and provide a comprehensive view of the contributing factors in learners' online interaction and give a big picture of them to educators, this study has conducted an in-depth review of current literature to elaborate and explore different factors that have influence on students' online interaction.The results show that they typically can be divided into four major categories: individual, behavioural, course design, and administrative factors.Providing all these factors and their sub categories that contains different traits could help researchers and instructors and gives them an entire perspective to improve online interaction in their educational settings and lead to a better and higher result in student' outcomes and increase level of cognition.

Qualitative
Exploring the interaction behaviour of different collaborative group types with respect to their performance (Daradoumis et al., 2003) 2004 The University of Texas thesis Mixed-method Students' attitudes toward four types of interactions: instructional, affective, collaborative, and vicarious (Brooks et al., 2004) 2005

Fig. 1 .
Fig. 1.Databases and proportion of studies of each one.

Fig. 7 .
Fig. 7. Factors impacting on student interaction and engagement was received her B.Sc. degree in Electrical-Control Engineering in 2007 and her Master of Engineering in 2013 from Queensland University of Technology (QUT).She is a PhD student studying Information and Communication Technology in Griffith University in Brisbane, Australia.Her research interests include, learning technologies, online learning, online interaction, and serious games.Chen is a senior lecturer and program director of Bachelor of Information Technology at School of Information and Communication Technology, Griffith University.He has more than ten years of experience in research and teaching at University level.His research interests include learning and teaching, collaborative systems, networking, and bioinformatics.Dr. A. Nguyen is a Senior Lecturer in the School of Information and Communication Technology at Griffith University.Her research interests include: eEducation, eBusiness, and eGovernment, with specific focus on models and supporting systems.