online teaching research paper

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• Published: 25 January 2021

Online education in the post-COVID era

• Barbara B. Lockee 1  

Nature Electronics volume  4 ,  pages 5–6 ( 2021 ) Cite this article

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The coronavirus pandemic has forced students and educators across all levels of education to rapidly adapt to online learning. The impact of this — and the developments required to make it work — could permanently change how education is delivered.

The COVID-19 pandemic has forced the world to engage in the ubiquitous use of virtual learning. And while online and distance learning has been used before to maintain continuity in education, such as in the aftermath of earthquakes 1 , the scale of the current crisis is unprecedented. Speculation has now also begun about what the lasting effects of this will be and what education may look like in the post-COVID era. For some, an immediate retreat to the traditions of the physical classroom is required. But for others, the forced shift to online education is a moment of change and a time to reimagine how education could be delivered 2 .

Looking back

Online education has traditionally been viewed as an alternative pathway, one that is particularly well suited to adult learners seeking higher education opportunities. However, the emergence of the COVID-19 pandemic has required educators and students across all levels of education to adapt quickly to virtual courses. (The term ‘emergency remote teaching’ was coined in the early stages of the pandemic to describe the temporary nature of this transition 3 .) In some cases, instruction shifted online, then returned to the physical classroom, and then shifted back online due to further surges in the rate of infection. In other cases, instruction was offered using a combination of remote delivery and face-to-face: that is, students can attend online or in person (referred to as the HyFlex model 4 ). In either case, instructors just had to figure out how to make it work, considering the affordances and constraints of the specific learning environment to create learning experiences that were feasible and effective.

The use of varied delivery modes does, in fact, have a long history in education. Mechanical (and then later electronic) teaching machines have provided individualized learning programmes since the 1950s and the work of B. F. Skinner 5 , who proposed using technology to walk individual learners through carefully designed sequences of instruction with immediate feedback indicating the accuracy of their response. Skinner’s notions formed the first formalized representations of programmed learning, or ‘designed’ learning experiences. Then, in the 1960s, Fred Keller developed a personalized system of instruction 6 , in which students first read assigned course materials on their own, followed by one-on-one assessment sessions with a tutor, gaining permission to move ahead only after demonstrating mastery of the instructional material. Occasional class meetings were held to discuss concepts, answer questions and provide opportunities for social interaction. A personalized system of instruction was designed on the premise that initial engagement with content could be done independently, then discussed and applied in the social context of a classroom.

These predecessors to contemporary online education leveraged key principles of instructional design — the systematic process of applying psychological principles of human learning to the creation of effective instructional solutions — to consider which methods (and their corresponding learning environments) would effectively engage students to attain the targeted learning outcomes. In other words, they considered what choices about the planning and implementation of the learning experience can lead to student success. Such early educational innovations laid the groundwork for contemporary virtual learning, which itself incorporates a variety of instructional approaches and combinations of delivery modes.

Online learning and the pandemic

Fast forward to 2020, and various further educational innovations have occurred to make the universal adoption of remote learning a possibility. One key challenge is access. Here, extensive problems remain, including the lack of Internet connectivity in some locations, especially rural ones, and the competing needs among family members for the use of home technology. However, creative solutions have emerged to provide students and families with the facilities and resources needed to engage in and successfully complete coursework 7 . For example, school buses have been used to provide mobile hotspots, and class packets have been sent by mail and instructional presentations aired on local public broadcasting stations. The year 2020 has also seen increased availability and adoption of electronic resources and activities that can now be integrated into online learning experiences. Synchronous online conferencing systems, such as Zoom and Google Meet, have allowed experts from anywhere in the world to join online classrooms 8 and have allowed presentations to be recorded for individual learners to watch at a time most convenient for them. Furthermore, the importance of hands-on, experiential learning has led to innovations such as virtual field trips and virtual labs 9 . A capacity to serve learners of all ages has thus now been effectively established, and the next generation of online education can move from an enterprise that largely serves adult learners and higher education to one that increasingly serves younger learners, in primary and secondary education and from ages 5 to 18.

The COVID-19 pandemic is also likely to have a lasting effect on lesson design. The constraints of the pandemic provided an opportunity for educators to consider new strategies to teach targeted concepts. Though rethinking of instructional approaches was forced and hurried, the experience has served as a rare chance to reconsider strategies that best facilitate learning within the affordances and constraints of the online context. In particular, greater variance in teaching and learning activities will continue to question the importance of ‘seat time’ as the standard on which educational credits are based 10 — lengthy Zoom sessions are seldom instructionally necessary and are not aligned with the psychological principles of how humans learn. Interaction is important for learning but forced interactions among students for the sake of interaction is neither motivating nor beneficial.

While the blurring of the lines between traditional and distance education has been noted for several decades 11 , the pandemic has quickly advanced the erasure of these boundaries. Less single mode, more multi-mode (and thus more educator choices) is becoming the norm due to enhanced infrastructure and developed skill sets that allow people to move across different delivery systems 12 . The well-established best practices of hybrid or blended teaching and learning 13 have served as a guide for new combinations of instructional delivery that have developed in response to the shift to virtual learning. The use of multiple delivery modes is likely to remain, and will be a feature employed with learners of all ages 14 , 15 . Future iterations of online education will no longer be bound to the traditions of single teaching modes, as educators can support pedagogical approaches from a menu of instructional delivery options, a mix that has been supported by previous generations of online educators 16 .

Also significant are the changes to how learning outcomes are determined in online settings. Many educators have altered the ways in which student achievement is measured, eliminating assignments and changing assessment strategies altogether 17 . Such alterations include determining learning through strategies that leverage the online delivery mode, such as interactive discussions, student-led teaching and the use of games to increase motivation and attention. Specific changes that are likely to continue include flexible or extended deadlines for assignment completion 18 , more student choice regarding measures of learning, and more authentic experiences that involve the meaningful application of newly learned skills and knowledge 19 , for example, team-based projects that involve multiple creative and social media tools in support of collaborative problem solving.

In response to the COVID-19 pandemic, technological and administrative systems for implementing online learning, and the infrastructure that supports its access and delivery, had to adapt quickly. While access remains a significant issue for many, extensive resources have been allocated and processes developed to connect learners with course activities and materials, to facilitate communication between instructors and students, and to manage the administration of online learning. Paths for greater access and opportunities to online education have now been forged, and there is a clear route for the next generation of adopters of online education.

Before the pandemic, the primary purpose of distance and online education was providing access to instruction for those otherwise unable to participate in a traditional, place-based academic programme. As its purpose has shifted to supporting continuity of instruction, its audience, as well as the wider learning ecosystem, has changed. It will be interesting to see which aspects of emergency remote teaching remain in the next generation of education, when the threat of COVID-19 is no longer a factor. But online education will undoubtedly find new audiences. And the flexibility and learning possibilities that have emerged from necessity are likely to shift the expectations of students and educators, diminishing further the line between classroom-based instruction and virtual learning.

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Lockee, B.B. Online education in the post-COVID era. Nat Electron 4 , 5–6 (2021). https://doi.org/10.1038/s41928-020-00534-0

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Online education amid COVID-19 pandemic and its opportunities, challenges and psychological impacts among students and teachers: a systematic review

Asian Association of Open Universities Journal

ISSN : 2414-6994

Article publication date: 21 October 2022

Issue publication date: 9 December 2022

The global spread of the COVID-19 pandemic resulted in the complete lockdown of almost every part of the world, including all educational institutions, resulting in the prompt implementation of online education to facilitate the students to carry on their learning. These conditions made the researchers study the experiences of online education among students and teachers. The influences of online teaching-learning during the COVID-19 pandemic undoubtedly offered numerous opportunities besides raising some challenges which impacted the overall psychology of students and teachers. So, this paper aims to conduct a systematic review of the research papers focussing on opportunities, challenges and psychological impacts raised due to the sudden shift to online education among students and teachers during the COVID-19 pandemic.

Design/methodology/approach

To conduct this systematic review, 19 articles published between July 2020 and May 2021 were considered and reported by following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).

It was found that online education influenced the interests and experiences of the students and teachers and has immensely impacted their overall psychology. So, for the effective implementation of online and blended education, psychological well-being of students and teachers should be taken care of with properly designed instructions, adequate infrastructure or resources and satisfactory technological skills.

Research limitations/implications

In the present study, the students were not categorised according to their subjects or streams, i.e. science, commerce, humanities, medical, dental, postgraduate or undergraduate. All the students were categorised into two categories only: (1) college students and (2) school students. And also, teachers were not categorised and were presented as a whole, as school, college or university teachers.

Practical implications

The current research identified the abrupt implementation of online education during the COVID-19 pandemic, which raised various challenges and psychological impacts among students and teachers besides offering them many opportunities in times of crisis.

Social implications

Students and teachers constitute the educational community of society. They should get ample opportunities to develop skills for online education; challenges faced during online education should be identified and tackled, and the issues concerning the psychological well-being during online education for both teachers and students should be addressed to achieve sustained development of online education–blended learning environments.

Originality/value

The paper is the original research work based on the systematic review and concludes with suggestions for the future of online and blended pedagogy while taking care of the psychological needs of students and teachers in online and blended learning environments.

• COVID-19 pandemic
• Online education
• Opportunities
• Psychological impacts
• Systematic review

Aisha, N. and Ratra, A. (2022), "Online education amid COVID-19 pandemic and its opportunities, challenges and psychological impacts among students and teachers: a systematic review", Asian Association of Open Universities Journal , Vol. 17 No. 3, pp. 242-260. https://doi.org/10.1108/AAOUJ-03-2022-0028

Emerald Publishing Limited

Copyright © 2022, Noor Aisha and Amiteshwar Ratra

Published in the Asian Association of Open Universities Journal . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at http://creativecommons.org/licences/by/4.0/ legalcode

Introduction

The global spread of the COVID-19 pandemic resulted in the complete lockdown of almost every part of the world, including all educational institutions in order to minimise and limit the gatherings/physical contacts in educational institutions to control the spread of the COVID-19 infection. This sudden outbreak of the COVID-19 pandemic and the subsequent lockdown confined everyone within the four walls of home for a long time, which became a major challenge to the whole educational community ( UNESCO, 2020 ) in their educational endeavours, which resulted in the sudden start of online delivery of instruction, in order to facilitate and continue the learning process during the COVID-19 pandemic. It consequently reduced the physical activity and increased the inactive behaviour ( Yarımkaya and Esentürk, 2020 ) of students as well as teachers which induced serious impacts on the overall quality of life, education, teaching-learning schedules and their psychological well-being.

Although online learning has been a ubiquitous part of our education, before the onset of the COVID-19, pandemic students and teachers had relied more on traditional forms of education. However, during the lockdown of the COVID-19 pandemic, students and teachers had to experience complete online teaching-learning with no other options. Almost all the educational institutions took only a little time in switching to entirely online, distance or remote teaching-learning with whatever possible resources and infrastructure they had in order to control and minimise the educational loss of the students during the pandemic. Thus, such a situation has resulted to influence the overall psychology. It was the very first time for the students and teachers to involve in the complete online, distance or remote teaching-learning experience. In the educational scenario prior to the COVID-19 pandemic, most of the students were familiar with the conventional classroom or face-to-face system of education, and online, distance or remote education was just an alternate and assistive tool for all the students. Therefore, these conditions made researchers all around the world conduct various research studies to study the experiences of online education among students and teachers. The influences of the online teaching-learning environment during the COVID-19 pandemic on the one hand offered numerous opportunities, while on the other hand, it posed some challenges which impacted the overall psychology of students and teachers. So, the present paper systematically reviews the research papers focussing on opportunities, challenges and psychological impacts raised due to the sudden shift to online education among students and teachers during the COVID-19 pandemic.

Online education and the COVID-19 pandemic

Technological interventions in education have impacted the whole educational system. Technological advancements have made it possible to connect online globally. Online education offers the flexibility of time, pace and place for education to students ( Huang, 1997 ; Jindal and Chahal, 2018 ), and acceptance of online education increased with its acceptability in the instructional transactions in no time ( Huang, 1997 ; Jindal and Chahal, 2018 ). Technological advancements, Internet penetration, sustainable utilisation of resources by saving time and money, providing flexibility and conveniences to study ( Huang, 1997 ; Livingstone and Bober, 2004 ), support from the authorities like institutions and government and development of skills were the prospects that online education promoted ( Jindal and Chahal, 2018 ). However, online education had many challenges ( Mäkelä et al., 2020 ) when it came to its implementation which includes insufficient digital infrastructure such as lack of availability of digital devices and low accessibility with poor technological skills ( Jindal and Chahal, 2018 ). Online education requires to be accessed from the home, office or a single quiet place to facilitate learning with concentration and without the physical presence of any facilitator or instructor, which ultimately creates a situation of isolation or limited social interaction ( Rakes and Dunn, 2010 ; Yarımkaya and Esentürk, 2020 ) and that may consequently lead to inactivity ( Yarımkaya and Esentürk, 2020 ) and low motivation and decreased self-regulation among students ( Rakes and Dunn, 2010 ).

Technical issues may also cause frustration ( Rakes and Dunn, 2010 ). Also, to some extent, credibility of degrees or certificates earned online was looked upon since it did not get institutional acceptance and authoritative support for their implementation ( Jindal and Chahal, 2018 ). But, over time this issue has been tackled ( University Grant Commission, 2022 ). Online education was earlier considered to play supportive and assistive roles ( Huang, 1997 ; Jindal and Chahal, 2018 ), and the COVID-19 pandemic forced the students and teachers to deal with fully online teaching-learning methods and experiences. The sudden adoption of online education made the students and teachers face various challenges and developed a situation of psychological distress. Therefore, the present systematic review attempts to report the opportunities that online education offered during the COVID-19 pandemic, the challenges that hindered the way to the successful and easy adoption of online education and the subsequent psychological impacts developed among students and teachers.

to study the opportunities, mentioned in the literature, that online education during the COVID-19 pandemic created for students and teachers.

to study the challenges, described in the literature, that students and teachers faced in the rapid implementation of online education during the COVID-19 pandemic.

to study the psychological impacts, reported in the literature, raised among students and teachers while switching rapidly to completely online education amid COVID-19 pandemic.

Methodology

Review protocol.

This systematic review article follows the quality reporting guidelines set out by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) ( Page et al. , 2021 ) to ensure clarity and transparency of review reporting.

Sources and search strings: The search process started in May 2021, by consulting the following sources: PubMed, ScienceDirect and Wiley Online Library.

“Opportunities and Challenges” AND “online education” AND (“teachers” OR “students”) AND “COVID-19”

“Psychological impacts” AND “online education” AND (“teachers” OR “students”) AND “COVID-19”

Psychological impacts of COVID-19”; “Psychological impacts of COVID-19 on students”; and “psychological impacts of COVID-19 on teachers.

Selection criteria

The research papers were searched through the application of the abovementioned keywords and search strings.

Exclusion criteria

EC1: Papers that are found common in all the searched databases (removal of duplicates).

EC2: Generally explained psychological impacts of the COVID-19 pandemic.

EC3: Research papers that include impacts of online teaching-learning but do not include psychological impacts due to online teaching-learning during the COVID-19 pandemic.

EC4: Reports not retrieved

R 2 = Research papers that have no direct linkage with online learning, that is, which do not explicitly describe the psychological impacts of online teaching-learning

R 3 = Research papers that do not fit well in the criteria/pattern of the present systematic review (it was either a qualitative study or a comparative study of two countries, conducted on various groups altogether, etc.)

Inclusion criteria

The inclusion criterion (IC) for the selection of the research papers for the present systematic review was limited to only those research articles that explicitly explained psychological impacts related to online teaching-learning on either teachers or students during the COVID-19 pandemic, and some studies were used for extracting opportunities and challenges raised due to the sudden shift to online teaching-learning, published from July 2020 to May 2021.

Data analysis

The studies for the systematic review were identified online through three databases (PubMed, ScienceDirect and Wiley Online Library) and random online searches. Then an analysis was conducted by inspecting each article’s title, abstract and keywords. Further, after the application of all ECs (EC1, EC2, EC3, EC4 and EC5), only 53 reports were found which were further taken for full-paper review. The whole process of data analysis was done manually with the utmost care, and no software was used for analysing the content of the selected studies for the systematic review. Thus, a total of 19 studies were identified after the application of IC and ECs as presented in Figure 1 . The research papers included in this systematic review were identified, screened and included by following the PRISMA guidelines ( Page et al., 2021 ).

The finally identified research studies were carefully analysed, and it was observed that the research studies were focused on the broader categories of students and teachers. On further analysis, the selected research studies on students were found to be in sufficient numbers to be categorised as college students and school students. However, the studies on teachers were not found in sufficient numbers to make more categories, and so, the teachers were put in one category altogether.

In the present study, the students were not categorised according to their subjects or streams that is science, commerce, humanities, medical, dental, postgraduate or undergraduate, etc. All the students were categorised into two categories only: (1) college students and (2) school students. And here, teachers were taken and presented all together in one category, may it be of school, college or university teachers.

Thus, the present systematic review was carried out by categorising the sample into three categories, viz., college students, school students and teachers, to study the opportunities, challenges and subsequent psychological impacts that were developed by the sudden shift to online teaching-learning during the COVID-19 pandemic.

The opportunities, mentioned in the literature, that online education during COVID-19 pandemic created for students and teachers

The data provided in Table 1 present the identified opportunities that online education offered to the students and teachers during the COVID-19 pandemic.

During the COVID-19 pandemic, online learning came up as an alternative ( Qanash et al. , 2020 ; Haider and Al-Salman, 2020 ; Hasan and Bao, 2020 ) which helped in adopting secure lockdown and controlling infections during the COVID-19 pandemic ( Hossain et al. , 2021 ; Khawar et al. , 2021 ; Akour et al. , 2020 ; Chaturvedi et al. , 2021 ) and, as well as in implementing “social-distancing” along with the continuation of learning ( Shrivastava et al. , 2021 ), in such a critical time. The online teaching-learning process during the COVID-19 pandemic promoted students' engagement in learning ( Unger and Meiran, 2020 ) with satisfaction ( Ma et al. , 2021 ). It also led to development of innovative ways ( Cuschieri and Agius, 2020 ) for learning, acquisition of new skills ( Cuschieri and Agius, 2020 ), and options for good communication among teachers and students for better student-teacher relationship ( Truzoli et al. , 2021 ; Stachteas and Stachteas, 2020 ; Ma et al. , 2021 ) that enhanced the whole educational process. The COVID-19 pandemic enforced  adoption to new educational technology environments which would act as a catalyst for new changes in education ( Nishimura et al. , 2021 ; Chaturvedi et al. , 2021 ) in future.

Also, educators, as a professional group, were predominantly possessed by optimism about the outcome of the COVID-19 pandemic, which was prevalent, and the unprecedented emergency implementation of distance learning did not cause them particular concern ( Stachteas and Stachteas, 2020 ). However, it was observed that students were found interested in online examinations as well as in both online with face-to-face examinations ( Dhahri et al. , 2020 ).

The challenges, described in the literature, that students and teachers faced in the rapid implementation of online education during the COVID-19 pandemic.

The rapid implementation of online education posed various challenges to all the stakeholders. Most of the students were inexperienced and new to distance and online learning ( Ma et al. , 2021 ; Qanash et al. , 2020 ); due to pandemic-forced online learning, emergency preparedness ( AlAzzam et al. , 2021 ; Unger and Meiran, 2020 ); use of same curricula as of face-to-face teaching during prompt implementation of remote and online classes ( Sundarasen et al. , 2020 ; Stachteas and Stachteas, 2020 ; Nishimura et al. , 2021 ; Chaturvedi et al. , 2021 ; AlAzzam et al. , 2021 ); inadequate learning approach that posed challenges; e-learning content costs were significantly associated variables for more serious psychological distress ( Hasan and Bao, 2020 ); changed instructional delivery and uncertainty ( Browning et al. , 2021 ; Cuschieri and Agius, 2020 ); lack of necessary technological and financial support in developing nations ( Hossain et al. (2021 ; Stachteas and Stachteas, 2020 ) to buy necessary technological tools ( Haider and Al-Salman, 2020 ; Kim and Asbury, 2020 ); lack of concentration, issues of audibility during online sessions, etc. ( Shrivastava et al. , 2021 ); familiarity with digital gadgets, type and quality of Internet connection and socio-economic status ( Khawar et al. , 2021 ; Stachteas and Stachteas, 2020 ) were quite challenging. Also, it took more time to design online instruction than the traditional material, and millennial students were found to be more comfortable although the older faculty members faced many challenges in designing instructions and in the assessment process due to their lack of practice of digital tools. Challenges during the COVID-19 pandemic situation were probing troubles to manage the educational needs by both teachers and students.

The data presented in Table 2 show the identified challenges the students and teachers face due to the sudden and abrupt shift to complete online education during the COVID-19 pandemic.

COVID-19 pandemic lockdown made the educational institutions implement online learning abruptly ( Kim and Asbury, 2020 ; Stachteas and Stachteas, 2020 ; Sundarasen et al. , 2020 ) with a limited resource ( Hossain et al. , 2021 ), with little planning ( Sundarasen et al. , 2020 ; Dhahri et al. , 2020 ) and without designing proper online instructions ( Cuschieri and Agius, 2020 ). This also resulted in a delay in the start of online teaching, leading to an unsatisfactory setup for online teaching ( Dhahri et al. , 2020 ).

To study the psychological impacts, reported in the literature, that were raised among students and teachers while switching rapidly to completely online education amid the COVID-19 pandemic.

The data presented in Table 3 show the identified psychological impacts developed among the students and teachers due to various challenges in adapting to the abrupt shift to complete online education during the COVID-19 pandemic.

The data presented in Table 4 show the empirical evaluations of psychological impacts due to online learning during the COVID-19 pandemic among students and teachers that were presented in the selected studies for this systematic review.

Thus, difficulties in online education were one of the significant predictors of depression and anxiety. Closure of institutions and delayed or abrupt online teaching raised depressive symptoms and overwhelming experience of uncertainty among students’ confidence ( Dhahri et al. , 2020 ). It was observed that the majority of students were reported to have severe to mild psychological distress which was due to the challenges they faced. Students were found to have concerns about the negative impacts of the COVID-19 pandemic on their future and career prospects ( Nishimura et al. , 2021 ). The reasons for these concerns included the belief that online education may not be as effective as on-site education, anxiety about finding online learning more time-consuming and consequently slow retention in learning online ( Unger and Meiran, 2020 ); lack of satisfaction ( Truzoli et al. , 2021 ); the possible resurgence of the COVID-19 pandemic outbreak leading to a sudden change in the curriculum and decreased clinical exposure and technical support for online education ( Nishimura et al. , 2021 ); decreased income ( Browning et al. , 2021 ); low quality of Internet service ( Akour et al. , 2020 ); lack of study area that has a conducive environment for learning, retention of information through online learning and loss of direct contact with teachers; lack of regular and routine activities ( Hossain et al. , 2021 ) and a desire to return to the previous methods of work ( Stachteas and Stachteas, 2020 ) were the significant challenges which made it more stressful. Teachers also felt distressed for being unable to help their students, faced hard times rethinking their approach to engaging the students; consequently, they felt isolated and complained about an imbalance between work and home and dismay about their professional identity in online interactions ( Kim and Asbury, 2020 ) was also observed. Despite teachers’ best efforts, the students continuously experienced increased levels of distress due to uncertainties ( AlAzzam et al. , 2021 ), and psychosomatic disorders were also significantly observed ( Haider and Al-Salman, 2020 ) among teachers also.

The COVID-19 pandemic had been a period that highlighted all these aspects of online education viz. , opportunities, challenges and psychological impacts simultaneously. From the present systematic review, it has been observed that online education alone has undoubtedly offered opportunities at all times; however, the challenges were only due to poor planning, inexperienced or unskilled handling and lack of resources and insufficient authoritative support, which ultimately has an adverse effect on the mental health. However, a well-planned and properly designed integration of digital technologies will foster learning activities ( Sevillano-García and Vázquez-Cano, 2015 ), thereby suggesting and supporting the idea of blended learning in our education system as blended learning can fill the gaps that face-to-face and online education cannot accomplish alone ( Owston, 2018 ). Therefore, in view of the present systematic review, the present study suggests adopting blended learning methodologies at various levels of education, in order to provide a healthy and well-planned balance of digital and face-to-face or in-person interactions ( Wycoff, 2018 ) as blended learning methodologies offer various models that can be used to cater to the learning needs of a learner while taking care of the psychological well-being and social-emotional support of students ( Wycoff, 2018 ), thus offering the balanced essence of online/distance/remote and face-to-face or in-person education. However, it needs to be explored further and deeper through research.

The research studies selected for the present systematic review were found to have been conducted in different scenarios and contexts of various countries of the world, which are presented in Table 5 . It revealed that most of the countries were developing nations ( Dhahri et al. , 2020 ; Hossain et al. , 2021 ; Shrivastava et al. , 2021 ) with limited resources, struggling with basic infrastructural issues, and comparatively a larger population with heterogeneity in their geographical and demographic situations. In addition to this, a major concern for such developing nations had been the socioeconomic circumstances such as larger families, low income and other such issues. Also, a few studies were identified from the developed nations ( Unger and Meiran, 2020 ; Kim and Asbury, 2020 ; Truzoli et al. , 2021 ; Nishimura et al. , 2021 ; Ma et al. , 2021 ). However, the single common component among the developed and developing nations that influenced the psychological impacts of the students and teachers was that adapting to a complete online learning environment had been a new challenge for all and everywhere, although online learning has been always there, but in a supporting and assistive role. And, many research studies identified/suggested that students and teachers would be more comfortable when online learning will be provided with some assistance or in-person training.

The major findings with respect to the opportunities, challenges and psychological impacts due to sudden online education amidst the COVID-19 pandemic are comprehensively presented in Table 6 .

Thus, the present study also revealed that the students demanded the physical presence or proper personalised interactions of teachers and peer students for an improved and enhanced learning environment, which suggests blended learning environments ( König et al. , 2020 ) by combining various educational design patterns, mobile technologies and software tools ( Milrad et al. , 2013 ). However, a well-planned and healthy balance between digital and in-person interactions purposefully implemented ( Wycoff, 2018 ) seems beneficial for the students to deal with the mental health crisis in the technologically dependent scenarios in the educational world.

The education system throughout the globe implemented online education during the COVID-19 pandemic. The COVID-19 pandemic had been a global crisis; it posed various challenges and caused numerous psychological impacts, but like the famous saying of Albert Einstein, “ in the midst of every crisis, lies great opportunity ”, it all made the stakeholders familiarise with the new innovative and advanced approaches to education and acquisition of new skills. In today’s world, when inculcating 21st-century skills in the students is ever demanded ( National Education Policy, 2020 ), this motive cannot be fulfilled without online education and digital skills. The influences of the online teaching-learning environment during the COVID-19 pandemic offered opportunities and challenges simultaneously which impacted the overall psychology of students as well as teachers. The current research identified the abrupt implementation of online education during the COVID-19 pandemic and raised various challenges and psychological impacts among students and teachers besides offering them many opportunities in a time of crisis. Teaching-learning requirements differ in relation to the degree/course, physical education, sport, gender, socioeconomic factors, etc. Therefore, it is suggested to adopt the ways for better learning and teaching for the students and teachers, respectively, and most importantly keeping the psychological well-being of the students and teachers. Thus, the present systematic review study concluded that the quality of online education should be enhanced and must be student-centred to meet their educational requirements. Furthermore, there is a need for regular counselling and other measures to enhance the students’ experiences which would be free from psychological stresses. Students and teachers constitute the educational community of society. They should get ample opportunities to develop their skills; their challenges should be tackled, and the issues harming their psychological well-being should be addressed to achieve sustained development. Moreover, it is suggested that the blended learning methodologies should be considered as it offers strategies and models that allow the students to become a part of a resilient education system in a comfortable manner that does not exert excess stress on a monotonous learning environment. Furthermore, it is recommended for the future of online and blended pedagogy to take care of the psychological well-being of both students and teachers in the teaching-learning process. It is suggested that future research may be undertaken by categorising the students and teachers according to different steams or subjects; also, teachers could be further categorised as school teachers and college or university teachers to know their opinions and situations of psychological well-being so that this aspect could also be considered while making policies and designing curriculum for students.

Selection process undertaken for the application of ECs and IC for data analysis

Identified opportunities from selected research papers

Identified challenges from selected research papers

Identified psychological impacts from selected research papers

Empirical evaluation of psychological impacts in the selected studies

Identified countries from the selected studies

Rapid implementation of online education amid COVID-19

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Impact of online classes on the satisfaction and performance of students during the pandemic period of COVID 19

• Published: 21 April 2021
• Volume 26 , pages 6923–6947, ( 2021 )

Cite this article

• Ram Gopal 1 ,
• Varsha Singh 1 &
• Arun Aggarwal   ORCID: orcid.org/0000-0003-3986-188X 2  

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The aim of the study is to identify the factors affecting students’ satisfaction and performance regarding online classes during the pandemic period of COVID–19 and to establish the relationship between these variables. The study is quantitative in nature, and the data were collected from 544 respondents through online survey who were studying the business management (B.B.A or M.B.A) or hotel management courses in Indian universities. Structural equation modeling was used to analyze the proposed hypotheses. The results show that four independent factors used in the study viz. quality of instructor, course design, prompt feedback, and expectation of students positively impact students’ satisfaction and further student’s satisfaction positively impact students’ performance. For educational management, these four factors are essential to have a high level of satisfaction and performance for online courses. This study is being conducted during the epidemic period of COVID- 19 to check the effect of online teaching on students’ performance.

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• Artificial Intelligence
• Digital Education and Educational Technology

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1 Introduction

Coronavirus is a group of viruses that is the main root of diseases like cough, cold, sneezing, fever, and some respiratory symptoms (WHO, 2019 ). Coronavirus is a contagious disease, which is spreading very fast amongst the human beings. COVID-19 is a new sprain which was originated in Wuhan, China, in December 2019. Coronavirus circulates in animals, but some of these viruses can transmit between animals and humans (Perlman & Mclntosh, 2020 ). As of March 282,020, according to the MoHFW, a total of 909 confirmed COVID-19 cases (862 Indians and 47 foreign nationals) had been reported in India (Centers for Disease Control and Prevention, 2020 ). Officially, no vaccine or medicine is evaluated to cure the spread of COVID-19 (Yu et al., 2020 ). The influence of the COVID-19 pandemic on the education system leads to schools and colleges’ widespread closures worldwide. On March 24, India declared a country-wide lockdown of schools and colleges (NDTV, 2020 ) for preventing the transmission of the coronavirus amongst the students (Bayham & Fenichel, 2020 ). School closures in response to the COVID-19 pandemic have shed light on several issues affecting access to education. COVID-19 is soaring due to which the huge number of children, adults, and youths cannot attend schools and colleges (UNESCO, 2020 ). Lah and Botelho ( 2012 ) contended that the effect of school closing on students’ performance is hazy.

Similarly, school closing may also affect students because of disruption of teacher and students’ networks, leading to poor performance. Bridge ( 2020 ) reported that schools and colleges are moving towards educational technologies for student learning to avoid a strain during the pandemic season. Hence, the present study’s objective is to develop and test a conceptual model of student’s satisfaction pertaining to online teaching during COVID-19, where both students and teachers have no other option than to use the online platform uninterrupted learning and teaching.

UNESCO recommends distance learning programs and open educational applications during school closure caused by COVID-19 so that schools and teachers use to teach their pupils and bound the interruption of education. Therefore, many institutes go for the online classes (Shehzadi et al., 2020 ).

As a versatile platform for learning and teaching processes, the E-learning framework has been increasingly used (Salloum & Shaalan, 2018 ). E-learning is defined as a new paradigm of online learning based on information technology (Moore et al., 2011 ). In contrast to traditional learning academics, educators, and other practitioners are eager to know how e-learning can produce better outcomes and academic achievements. Only by analyzing student satisfaction and their performance can the answer be sought.

Many comparative studies have been carried out to prove the point to explore whether face-to-face or traditional teaching methods are more productive or whether online or hybrid learning is better (Lockman & Schirmer, 2020 ; Pei & Wu, 2019 ; González-Gómez et al., 2016 ; González-Gómez et al., 2016 ). Results of the studies show that the students perform much better in online learning than in traditional learning. Henriksen et al. ( 2020 ) highlighted the problems faced by educators while shifting from offline to online mode of teaching. In the past, several research studies had been carried out on online learning to explore student satisfaction, acceptance of e-learning, distance learning success factors, and learning efficiency (Sher, 2009 ; Lee, 2014 ; Yen et al., 2018 ). However, scant amount of literature is available on the factors that affect the students’ satisfaction and performance in online classes during the pandemic of Covid-19 (Rajabalee & Santally, 2020 ). In the present study, the authors proposed that course design, quality of the instructor, prompt feedback, and students’ expectations are the four prominent determinants of learning outcome and satisfaction of the students during online classes (Lee, 2014 ).

The Course Design refers to curriculum knowledge, program organization, instructional goals, and course structure (Wright, 2003 ). If well planned, course design increasing the satisfaction of pupils with the system (Almaiah & Alyoussef, 2019 ). Mtebe and Raisamo ( 2014 ) proposed that effective course design will help in improving the performance through learners knowledge and skills (Khan & Yildiz, 2020 ; Mohammed et al., 2020 ). However, if the course is not designed effectively then it might lead to low usage of e-learning platforms by the teachers and students (Almaiah & Almulhem, 2018 ). On the other hand, if the course is designed effectively then it will lead to higher acceptance of e-learning system by the students and their performance also increases (Mtebe & Raisamo, 2014 ). Hence, to prepare these courses for online learning, many instructors who are teaching blended courses for the first time are likely to require a complete overhaul of their courses (Bersin, 2004 ; Ho et al., 2006 ).

The second-factor, Instructor Quality, plays an essential role in affecting the students’ satisfaction in online classes. Instructor quality refers to a professional who understands the students’ educational needs, has unique teaching skills, and understands how to meet the students’ learning needs (Luekens et al., 2004 ). Marsh ( 1987 ) developed five instruments for measuring the instructor’s quality, in which the main method was Students’ Evaluation of Educational Quality (SEEQ), which delineated the instructor’s quality. SEEQ is considered one of the methods most commonly used and embraced unanimously (Grammatikopoulos et al., 2014 ). SEEQ was a very useful method of feedback by students to measure the instructor’s quality (Marsh, 1987 ).

The third factor that improves the student’s satisfaction level is prompt feedback (Kinicki et al., 2004 ). Feedback is defined as information given by lecturers and tutors about the performance of students. Within this context, feedback is a “consequence of performance” (Hattie & Timperley, 2007 , p. 81). In education, “prompt feedback can be described as knowing what you know and what you do not related to learning” (Simsek et al., 2017 , p.334). Christensen ( 2014 ) studied linking feedback to performance and introduced the positivity ratio concept, which is a mechanism that plays an important role in finding out the performance through feedback. It has been found that prompt feedback helps in developing a strong linkage between faculty and students which ultimately leads to better learning outcomes (Simsek et al., 2017 ; Chang, 2011 ).

The fourth factor is students’ expectation . Appleton-Knapp and Krentler ( 2006 ) measured the impact of student’s expectations on their performance. They pin pointed that the student expectation is important. When the expectations of the students are achieved then it lead to the higher satisfaction level of the student (Bates & Kaye, 2014 ). These findings were backed by previous research model “Student Satisfaction Index Model” (Zhang et al., 2008 ). However, when the expectations are students is not fulfilled then it might lead to lower leaning and satisfaction with the course. Student satisfaction is defined as students’ ability to compare the desired benefit with the observed effect of a particular product or service (Budur et al., 2019 ). Students’ whose grade expectation is high will show high satisfaction instead of those facing lower grade expectations.

The scrutiny of the literature show that although different researchers have examined the factors affecting student satisfaction but none of the study has examined the effect of course design, quality of the instructor, prompt feedback, and students’ expectations on students’ satisfaction with online classes during the pandemic period of Covid-19. Therefore, this study tries to explore the factors that affect students’ satisfaction and performance regarding online classes during the pandemic period of COVID–19. As the pandemic compelled educational institutions to move online with which they were not acquainted, including teachers and learners. The students were not mentally prepared for such a shift. Therefore, this research will be examined to understand what factors affect students and how students perceived these changes which are reflected through their satisfaction level.

This paper is structured as follows: The second section provides a description of theoretical framework and the linkage among different research variables and accordingly different research hypotheses were framed. The third section deals with the research methodology of the paper as per APA guideline. The outcomes and corresponding results of the empirical analysis are then discussed. Lastly, the paper concludes with a discussion and proposes implications for future studies.

2 Theoretical framework

Achievement goal theory (AGT) is commonly used to understand the student’s performance, and it is proposed by four scholars Carole Ames, Carol Dweck, Martin Maehr, and John Nicholls in the late 1970s (Elliot, 2005 ). Elliott & Dweck ( 1988 , p11) define that “an achievement goal involves a program of cognitive processes that have cognitive, affective and behavioral consequence”. This theory suggests that students’ motivation and achievement-related behaviors can be easily understood by the purpose and the reasons they adopted while they are engaged in the learning activities (Dweck & Leggett, 1988 ; Ames, 1992 ; Urdan, 1997 ). Some of the studies believe that there are four approaches to achieve a goal, i.e., mastery-approach, mastery avoidance, performance approach, and performance-avoidance (Pintrich, 1999 ; Elliot & McGregor, 2001 ; Schwinger & Stiensmeier-Pelster, 2011 , Hansen & Ringdal, 2018 ; Mouratidis et al., 2018 ). The environment also affects the performance of students (Ames & Archer, 1988 ). Traditionally, classroom teaching is an effective method to achieve the goal (Ames & Archer, 1988 ; Ames, 1992 ; Clayton et al., 2010 ) however in the modern era, the internet-based teaching is also one of the effective tools to deliver lectures, and web-based applications are becoming modern classrooms (Azlan et al., 2020 ). Hence, following section discuss about the relationship between different independent variables and dependent variables (Fig. 1 ).

Proposed Model

3 Hypotheses development

3.1 quality of the instructor and satisfaction of the students.

Quality of instructor with high fanaticism on student’s learning has a positive impact on their satisfaction. Quality of instructor is one of the most critical measures for student satisfaction, leading to the education process’s outcome (Munteanu et al., 2010 ; Arambewela & Hall, 2009 ; Ramsden, 1991 ). Suppose the teacher delivers the course effectively and influence the students to do better in their studies. In that case, this process leads to student satisfaction and enhances the learning process (Ladyshewsky, 2013 ). Furthermore, understanding the need of learner by the instructor also ensures student satisfaction (Kauffman, 2015 ). Hence the hypothesis that the quality of instructor significantly affects the satisfaction of the students was included in this study.

H1: The quality of the instructor positively affects the satisfaction of the students.

3.2 Course design and satisfaction of students

The course’s technological design is highly persuading the students’ learning and satisfaction through their course expectations (Liaw, 2008 ; Lin et al., 2008 ). Active course design indicates the students’ effective outcomes compared to the traditional design (Black & Kassaye, 2014 ). Learning style is essential for effective course design (Wooldridge, 1995 ). While creating an online course design, it is essential to keep in mind that we generate an experience for students with different learning styles. Similarly, (Jenkins, 2015 ) highlighted that the course design attributes could be developed and employed to enhance student success. Hence the hypothesis that the course design significantly affects students’ satisfaction was included in this study.

H2: Course design positively affects the satisfaction of students.

3.3 Prompt feedback and satisfaction of students

The emphasis in this study is to understand the influence of prompt feedback on satisfaction. Feedback gives the information about the students’ effective performance (Chang, 2011 ; Grebennikov & Shah, 2013 ; Simsek et al., 2017 ). Prompt feedback enhances student learning experience (Brownlee et al., 2009 ) and boosts satisfaction (O'donovan, 2017 ). Prompt feedback is the self-evaluation tool for the students (Rogers, 1992 ) by which they can improve their performance. Eraut ( 2006 ) highlighted the impact of feedback on future practice and student learning development. Good feedback practice is beneficial for student learning and teachers to improve students’ learning experience (Yorke, 2003 ). Hence the hypothesis that prompt feedback significantly affects satisfaction was included in this study.

H3: Prompt feedback of the students positively affects the satisfaction.

3.4 Expectations and satisfaction of students

Expectation is a crucial factor that directly influences the satisfaction of the student. Expectation Disconfirmation Theory (EDT) (Oliver, 1980 ) was utilized to determine the level of satisfaction based on their expectations (Schwarz & Zhu, 2015 ). Student’s expectation is the best way to improve their satisfaction (Brown et al., 2014 ). It is possible to recognize student expectations to progress satisfaction level (ICSB, 2015 ). Finally, the positive approach used in many online learning classes has been shown to place a high expectation on learners (Gold, 2011 ) and has led to successful outcomes. Hence the hypothesis that expectations of the student significantly affect the satisfaction was included in this study.

H4: Expectations of the students positively affects the satisfaction.

3.5 Satisfaction and performance of the students

Zeithaml ( 1988 ) describes that satisfaction is the outcome result of the performance of any educational institute. According to Kotler and Clarke ( 1986 ), satisfaction is the desired outcome of any aim that amuses any individual’s admiration. Quality interactions between instructor and students lead to student satisfaction (Malik et al., 2010 ; Martínez-Argüelles et al., 2016 ). Teaching quality and course material enhances the student satisfaction by successful outcomes (Sanderson, 1995 ). Satisfaction relates to the student performance in terms of motivation, learning, assurance, and retention (Biner et al., 1996 ). Mensink and King ( 2020 ) described that performance is the conclusion of student-teacher efforts, and it shows the interest of students in the studies. The critical element in education is students’ academic performance (Rono, 2013 ). Therefore, it is considered as center pole, and the entire education system rotates around the student’s performance. Narad and Abdullah ( 2016 ) concluded that the students’ academic performance determines academic institutions’ success and failure.

Singh et al. ( 2016 ) asserted that the student academic performance directly influences the country’s socio-economic development. Farooq et al. ( 2011 ) highlights the students’ academic performance is the primary concern of all faculties. Additionally, the main foundation of knowledge gaining and improvement of skills is student’s academic performance. According to Narad and Abdullah ( 2016 ), regular evaluation or examinations is essential over a specific period of time in assessing students’ academic performance for better outcomes. Hence the hypothesis that satisfaction significantly affects the performance of the students was included in this study.

H5: Students’ satisfaction positively affects the performance of the students.

3.6 Satisfaction as mediator

Sibanda et al. ( 2015 ) applied the goal theory to examine the factors persuading students’ academic performance that enlightens students’ significance connected to their satisfaction and academic achievement. According to this theory, students perform well if they know about factors that impact on their performance. Regarding the above variables, institutional factors that influence student satisfaction through performance include course design and quality of the instructor (DeBourgh, 2003 ; Lado et al., 2003 ), prompt feedback, and expectation (Fredericksen et al., 2000 ). Hence the hypothesis that quality of the instructor, course design, prompts feedback, and student expectations significantly affect the students’ performance through satisfaction was included in this study.

H6: Quality of the instructor, course design, prompt feedback, and student’ expectations affect the students’ performance through satisfaction.

H6a: Students’ satisfaction mediates the relationship between quality of the instructor and student’s performance.

H6b: Students’ satisfaction mediates the relationship between course design and student’s performance.

H6c: Students’ satisfaction mediates the relationship between prompt feedback and student’s performance.

H6d: Students’ satisfaction mediates the relationship between student’ expectations and student’s performance.

4.1 Participants

In this cross-sectional study, the data were collected from 544 respondents who were studying the management (B.B.A or M.B.A) and hotel management courses. The purposive sampling technique was used to collect the data. Descriptive statistics shows that 48.35% of the respondents were either MBA or BBA and rests of the respondents were hotel management students. The percentages of male students were (71%) and female students were (29%). The percentage of male students is almost double in comparison to females. The ages of the students varied from 18 to 35. The dominant group was those aged from 18 to 22, and which was the under graduation student group and their ratio was (94%), and another set of students were from the post-graduation course, which was (6%) only.

4.2 Materials

The research instrument consists of two sections. The first section is related to demographical variables such as discipline, gender, age group, and education level (under-graduate or post-graduate). The second section measures the six factors viz. instructor’s quality, course design, prompt feedback, student expectations, satisfaction, and performance. These attributes were taken from previous studies (Yin & Wang, 2015 ; Bangert, 2004 ; Chickering & Gamson, 1987 ; Wilson et al., 1997 ). The “instructor quality” was measured through the scale developed by Bangert ( 2004 ). The scale consists of seven items. The “course design” and “prompt feedback” items were adapted from the research work of Bangert ( 2004 ). The “course design” scale consists of six items. The “prompt feedback” scale consists of five items. The “students’ expectation” scale consists of five items. Four items were adapted from Bangert, 2004 and one item was taken from Wilson et al. ( 1997 ). Students’ satisfaction was measure with six items taken from Bangert ( 2004 ); Wilson et al. ( 1997 ); Yin and Wang ( 2015 ). The “students’ performance” was measured through the scale developed by Wilson et al. ( 1997 ). The scale consists of six items. These variables were accessed on a five-point likert scale, ranging from 1(strongly disagree) to 5(strongly agree). Only the students from India have taken part in the survey. A total of thirty-four questions were asked in the study to check the effect of the first four variables on students’ satisfaction and performance. For full details of the questionnaire, kindly refer Appendix Tables 6 .

The study used a descriptive research design. The factors “instructor quality, course design, prompt feedback and students’ expectation” were independent variables. The students’ satisfaction was mediator and students’ performance was the dependent variable in the current study.

4.4 Procedure

In this cross-sectional research the respondents were selected through judgment sampling. They were informed about the objective of the study and information gathering process. They were assured about the confidentiality of the data and no incentive was given to then for participating in this study. The information utilizes for this study was gathered through an online survey. The questionnaire was built through Google forms, and then it was circulated through the mails. Students’ were also asked to write the name of their college, and fifteen colleges across India have taken part to fill the data. The data were collected in the pandemic period of COVID-19 during the total lockdown in India. This was the best time to collect the data related to the current research topic because all the colleges across India were involved in online classes. Therefore, students have enough time to understand the instrument and respondent to the questionnaire in an effective manner. A total of 615 questionnaires were circulated, out of which the students returned 574. Thirty responses were not included due to the unengaged responses. Finally, 544 questionnaires were utilized in the present investigation. Male and female students both have taken part to fill the survey, different age groups, and various courses, i.e., under graduation and post-graduation students of management and hotel management students were the part of the sample.

5.1 Exploratory factor analysis (EFA)

To analyze the data, SPSS and AMOS software were used. First, to extract the distinct factors, an exploratory factor analysis (EFA) was performed using VARIMAX rotation on a sample of 544. Results of the exploratory analysis rendered six distinct factors. Factor one was named as the quality of instructor, and some of the items were “The instructor communicated effectively”, “The instructor was enthusiastic about online teaching” and “The instructor was concerned about student learning” etc. Factor two was labeled as course design, and the items were “The course was well organized”, “The course was designed to allow assignments to be completed across different learning environments.” and “The instructor facilitated the course effectively” etc. Factor three was labeled as prompt feedback of students, and some of the items were “The instructor responded promptly to my questions about the use of Webinar”, “The instructor responded promptly to my questions about general course requirements” etc. The fourth factor was Student’s Expectations, and the items were “The instructor provided models that clearly communicated expectations for weekly group assignments”, “The instructor used good examples to explain statistical concepts” etc. The fifth factor was students’ satisfaction, and the items were “The online classes were valuable”, “Overall, I am satisfied with the quality of this course” etc. The sixth factor was performance of the student, and the items were “The online classes has sharpened my analytic skills”, “Online classes really tries to get the best out of all its students” etc. These six factors explained 67.784% of the total variance. To validate the factors extracted through EFA, the researcher performed confirmatory factor analysis (CFA) through AMOS. Finally, structural equation modeling (SEM) was used to test the hypothesized relationships.

5.2 Measurement model

The results of Table 1 summarize the findings of EFA and CFA. Results of the table showed that EFA renders six distinct factors, and CFA validated these factors. Table 2 shows that the proposed measurement model achieved good convergent validity (Aggarwal et al., 2018a , b ). Results of the confirmatory factor analysis showed that the values of standardized factor loadings were statistically significant at the 0.05 level. Further, the results of the measurement model also showed acceptable model fit indices such that CMIN = 710.709; df = 480; CMIN/df = 1.481 p  < .000; Incremental Fit Index (IFI) = 0.979; Tucker-Lewis Index (TLI) = 0.976; Goodness of Fit index (GFI) = 0.928; Adjusted Goodness of Fit Index (AGFI) = 0.916; Comparative Fit Index (CFI) = 0.978; Root Mean Square Residual (RMR) = 0.042; Root Mean Squared Error of Approximation (RMSEA) = 0.030 is satisfactory.

The Average Variance Explained (AVE) according to the acceptable index should be higher than the value of squared correlations between the latent variables and all other variables. The discriminant validity is confirmed (Table 2 ) as the value of AVE’s square root is greater than the inter-construct correlations coefficient (Hair et al., 2006 ). Additionally, the discriminant validity existed when there was a low correlation between each variable measurement indicator with all other variables except with the one with which it must be theoretically associated (Aggarwal et al., 2018a , b ; Aggarwal et al., 2020 ). The results of Table 2 show that the measurement model achieved good discriminate validity.

5.3 Structural model

To test the proposed hypothesis, the researcher used the structural equation modeling technique. This is a multivariate statistical analysis technique, and it includes the amalgamation of factor analysis and multiple regression analysis. It is used to analyze the structural relationship between measured variables and latent constructs.

Table  3 represents the structural model’s model fitness indices where all variables put together when CMIN/DF is 2.479, and all the model fit values are within the particular range. That means the model has attained a good model fit. Furthermore, other fit indices as GFI = .982 and AGFI = 0.956 be all so supportive (Schumacker & Lomax, 1996 ; Marsh & Grayson, 1995 ; Kline, 2005 ).

Hence, the model fitted the data successfully. All co-variances among the variables and regression weights were statistically significant ( p  < 0.001).

Table 4 represents the relationship between exogenous, mediator and endogenous variables viz—quality of instructor, prompt feedback, course design, students’ expectation, students’ satisfaction and students’ performance. The first four factors have a positive relationship with satisfaction, which further leads to students’ performance positively. Results show that the instructor’s quality has a positive relationship with the satisfaction of students for online classes (SE = 0.706, t-value = 24.196; p  < 0.05). Hence, H1 was supported. The second factor is course design, which has a positive relationship with students’ satisfaction of students (SE = 0.064, t-value = 2.395; p < 0.05). Hence, H2 was supported. The third factor is Prompt feedback, and results show that feedback has a positive relationship with the satisfaction of the students (SE = 0.067, t-value = 2.520; p < 0.05). Hence, H3 was supported. The fourth factor is students’ expectations. The results show a positive relationship between students’ expectation and students’ satisfaction with online classes (SE = 0.149, t-value = 5.127; p < 0.05). Hence, H4 was supported. The results of SEM show that out of quality of instructor, prompt feedback, course design, and students’ expectation, the most influencing factor that affect the students’ satisfaction was instructor’s quality (SE = 0.706) followed by students’ expectation (SE =5.127), prompt feedback (SE = 2.520). The factor that least affects the students’ satisfaction was course design (2.395). The results of Table 4 finally depicts that students’ satisfaction has positive effect on students’ performance ((SE = 0.186, t-value = 2.800; p < 0.05). Hence H5 was supported.

Table 5 shows that students’ satisfaction partially mediates the positive relationship between the instructor’s quality and student performance. Hence, H6(a) was supported. Further, the mediation analysis results showed that satisfaction again partially mediates the positive relationship between course design and student’s performance. Hence, H6(b) was supported However, the mediation analysis results showed that satisfaction fully mediates the positive relationship between prompt feedback and student performance. Hence, H6(c) was supported. Finally, the results of the Table 5 showed that satisfaction partially mediates the positive relationship between expectations of the students and student’s performance. Hence, H6(d) was supported.

6 Discussion

In the present study, the authors evaluated the different factors directly linked with students’ satisfaction and performance with online classes during Covid-19. Due to the pandemic situation globally, all the colleges and universities were shifted to online mode by their respective governments. No one has the information that how long this pandemic will remain, and hence the teaching method was shifted to online mode. Even though some of the educators were not tech-savvy, they updated themselves to battle the unexpected circumstance (Pillai et al., 2021 ). The present study results will help the educators increase the student’s satisfaction and performance in online classes. The current research assists educators in understanding the different factors that are required for online teaching.

Comparing the current research with past studies, the past studies have examined the factors affecting the student’s satisfaction in the conventional schooling framework. However, the present study was conducted during India’s lockdown period to identify the prominent factors that derive the student’s satisfaction with online classes. The study also explored the direct linkage between student’s satisfaction and their performance. The present study’s findings indicated that instructor’s quality is the most prominent factor that affects the student’s satisfaction during online classes. This means that the instructor needs to be very efficient during the lectures. He needs to understand students’ psychology to deliver the course content prominently. If the teacher can deliver the course content properly, it affects the student’s satisfaction and performance. The teachers’ perspective is critical because their enthusiasm leads to a better online learning process quality.

The present study highlighted that the second most prominent factor affecting students’ satisfaction during online classes is the student’s expectations. Students might have some expectations during the classes. If the instructor understands that expectation and customizes his/her course design following the student’s expectations, then it is expected that the students will perform better in the examinations. The third factor that affects the student’s satisfaction is feedback. After delivering the course, appropriate feedback should be taken by the instructors to plan future courses. It also helps to make the future strategies (Tawafak et al., 2019 ). There must be a proper feedback system for improvement because feedback is the course content’s real image. The last factor that affects the student’s satisfaction is design. The course content needs to be designed in an effective manner so that students should easily understand it. If the instructor plans the course, so the students understand the content without any problems it effectively leads to satisfaction, and the student can perform better in the exams. In some situations, the course content is difficult to deliver in online teaching like the practical part i.e. recipes of dishes or practical demonstration in the lab. In such a situation, the instructor needs to be more creative in designing and delivering the course content so that it positively impacts the students’ overall satisfaction with online classes.

Overall, the students agreed that online teaching was valuable for them even though the online mode of classes was the first experience during the pandemic period of Covid-19 (Agarwal & Kaushik, 2020 ; Rajabalee & Santally, 2020 ). Some of the previous studies suggest that the technology-supported courses have a positive relationship with students’ performance (Cho & Schelzer, 2000 ; Harasim, 2000 ; Sigala, 2002 ). On the other hand, the demographic characteristic also plays a vital role in understanding the online course performance. According to APA Work Group of the Board of Educational Affairs ( 1997 ), the learner-centered principles suggest that students must be willing to invest the time required to complete individual course assignments. Online instructors must be enthusiastic about developing genuine instructional resources that actively connect learners and encourage them toward proficient performances. For better performance in studies, both teachers and students have equal responsibility. When the learner faces any problem to understand the concepts, he needs to make inquiries for the instructor’s solutions (Bangert, 2004 ). Thus, we can conclude that “instructor quality, student’s expectation, prompt feedback, and effective course design” significantly impact students’ online learning process.

7 Implications of the study

The results of this study have numerous significant practical implications for educators, students and researchers. It also contributes to the literature by demonstrating that multiple factors are responsible for student satisfaction and performance in the context of online classes during the period of the COVID-19 pandemic. This study was different from the previous studies (Baber, 2020 ; Ikhsan et al., 2019 ; Eom & Ashill, 2016 ). None of the studies had examined the effect of students’ satisfaction on their perceived academic performance. The previous empirical findings have highlighted the importance of examining the factors affecting student satisfaction (Maqableh & Jaradat, 2021 ; Yunusa & Umar, 2021 ). Still, none of the studies has examined the effect of course design, quality of instructor, prompt feedback, and students’ expectations on students’ satisfaction all together with online classes during the pandemic period. The present study tries to fill this research gap.

The first essential contribution of this study was the instructor’s facilitating role, and the competence he/she possesses affects the level of satisfaction of the students (Gray & DiLoreto, 2016 ). There was an extra obligation for instructors who taught online courses during the pandemic. They would have to adapt to a changing climate, polish their technical skills throughout the process, and foster new students’ technical knowledge in this environment. The present study’s findings indicate that instructor quality is a significant determinant of student satisfaction during online classes amid a pandemic. In higher education, the teacher’s standard referred to the instructor’s specific individual characteristics before entering the class (Darling-Hammond, 2010 ). These attributes include factors such as instructor content knowledge, pedagogical knowledge, inclination, and experience. More significantly, at that level, the amount of understanding could be given by those who have a significant amount of technical expertise in the areas they are teaching (Martin, 2021 ). Secondly, the present study results contribute to the profession of education by illustrating a realistic approach that can be used to recognize students’ expectations in their class effectively. The primary expectation of most students before joining a university is employment. Instructors have agreed that they should do more to fulfill students’ employment expectations (Gorgodze et al., 2020 ). The instructor can then use that to balance expectations to improve student satisfaction. Study results can be used to continually improve and build courses, as well as to make policy decisions to improve education programs. Thirdly, from result outcomes, online course design and instructors will delve deeper into how to structure online courses more efficiently, including design features that minimize adversely and maximize optimistic emotion, contributing to greater student satisfaction (Martin et al., 2018 ). The findings suggest that the course design has a substantial positive influence on the online class’s student performance. The findings indicate that the course design of online classes need to provide essential details like course content, educational goals, course structure, and course output in a consistent manner so that students would find the e-learning system beneficial for them; this situation will enable students to use the system and that leads to student performance (Almaiah & Alyoussef, 2019 ). Lastly, the results indicate that instructors respond to questions promptly and provide timely feedback on assignments to facilitate techniques that help students in online courses improve instructor participation, instructor interaction, understanding, and participation (Martin et al., 2018 ). Feedback can be beneficial for students to focus on the performance that enhances their learning.

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Gopal, R., Singh, V. & Aggarwal, A. Impact of online classes on the satisfaction and performance of students during the pandemic period of COVID 19. Educ Inf Technol 26 , 6923–6947 (2021). https://doi.org/10.1007/s10639-021-10523-1

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Received : 07 December 2020

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Issue Date : November 2021

DOI : https://doi.org/10.1007/s10639-021-10523-1

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A systematic review of research on online teaching and learning from 2009 to 2018

Associated data.

Systematic reviews were conducted in the nineties and early 2000's on online learning research. However, there is no review examining the broader aspect of research themes in online learning in the last decade. This systematic review addresses this gap by examining 619 research articles on online learning published in twelve journals in the last decade. These studies were examined for publication trends and patterns, research themes, research methods, and research settings and compared with the research themes from the previous decades. While there has been a slight decrease in the number of studies on online learning in 2015 and 2016, it has then continued to increase in 2017 and 2018. The majority of the studies were quantitative in nature and were examined in higher education. Online learning research was categorized into twelve themes and a framework across learner, course and instructor, and organizational levels was developed. Online learner characteristics and online engagement were examined in a high number of studies and were consistent with three of the prior systematic reviews. However, there is still a need for more research on organization level topics such as leadership, policy, and management and access, culture, equity, inclusion, and ethics and also on online instructor characteristics.

• • Twelve online learning research themes were identified in 2009–2018.
• • A framework with learner, course and instructor, and organizational levels was used.
• • Online learner characteristics and engagement were the mostly examined themes.
• • The majority of the studies used quantitative research methods and in higher education.
• • There is a need for more research on organization level topics.

1. Introduction

Online learning has been on the increase in the last two decades. In the United States, though higher education enrollment has declined, online learning enrollment in public institutions has continued to increase ( Allen & Seaman, 2017 ), and so has the research on online learning. There have been review studies conducted on specific areas on online learning such as innovations in online learning strategies ( Davis et al., 2018 ), empirical MOOC literature ( Liyanagunawardena et al., 2013 ; Veletsianos & Shepherdson, 2016 ; Zhu et al., 2018 ), quality in online education ( Esfijani, 2018 ), accessibility in online higher education ( Lee, 2017 ), synchronous online learning ( Martin et al., 2017 ), K-12 preparation for online teaching ( Moore-Adams et al., 2016 ), polychronicity in online learning ( Capdeferro et al., 2014 ), meaningful learning research in elearning and online learning environments ( Tsai, Shen, & Chiang, 2013 ), problem-based learning in elearning and online learning environments ( Tsai & Chiang, 2013 ), asynchronous online discussions ( Thomas, 2013 ), self-regulated learning in online learning environments ( Tsai, Shen, & Fan, 2013 ), game-based learning in online learning environments ( Tsai & Fan, 2013 ), and online course dropout ( Lee & Choi, 2011 ). While there have been review studies conducted on specific online learning topics, very few studies have been conducted on the broader aspect of online learning examining research themes.

2. Systematic Reviews of Distance Education and Online Learning Research

Distance education has evolved from offline to online settings with the access to internet and COVID-19 has made online learning the common delivery method across the world. Tallent-Runnels et al. (2006) reviewed research late 1990's to early 2000's, Berge and Mrozowski (2001) reviewed research 1990 to 1999, and Zawacki-Richter et al. (2009) reviewed research in 2000–2008 on distance education and online learning. Table 1 shows the research themes from previous systematic reviews on online learning research. There are some themes that re-occur in the various reviews, and there are also new themes that emerge. Though there have been reviews conducted in the nineties and early 2000's, there is no review examining the broader aspect of research themes in online learning in the last decade. Hence, the need for this systematic review which informs the research themes in online learning from 2009 to 2018. In the following sections, we review these systematic review studies in detail.

Comparison of online learning research themes from previous studies.

2.1. Distance education research themes, 1990 to 1999 ( Berge & Mrozowski, 2001 )

Berge and Mrozowski (2001) reviewed 890 research articles and dissertation abstracts on distance education from 1990 to 1999. The four distance education journals chosen by the authors to represent distance education included, American Journal of Distance Education, Distance Education, Open Learning, and the Journal of Distance Education. This review overlapped in the dates of the Tallent-Runnels et al. (2006) study. Berge and Mrozowski (2001) categorized the articles according to Sherry's (1996) ten themes of research issues in distance education: redefining roles of instructor and students, technologies used, issues of design, strategies to stimulate learning, learner characteristics and support, issues related to operating and policies and administration, access and equity, and costs and benefits.

In the Berge and Mrozowski (2001) study, more than 100 studies focused on each of the three themes: (1) design issues, (2) learner characteristics, and (3) strategies to increase interactivity and active learning. By design issues, the authors focused on instructional systems design and focused on topics such as content requirement, technical constraints, interactivity, and feedback. The next theme, strategies to increase interactivity and active learning, were closely related to design issues and focused on students’ modes of learning. Learner characteristics focused on accommodating various learning styles through customized instructional theory. Less than 50 studies focused on the three least examined themes: (1) cost-benefit tradeoffs, (2) equity and accessibility, and (3) learner support. Cost-benefit trade-offs focused on the implementation costs of distance education based on school characteristics. Equity and accessibility focused on the equity of access to distance education systems. Learner support included topics such as teacher to teacher support as well as teacher to student support.

2.2. Online learning research themes, 1993 to 2004 ( Tallent-Runnels et al., 2006 )

Tallent-Runnels et al. (2006) reviewed research on online instruction from 1993 to 2004. They reviewed 76 articles focused on online learning by searching five databases, ERIC, PsycINFO, ContentFirst, Education Abstracts, and WilsonSelect. Tallent-Runnels et al. (2006) categorized research into four themes, (1) course environment, (2) learners' outcomes, (3) learners’ characteristics, and (4) institutional and administrative factors. The first theme that the authors describe as course environment ( n  = 41, 53.9%) is an overarching theme that includes classroom culture, structural assistance, success factors, online interaction, and evaluation.

Tallent-Runnels et al. (2006) for their second theme found that studies focused on questions involving the process of teaching and learning and methods to explore cognitive and affective learner outcomes ( n  = 29, 38.2%). The authors stated that they found the research designs flawed and lacked rigor. However, the literature comparing traditional and online classrooms found both delivery systems to be adequate. Another research theme focused on learners’ characteristics ( n  = 12, 15.8%) and the synergy of learners, design of the online course, and system of delivery. Research findings revealed that online learners were mainly non-traditional, Caucasian, had different learning styles, and were highly motivated to learn. The final theme that they reported was institutional and administrative factors (n  = 13, 17.1%) on online learning. Their findings revealed that there was a lack of scholarly research in this area and most institutions did not have formal policies in place for course development as well as faculty and student support in training and evaluation. Their research confirmed that when universities offered online courses, it improved student enrollment numbers.

2.3. Distance education research themes 2000 to 2008 ( Zawacki-Richter et al., 2009 )

Zawacki-Richter et al. (2009) reviewed 695 articles on distance education from 2000 to 2008 using the Delphi method for consensus in identifying areas and classified the literature from five prominent journals. The five journals selected due to their wide scope in research in distance education included Open Learning, Distance Education, American Journal of Distance Education, the Journal of Distance Education, and the International Review of Research in Open and Distributed Learning. The reviewers examined the main focus of research and identified gaps in distance education research in this review.

Zawacki-Richter et al. (2009) classified the studies into macro, meso and micro levels focusing on 15 areas of research. The five areas of the macro-level addressed: (1) access, equity and ethics to deliver distance education for developing nations and the role of various technologies to narrow the digital divide, (2) teaching and learning drivers, markets, and professional development in the global context, (3) distance delivery systems and institutional partnerships and programs and impact of hybrid modes of delivery, (4) theoretical frameworks and models for instruction, knowledge building, and learner interactions in distance education practice, and (5) the types of preferred research methodologies. The meso-level focused on seven areas that involve: (1) management and organization for sustaining distance education programs, (2) examining financial aspects of developing and implementing online programs, (3) the challenges and benefits of new technologies for teaching and learning, (4) incentives to innovate, (5) professional development and support for faculty, (6) learner support services, and (7) issues involving quality standards and the impact on student enrollment and retention. The micro-level focused on three areas: (1) instructional design and pedagogical approaches, (2) culturally appropriate materials, interaction, communication, and collaboration among a community of learners, and (3) focus on characteristics of adult learners, socio-economic backgrounds, learning preferences, and dispositions.

The top three research themes in this review by Zawacki-Richter et al. (2009) were interaction and communities of learning ( n  = 122, 17.6%), instructional design ( n  = 121, 17.4%) and learner characteristics ( n  = 113, 16.3%). The lowest number of studies (less than 3%) were found in studies examining the following research themes, management and organization ( n  = 18), research methods in DE and knowledge transfer ( n  = 13), globalization of education and cross-cultural aspects ( n  = 13), innovation and change ( n  = 13), and costs and benefits ( n  = 12).

2.4. Online learning research themes

These three systematic reviews provide a broad understanding of distance education and online learning research themes from 1990 to 2008. However, there is an increase in the number of research studies on online learning in this decade and there is a need to identify recent research themes examined. Based on the previous systematic reviews ( Berge & Mrozowski, 2001 ; Hung, 2012 ; Tallent-Runnels et al., 2006 ; Zawacki-Richter et al., 2009 ), online learning research in this study is grouped into twelve different research themes which include Learner characteristics, Instructor characteristics, Course or program design and development, Course Facilitation, Engagement, Course Assessment, Course Technologies, Access, Culture, Equity, Inclusion, and Ethics, Leadership, Policy and Management, Instructor and Learner Support, and Learner Outcomes. Table 2 below describes each of the research themes and using these themes, a framework is derived in Fig. 1 .

Research themes in online learning.

Online learning research themes framework.

The collection of research themes is presented as a framework in Fig. 1 . The themes are organized by domain or level to underscore the nested relationship that exists. As evidenced by the assortment of themes, research can focus on any domain of delivery or associated context. The “Learner” domain captures characteristics and outcomes related to learners and their interaction within the courses. The “Course and Instructor” domain captures elements about the broader design of the course and facilitation by the instructor, and the “Organizational” domain acknowledges the contextual influences on the course. It is important to note as well that due to the nesting, research themes can cross domains. For example, the broader cultural context may be studied as it pertains to course design and development, and institutional support can include both learner support and instructor support. Likewise, engagement research can involve instructors as well as learners.

In this introduction section, we have reviewed three systematic reviews on online learning research ( Berge & Mrozowski, 2001 ; Tallent-Runnels et al., 2006 ; Zawacki-Richter et al., 2009 ). Based on these reviews and other research, we have derived twelve themes to develop an online learning research framework which is nested in three levels: learner, course and instructor, and organization.

2.5. Purpose of this research

In two out of the three previous reviews, design, learner characteristics and interaction were examined in the highest number of studies. On the other hand, cost-benefit tradeoffs, equity and accessibility, institutional and administrative factors, and globalization and cross-cultural aspects were examined in the least number of studies. One explanation for this may be that it is a function of nesting, noting that studies falling in the Organizational and Course levels may encompass several courses or many more participants within courses. However, while some research themes re-occur, there are also variations in some themes across time, suggesting the importance of research themes rise and fall over time. Thus, a critical examination of the trends in themes is helpful for understanding where research is needed most. Also, since there is no recent study examining online learning research themes in the last decade, this study strives to address that gap by focusing on recent research themes found in the literature, and also reviewing research methods and settings. Notably, one goal is to also compare findings from this decade to the previous review studies. Overall, the purpose of this study is to examine publication trends in online learning research taking place during the last ten years and compare it with the previous themes identified in other review studies. Due to the continued growth of online learning research into new contexts and among new researchers, we also examine the research methods and settings found in the studies of this review.

The following research questions are addressed in this study.

• 1. What percentage of the population of articles published in the journals reviewed from 2009 to 2018 were related to online learning and empirical?
• 2. What is the frequency of online learning research themes in the empirical online learning articles of journals reviewed from 2009 to 2018?
• 3. What is the frequency of research methods and settings that researchers employed in the empirical online learning articles of the journals reviewed from 2009 to 2018?

This five-step systematic review process described in the U.S. Department of Education, Institute of Education Sciences, What Works Clearinghouse Procedures and Standards Handbook, Version 4.0 ( 2017 ) was used in this systematic review: (a) developing the review protocol, (b) identifying relevant literature, (c) screening studies, (d) reviewing articles, and (e) reporting findings.

3.1. Data sources and search strategies

The Education Research Complete database was searched using the keywords below for published articles between the years 2009 and 2018 using both the Title and Keyword function for the following search terms.

“online learning" OR "online teaching" OR "online program" OR "online course" OR “online education”

3.2. Inclusion/exclusion criteria

The initial search of online learning research among journals in the database resulted in more than 3000 possible articles. Therefore, we limited our search to select journals that focus on publishing peer-reviewed online learning and educational research. Our aim was to capture the journals that published the most articles in online learning. However, we also wanted to incorporate the concept of rigor, so we used expert perception to identify 12 peer-reviewed journals that publish high-quality online learning research. Dissertations and conference proceedings were excluded. To be included in this systematic review, each study had to meet the screening criteria as described in Table 3 . A research study was excluded if it did not meet all of the criteria to be included.

Inclusion/Exclusion criteria.

3.3. Process flow selection of articles

Fig. 2 shows the process flow involved in the selection of articles. The search in the database Education Research Complete yielded an initial sample of 3332 articles. Targeting the 12 journals removed 2579 articles. After reviewing the abstracts, we removed 134 articles based on the inclusion/exclusion criteria. The final sample, consisting of 619 articles, was entered into the computer software MAXQDA ( VERBI Software, 2019 ) for coding.

Flowchart of online learning research selection.

3.4. Developing review protocol

A review protocol was designed as a codebook in MAXQDA ( VERBI Software, 2019 ) by the three researchers. The codebook was developed based on findings from the previous review studies and from the initial screening of the articles in this review. The codebook included 12 research themes listed earlier in Table 2 (Learner characteristics, Instructor characteristics, Course or program design and development, Course Facilitation, Engagement, Course Assessment, Course Technologies, Access, Culture, Equity, Inclusion, and Ethics, Leadership, Policy and Management, Instructor and Learner Support, and Learner Outcomes), four research settings (higher education, continuing education, K-12, corporate/military), and three research designs (quantitative, qualitative and mixed methods). Fig. 3 below is a screenshot of MAXQDA used for the coding process.

Codebook from MAXQDA.

3.5. Data coding

Research articles were coded by two researchers in MAXQDA. Two researchers independently coded 10% of the articles and then discussed and updated the coding framework. The second author who was a doctoral student coded the remaining studies. The researchers met bi-weekly to address coding questions that emerged. After the first phase of coding, we found that more than 100 studies fell into each of the categories of Learner Characteristics or Engagement, so we decided to pursue a second phase of coding and reexamine the two themes. Learner Characteristics were classified into the subthemes of Academic, Affective, Motivational, Self-regulation, Cognitive, and Demographic Characteristics. Engagement was classified into the subthemes of Collaborating, Communication, Community, Involvement, Interaction, Participation, and Presence.

3.6. Data analysis

Frequency tables were generated for each of the variables so that outliers could be examined and narrative data could be collapsed into categories. Once cleaned and collapsed into a reasonable number of categories, descriptive statistics were used to describe each of the coded elements. We first present the frequencies of publications related to online learning in the 12 journals. The total number of articles for each journal (collectively, the population) was hand-counted from journal websites, excluding editorials and book reviews. The publication trend of online learning research was also depicted from 2009 to 2018. Then, the descriptive information of the 12 themes, including the subthemes of Learner Characteristics and Engagement were provided. Finally, research themes by research settings and methodology were elaborated.

4.1. Publication trends on online learning

Publication patterns of the 619 articles reviewed from the 12 journals are presented in Table 4 . International Review of Research in Open and Distributed Learning had the highest number of publications in this review. Overall, about 8% of the articles appearing in these twelve journals consisted of online learning publications; however, several journals had concentrations of online learning articles totaling more than 20%.

Empirical online learning research articles by journal, 2009–2018.

Note . Journal's Total Article count excludes reviews and editorials.

The publication trend of online learning research is depicted in Fig. 4 . When disaggregated by year, the total frequency of publications shows an increasing trend. Online learning articles increased throughout the decade and hit a relative maximum in 2014. The greatest number of online learning articles ( n  = 86) occurred most recently, in 2018.

Online learning publication trends by year.

4.2. Online learning research themes that appeared in the selected articles

The publications were categorized into the twelve research themes identified in Fig. 1 . The frequency counts and percentages of the research themes are provided in Table 5 below. A majority of the research is categorized into the Learner domain. The fewest number of articles appears in the Organization domain.

Research themes in the online learning publications from 2009 to 2018.

The specific themes of Engagement ( n  = 179, 28.92%) and Learner Characteristics ( n  = 134, 21.65%) were most often examined in publications. These two themes were further coded to identify sub-themes, which are described in the next two sections. Publications focusing on Instructor Characteristics ( n  = 21, 3.39%) were least common in the dataset.

4.2.1. Research on engagement

The largest number of studies was on engagement in online learning, which in the online learning literature is referred to and examined through different terms. Hence, we explore this category in more detail. In this review, we categorized the articles into seven different sub-themes as examined through different lenses including presence, interaction, community, participation, collaboration, involvement, and communication. We use the term “involvement” as one of the terms since researchers sometimes broadly used the term engagement to describe their work without further description. Table 6 below provides the description, frequency, and percentages of the various studies related to engagement.

Research sub-themes on engagement.

In the sections below, we provide several examples of the different engagement sub-themes that were studied within the larger engagement theme.

Presence. This sub-theme was the most researched in engagement. With the development of the community of inquiry framework most of the studies in this subtheme examined social presence ( Akcaoglu & Lee, 2016 ; Phirangee & Malec, 2017 ; Wei et al., 2012 ), teaching presence ( Orcutt & Dringus, 2017 ; Preisman, 2014 ; Wisneski et al., 2015 ) and cognitive presence ( Archibald, 2010 ; Olesova et al., 2016 ).

Interaction . This was the second most studied theme under engagement. Researchers examined increasing interpersonal interactions ( Cung et al., 2018 ), learner-learner interactions ( Phirangee, 2016 ; Shackelford & Maxwell, 2012 ; Tawfik et al., 2018 ), peer-peer interaction ( Comer et al., 2014 ), learner-instructor interaction ( Kuo et al., 2014 ), learner-content interaction ( Zimmerman, 2012 ), interaction through peer mentoring ( Ruane & Koku, 2014 ), interaction and community building ( Thormann & Fidalgo, 2014 ), and interaction in discussions ( Ruane & Lee, 2016 ; Tibi, 2018 ).

Community. Researchers examined building community in online courses ( Berry, 2017 ), supporting a sense of community ( Jiang, 2017 ), building an online learning community of practice ( Cho, 2016 ), building an academic community ( Glazer & Wanstreet, 2011 ; Nye, 2015 ; Overbaugh & Nickel, 2011 ), and examining connectedness and rapport in an online community ( Bolliger & Inan, 2012 ; Murphy & Rodríguez-Manzanares, 2012 ; Slagter van Tryon & Bishop, 2012 ).

Participation. Researchers examined engagement through participation in a number of studies. Some of the topics include, participation patterns in online discussion ( Marbouti & Wise, 2016 ; Wise et al., 2012 ), participation in MOOCs ( Ahn et al., 2013 ; Saadatmand & Kumpulainen, 2014 ), features that influence students’ online participation ( Rye & Støkken, 2012 ) and active participation.

Collaboration. Researchers examined engagement through collaborative learning. Specific studies focused on cross-cultural collaboration ( Kumi-Yeboah, 2018 ; Yang et al., 2014 ), how virtual teams collaborate ( Verstegen et al., 2018 ), types of collaboration teams ( Wicks et al., 2015 ), tools for collaboration ( Boling et al., 2014 ), and support for collaboration ( Kopp et al., 2012 ).

Involvement. Researchers examined engaging learners through involvement in various learning activities ( Cundell & Sheepy, 2018 ), student engagement through various measures ( Dixson, 2015 ), how instructors included engagement to involve students in learning ( O'Shea et al., 2015 ), different strategies to engage the learner ( Amador & Mederer, 2013 ), and designed emotionally engaging online environments ( Koseoglu & Doering, 2011 ).

Communication. Researchers examined communication in online learning in studies using social network analysis ( Ergün & Usluel, 2016 ), using informal communication tools such as Facebook for class discussion ( Kent, 2013 ), and using various modes of communication ( Cunningham et al., 2010 ; Rowe, 2016 ). Studies have also focused on both asynchronous and synchronous aspects of communication ( Swaggerty & Broemmel, 2017 ; Yamagata-Lynch, 2014 ).

4.2.2. Research on learner characteristics

The second largest theme was learner characteristics. In this review, we explore this further to identify several aspects of learner characteristics. In this review, we categorized the learner characteristics into self-regulation characteristics, motivational characteristics, academic characteristics, affective characteristics, cognitive characteristics, and demographic characteristics. Table 7 provides the number of studies and percentages examining the various learner characteristics.

Research sub-themes on learner characteristics.

Online learning has elements that are different from the traditional face-to-face classroom and so the characteristics of the online learners are also different. Yukselturk and Top (2013) categorized online learner profile into ten aspects: gender, age, work status, self-efficacy, online readiness, self-regulation, participation in discussion list, participation in chat sessions, satisfaction, and achievement. Their categorization shows that there are differences in online learner characteristics in these aspects when compared to learners in other settings. Some of the other aspects such as participation and achievement as discussed by Yukselturk and Top (2013) are discussed in different research themes in this study. The sections below provide examples of the learner characteristics sub-themes that were studied.

Self-regulation. Several researchers have examined self-regulation in online learning. They found that successful online learners are academically motivated ( Artino & Stephens, 2009 ), have academic self-efficacy ( Cho & Shen, 2013 ), have grit and intention to succeed ( Wang & Baker, 2018 ), have time management and elaboration strategies ( Broadbent, 2017 ), set goals and revisit course content ( Kizilcec et al., 2017 ), and persist ( Glazer & Murphy, 2015 ). Researchers found a positive relationship between learner's self-regulation and interaction ( Delen et al., 2014 ) and self-regulation and communication and collaboration ( Barnard et al., 2009 ).

Motivation. Researchers focused on motivation of online learners including different motivation levels of online learners ( Li & Tsai, 2017 ), what motivated online learners ( Chaiprasurt & Esichaikul, 2013 ), differences in motivation of online learners ( Hartnett et al., 2011 ), and motivation when compared to face to face learners ( Paechter & Maier, 2010 ). Harnett et al. (2011) found that online learner motivation was complex, multifaceted, and sensitive to situational conditions.

Academic. Several researchers have focused on academic aspects for online learner characteristics. Readiness for online learning has been examined as an academic factor by several researchers ( Buzdar et al., 2016 ; Dray et al., 2011 ; Wladis & Samuels, 2016 ; Yu, 2018 ) specifically focusing on creating and validating measures to examine online learner readiness including examining students emotional intelligence as a measure of student readiness for online learning. Researchers have also examined other academic factors such as academic standing ( Bradford & Wyatt, 2010 ), course level factors ( Wladis et al., 2014 ) and academic skills in online courses ( Shea & Bidjerano, 2014 ).

Affective. Anderson and Bourke (2013) describe affective characteristics through which learners express feelings or emotions. Several research studies focused on the affective characteristics of online learners. Learner satisfaction for online learning has been examined by several researchers ( Cole et al., 2014 ; Dziuban et al., 2015 ; Kuo et al., 2013 ; Lee, 2014a ) along with examining student emotions towards online assessment ( Kim et al., 2014 ).

Cognitive. Researchers have also examined cognitive aspects of learner characteristics including meta-cognitive skills, cognitive variables, higher-order thinking, cognitive density, and critical thinking ( Chen & Wu, 2012 ; Lee, 2014b ). Lee (2014b) examined the relationship between cognitive presence density and higher-order thinking skills. Chen and Wu (2012) examined the relationship between cognitive and motivational variables in an online system for secondary physical education.

Demographic. Researchers have examined various demographic factors in online learning. Several researchers have examined gender differences in online learning ( Bayeck et al., 2018 ; Lowes et al., 2016 ; Yukselturk & Bulut, 2009 ), ethnicity, age ( Ke & Kwak, 2013 ), and minority status ( Yeboah & Smith, 2016 ) of online learners.

4.2.3. Less frequently studied research themes

While engagement and learner characteristics were studied the most, other themes were less often studied in the literature and are presented here, according to size, with general descriptions of the types of research examined for each.

Evaluation and Quality Assurance. There were 38 studies (6.14%) published in the theme of evaluation and quality assurance. Some of the studies in this theme focused on course quality standards, using quality matters to evaluate quality, using the CIPP model for evaluation, online learning system evaluation, and course and program evaluations.

Course Technologies. There were 35 studies (5.65%) published in the course technologies theme. Some of the studies examined specific technologies such as Edmodo, YouTube, Web 2.0 tools, wikis, Twitter, WebCT, Screencasts, and Web conferencing systems in the online learning context.

Course Facilitation. There were 34 studies (5.49%) published in the course facilitation theme. Some of the studies in this theme examined facilitation strategies and methods, experiences of online facilitators, and online teaching methods.

Institutional Support. There were 33 studies (5.33%) published in the institutional support theme which included support for both the instructor and learner. Some of the studies on instructor support focused on training new online instructors, mentoring programs for faculty, professional development resources for faculty, online adjunct faculty training, and institutional support for online instructors. Studies on learner support focused on learning resources for online students, cognitive and social support for online learners, and help systems for online learner support.

Learner Outcome. There were 32 studies (5.17%) published in the learner outcome theme. Some of the studies that were examined in this theme focused on online learner enrollment, completion, learner dropout, retention, and learner success.

Course Assessment. There were 30 studies (4.85%) published in the course assessment theme. Some of the studies in the course assessment theme examined online exams, peer assessment and peer feedback, proctoring in online exams, and alternative assessments such as eportfolio.

Access, Culture, Equity, Inclusion, and Ethics. There were 29 studies (4.68%) published in the access, culture, equity, inclusion, and ethics theme. Some of the studies in this theme examined online learning across cultures, multi-cultural effectiveness, multi-access, and cultural diversity in online learning.

Leadership, Policy, and Management. There were 27 studies (4.36%) published in the leadership, policy, and management theme. Some of the studies on leadership, policy, and management focused on online learning leaders, stakeholders, strategies for online learning leadership, resource requirements, university policies for online course policies, governance, course ownership, and faculty incentives for online teaching.

Course Design and Development. There were 27 studies (4.36%) published in the course design and development theme. Some of the studies examined in this theme focused on design elements, design issues, design process, design competencies, design considerations, and instructional design in online courses.

Instructor Characteristics. There were 21 studies (3.39%) published in the instructor characteristics theme. Some of the studies in this theme were on motivation and experiences of online instructors, ability to perform online teaching duties, roles of online instructors, and adjunct versus full-time online instructors.

4.3. Research settings and methodology used in the studies

The research methods used in the studies were classified into quantitative, qualitative, and mixed methods ( Harwell, 2012 , pp. 147–163). The research setting was categorized into higher education, continuing education, K-12, and corporate/military. As shown in Table A in the appendix, the vast majority of the publications used higher education as the research setting ( n  = 509, 67.6%). Table B in the appendix shows that approximately half of the studies adopted the quantitative method ( n  = 324, 43.03%), followed by the qualitative method ( n  = 200, 26.56%). Mixed methods account for the smallest portion ( n  = 95, 12.62%).

Table A shows that the patterns of the four research settings were approximately consistent across the 12 themes except for the theme of Leaner Outcome and Institutional Support. Continuing education had a higher relative frequency in Learner Outcome (0.28) and K-12 had a higher relative frequency in Institutional Support (0.33) compared to the frequencies they had in the total themes (0.09 and 0.08 respectively). Table B in the appendix shows that the distribution of the three methods were not consistent across the 12 themes. While quantitative studies and qualitative studies were roughly evenly distributed in Engagement, they had a large discrepancy in Learner Characteristics. There were 100 quantitative studies; however, only 18 qualitative studies published in the theme of Learner Characteristics.

In summary, around 8% of the articles published in the 12 journals focus on online learning. Online learning publications showed a tendency of increase on the whole in the past decade, albeit fluctuated, with the greatest number occurring in 2018. Among the 12 research themes related to online learning, the themes of Engagement and Learner Characteristics were studied the most and the theme of Instructor Characteristics was studied the least. Most studies were conducted in the higher education setting and approximately half of the studies used the quantitative method. Looking at the 12 themes by setting and method, we found that the patterns of the themes by setting or by method were not consistent across the 12 themes.

The quality of our findings was ensured by scientific and thorough searches and coding consistency. The selection of the 12 journals provides evidence of the representativeness and quality of primary studies. In the coding process, any difficulties and questions were resolved by consultations with the research team at bi-weekly meetings, which ensures the intra-rater and interrater reliability of coding. All these approaches guarantee the transparency and replicability of the process and the quality of our results.

5. Discussion

This review enabled us to identify the online learning research themes examined from 2009 to 2018. In the section below, we review the most studied research themes, engagement and learner characteristics along with implications, limitations, and directions for future research.

5.1. Most studied research themes

Three out of the four systematic reviews informing the design of the present study found that online learner characteristics and online engagement were examined in a high number of studies. In this review, about half of the studies reviewed (50.57%) focused on online learner characteristics or online engagement. This shows the continued importance of these two themes. In the Tallent-Runnels et al.’s (2006) study, the learner characteristics theme was identified as least studied for which they state that researchers are beginning to investigate learner characteristics in the early days of online learning.

One of the differences found in this review is that course design and development was examined in the least number of studies in this review compared to two prior systematic reviews ( Berge & Mrozowski, 2001 ; Zawacki-Richter et al., 2009 ). Zawacki-Richter et al. did not use a keyword search but reviewed all the articles in five different distance education journals. Berge and Mrozowski (2001) included a research theme called design issues to include all aspects of instructional systems design in distance education journals. In our study, in addition to course design and development, we also had focused themes on learner outcomes, course facilitation, course assessment and course evaluation. These are all instructional design focused topics and since we had multiple themes focusing on instructional design topics, the course design and development category might have resulted in fewer studies. There is still a need for more studies to focus on online course design and development.

5.2. Least frequently studied research themes

Three out of the four systematic reviews discussed in the opening of this study found management and organization factors to be least studied. In this review, Leadership, Policy, and Management was studied among 4.36% of the studies and Access, Culture, Equity, Inclusion, and Ethics was studied among 4.68% of the studies in the organizational level. The theme on Equity and accessibility was also found to be the least studied theme in the Berge and Mrozowski (2001) study. In addition, instructor characteristics was the least examined research theme among the twelve themes studied in this review. Only 3.39% of the studies were on instructor characteristics. While there were some studies examining instructor motivation and experiences, instructor ability to teach online, online instructor roles, and adjunct versus full-time online instructors, there is still a need to examine topics focused on instructors and online teaching. This theme was not included in the prior reviews as the focus was more on the learner and the course but not on the instructor. While it is helpful to see research evolving on instructor focused topics, there is still a need for more research on the online instructor.

5.3. Comparing research themes from current study to previous studies

The research themes from this review were compared with research themes from previous systematic reviews, which targeted prior decades. Table 8 shows the comparison.

Comparison of most and least studied online learning research themes from current to previous reviews.

L = Learner, C=Course O=Organization.

5.4. Need for more studies on organizational level themes of online learning

In this review there is a greater concentration of studies focused on Learner domain topics, and reduced attention to broader more encompassing research themes that fall into the Course and Organization domains. There is a need for organizational level topics such as Access, Culture, Equity, Inclusion and Ethics, and Leadership, Policy and Management to be researched on within the context of online learning. Examination of access, culture, equity, inclusion and ethics is very important to support diverse online learners, particularly with the rapid expansion of online learning across all educational levels. This was also least studied based on Berge and Mrozowski (2001) systematic review.

The topics on leadership, policy and management were least studied both in this review and also in the Tallent-Runnels et al. (2006) and Zawacki-Richter et al. (2009) study. Tallent-Runnels categorized institutional and administrative aspects into institutional policies, institutional support, and enrollment effects. While we included support as a separate category, in this study leadership, policy and management were combined. There is still a need for research on leadership of those who manage online learning, policies for online education, and managing online programs. In the Zawacki-Richter et al. (2009) study, only a few studies examined management and organization focused topics. They also found management and organization to be strongly correlated with costs and benefits. In our study, costs and benefits were collectively included as an aspect of management and organization and not as a theme by itself. These studies will provide research-based evidence for online education administrators.

6. Limitations

As with any systematic review, there are limitations to the scope of the review. The search is limited to twelve journals in the field that typically include research on online learning. These manuscripts were identified by searching the Education Research Complete database which focuses on education students, professionals, and policymakers. Other discipline-specific journals as well as dissertations and proceedings were not included due to the volume of articles. Also, the search was performed using five search terms “online learning" OR "online teaching" OR "online program" OR "online course" OR “online education” in title and keyword. If authors did not include these terms, their respective work may have been excluded from this review even if it focused on online learning. While these terms are commonly used in North America, it may not be commonly used in other parts of the world. Additional studies may exist outside this scope.

The search strategy also affected how we presented results and introduced limitations regarding generalization. We identified that only 8% of the articles published in these journals were related to online learning; however, given the use of search terms to identify articles within select journals it was not feasible to identify the total number of research-based articles in the population. Furthermore, our review focused on the topics and general methods of research and did not systematically consider the quality of the published research. Lastly, some journals may have preferences for publishing studies on a particular topic or that use a particular method (e.g., quantitative methods), which introduces possible selection and publication biases which may skew the interpretation of results due to over/under representation. Future studies are recommended to include more journals to minimize the selection bias and obtain a more representative sample.

Certain limitations can be attributed to the coding process. Overall, the coding process for this review worked well for most articles, as each tended to have an individual or dominant focus as described in the abstracts, though several did mention other categories which likely were simultaneously considered to a lesser degree. However, in some cases, a dominant theme was not as apparent and an effort to create mutually exclusive groups for clearer interpretation the coders were occasionally forced to choose between two categories. To facilitate this coding, the full-texts were used to identify a study focus through a consensus seeking discussion among all authors. Likewise, some studies focused on topics that we have associated with a particular domain, but the design of the study may have promoted an aggregated examination or integrated factors from multiple domains (e.g., engagement). Due to our reliance on author descriptions, the impact of construct validity is likely a concern that requires additional exploration. Our final grouping of codes may not have aligned with the original author's description in the abstract. Additionally, coding of broader constructs which disproportionately occur in the Learner domain, such as learner outcomes, learner characteristics, and engagement, likely introduced bias towards these codes when considering studies that involved multiple domains. Additional refinement to explore the intersection of domains within studies is needed.

7. Implications and future research

One of the strengths of this review is the research categories we have identified. We hope these categories will support future researchers and identify areas and levels of need for future research. Overall, there is some agreement on research themes on online learning research among previous reviews and this one, at the same time there are some contradicting findings. We hope the most-researched themes and least-researched themes provide authors a direction on the importance of research and areas of need to focus on.

The leading themes found in this review is online engagement research. However, presentation of this research was inconsistent, and often lacked specificity. This is not unique to online environments, but the nuances of defining engagement in an online environment are unique and therefore need further investigation and clarification. This review points to seven distinct classifications of online engagement. Further research on engagement should indicate which type of engagement is sought. This level of specificity is necessary to establish instruments for measuring engagement and ultimately testing frameworks for classifying engagement and promoting it in online environments. Also, it might be of importance to examine the relationship between these seven sub-themes of engagement.

Additionally, this review highlights growing attention to learner characteristics, which constitutes a shift in focus away from instructional characteristics and course design. Although this is consistent with the focus on engagement, the role of the instructor, and course design with respect to these outcomes remains important. Results of the learner characteristics and engagement research paired with course design will have important ramifications for the use of teaching and learning professionals who support instruction. Additionally, the review also points to a concentration of research in the area of higher education. With an immediate and growing emphasis on online learning in K-12 and corporate settings, there is a critical need for further investigation in these settings.

Lastly, because the present review did not focus on the overall effect of interventions, opportunities exist for dedicated meta-analyses. Particular attention to research on engagement and learner characteristics as well as how these vary by study design and outcomes would be logical additions to the research literature.

8. Conclusion

This systematic review builds upon three previous reviews which tackled the topic of online learning between 1990 and 2010 by extending the timeframe to consider the most recent set of published research. Covering the most recent decade, our review of 619 articles from 12 leading online learning journal points to a more concentrated focus on the learner domain including engagement and learner characteristics, with more limited attention to topics pertaining to the classroom or organizational level. The review highlights an opportunity for the field to clarify terminology concerning online learning research, particularly in the areas of learner outcomes where there is a tendency to classify research more generally (e.g., engagement). Using this sample of published literature, we provide a possible taxonomy for categorizing this research using subcategories. The field could benefit from a broader conversation about how these categories can shape a comprehensive framework for online learning research. Such efforts will enable the field to effectively prioritize research aims over time and synthesize effects.

Credit author statement

Florence Martin: Conceptualization; Writing - original draft, Writing - review & editing Preparation, Supervision, Project administration. Ting Sun: Methodology, Formal analysis, Writing - original draft, Writing - review & editing. Carl Westine: Methodology, Formal analysis, Writing - original draft, Writing - review & editing, Supervision

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

1 Includes articles that are cited in this manuscript and also included in the systematic review. The entire list of 619 articles used in the systematic review can be obtained by emailing the authors.*

Appendix B Supplementary data to this article can be found online at https://doi.org/10.1016/j.compedu.2020.104009 .

Appendix A. 

Research Themes by the Settings in the Online Learning Publications

Research Themes by the Methodology in the Online Learning Publications

Appendix B. Supplementary data

The following are the Supplementary data to this article:

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Application of the UTAUT model to understand learning behavior using Online Video Conference media for RPL students

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