The Success of Learning Management System in Higher Educational Institutions in India

Saumya Kapoor Sharma
Assistant Professor, HR and OB, Department of Human Resource Management and Soft Skills, IBS Hyderabad (Under IFHE - A Deemed to be University u/s 3 of the UGC Act, 1956), Hyderabad, Telangana, India. E-mail: saumya.sharma@ibsindia.org, saumyasharma4910@gmail.com

N Akbar Jan
Assistant Professor, OB and HRM, Department of Human Resource Management and Soft Skills, IBS Hyderabad (Under IFHE - A Deemed to be University u/s 3 of the UGC Act, 1956), Hyderabad, Telangana, India; and is the corresponding author. E-mail: akbarjan.1975@gmail.com; akbarjan75@ibsindia.org

A K Subramani
Associate Professor and Head, Department of Management Studies, St. Peter's College of Engineering and Technology, Avadi, Chennai 600054, Tamil Nadu, India. E-mail: aksubramani@gmail.com/ draksubramani@gmail.com

The study's key objective is to examine the success of the Learning Management System (LMS) used in various Higher Educational Institutions (HEIs) in Chennai city. This study used a descriptive research design, which describes the users' perspective towards the success of LMS used in various HEIs in Chennai city. Data was collected through a stratified sampling technique to measure the satisfaction level attained by institutions adopting LMS. The SEM model shows that all the LMS factors have a significant positive effect on the usage of LMS. The findings of the study will help policymakers of HEI focus more on content quality while developing LMS platforms.

Introduction

The economic growth of a country depends on the knowledge possessed by its citizens. Therefore, education is considered fundamental for building a sustainable society. Knowledge platforms across the globe are changing with varied methods incorporated for enrichment. Even our government has drafted National Education Policy, 2021, which plans for everyone's equitable and lifelong learning opportunities by 2030. The future of our country depends on the knowledge landscape provided primarily to the younger generation. Therefore, learning is an inevitable part of human life. The emergence of an unforeseen contingency like Covid-19 has taught us to innovate and inculcate new methodologies for teaching and learning. The basic premise of learning has shifted its attention from "what to" to "how to" learn in the current scenario. Learning may be of two types, namely, formal learning and informal learning. Formal learning refers to learning in a training-based organization, workplace, mobile devices, classrooms, online and through e-learning portals. Formal learning occurs through the formal education system. Formal learning occurs in a structured and organized environment like training/education institutions or jobs. It is explicitly designed as education regarding time, objectives and resources. It is intentional learning from the learner's perspective, leading to degrees and certifications. Formal learning is a structured model that presents a rigid curriculum corresponding to laws and norms. It is somewhat presentational education.

Informal learning refers to learning based on practical and lifelong learning. Informal learning is crucial, especially for individuals who must stay abreast with rapid technological and economic changes. While informal learning symbolizes the key to entering the world of employment, it also represents the steps in building a successful career. Informal learning is the education beyond limitations and outside of a traditional formal learning environment like university, school or college. It is an education seen as learning that goes on in our daily lives or learning projects to teach ourselves.

This learning is based on daily life experiences like peer groups, family, media or any other influence in the learner's surroundings. This learning platform encompasses a range of activities; it could be researching the international gallery collection, learning cookery skills in a community center, taking part in a project voluntarily or otherwise. In other words, informal learning involves learning things without realizing the learning process. This may include picking up information from TV, the Internet, films, direct interaction with individuals, or other informal ways.

The information technology facilitates managing formal learning through Learning Management System (LMS). LMS is an operating system that supports the education system over various tasks like maintaining data, keeping records, monitoring and tracking various educational programs, and facilitating the distribution of educational material. LMS serves as an effective medium to facilitate synchronous and asynchronous learning through an online learning platform by identifying gaps related to training and learning by applying various analytical data to the system when needed. Online learning gained popularity post identification of e-learning, which further went a long journey by supporting not only educational but corporate needs and started becoming tailor-made according to need and demand. Its features increased its scope beyond online learning, from classroom to online teaching, making it a critical component in our education policy. LMS became our savior to sail through the classroom to virtual teaching difficulties with the ongoing pandemic. Previous research displayed that LMS characteristics affect users' learning through the system; therefore, it is very significant to estimate the efficacy of LMS systems in the organization.

As mentioned earlier, LMS plays a vital role in educational organizations and the corporate world. Educational institutions such as schools, colleges, universities, etc., adopt LMS in their organization to motivate, monitor, regulate the learning of students and teaching faculty in their institutions in the specific topic, subject or course. In contrast, in the corporate world, LMS is used in training or updating the knowledge and skills of employees in a specific domain to enhance their productivity and performance in the job and prepare them for future positions. Moreover, the active engagement of learners with the LMS improves their learning in the organization. So the success of LMS depends upon the extent to which it can actively engage the users in the formal learning system, which results in optimal learning in the particular topic/subject/course.

Tamil Nadu is the "Mecca of higher education", which comprises various categories of Higher Educational Institutions (HEI) such as government colleges, government-aided colleges, self-finance colleges, private universities, deemed-to-be universities, state universities, and central universities. These HEIs offer several programs in different disciplines such as arts and science, engineering, law, medical, etc. The HEIs adopt online LMS (i.e., NPTEL, MOOC, Moodle), customized LMS from the vendors (Enhance, Course-play, SABA LMS, Learn-Trak, etc.) and/or develop their own LMS according to their requirements. The HEI invest colossal money, effort, and time in enhancing their students' learning experience through LMS adoption in their organization. However, the success (or effectiveness) of LMS should be ascertained to ensure the students' practical learning through LMS in HEIs. Therefore, the key objective of the research is to evaluate the success of the LMS used by various HEIs in Chennai city.

Literature Review
Rashida (2018) discussed LMS in Higher Education Institutions. E-learning plays a significant role in this knowledge world. LMS is a device used as a platform to execute e-learning procedures. It offers effective and active methods to store, handle, exchange its academic resources, knowledge and enhance their traditional means of teaching (Rosenberg, 2001; and Zhang et al., 2004). The present era is considered a techno-savvy era. The New Education Policy supports and motivates to adopt novel concepts in imparting education, making it more accessible, exciting and reachable throughout the education system and comparing our present learning with the Gurukul system where scholars and guides used to stay together for face-to-face learning, compared to now, where learning platforms have modelled our lives. The deployment of various digital tools has shaped a prosperous e-learning environment, especially in India (Bhattacharya and Sharma, 2007).

Students perceive that the performance of the lecturers, characteristics of LMS and support of the university plays an essential role in determining e-learning application. In inference, universities should use LMS by educating learners' viewpoints and authorizing that the lecturers use the LMS in their teaching and learning events. They are equipped at using it, must point out the significance of LMS on learning atmosphere and deliver good service for operating LMS application in the university learning atmosphere. Hence, the question lies in selecting proper LMS supported by user-friendly, easy-to-use material, records, and synchronous platforms that guide developing self-learning models (Chao and Chen, 2009; and Karagoz et al., 2017).

Based on LMS, Kennedy and Elijah (2017) introduced a model to evaluate learning outcomes from e-learning modules that could further support e-learning models with enhanced quality framework. The review process measured the six dimensions and various factors labeled as the P3 Course Evaluation Model, the PDPP evaluation model, the e-learning Quality Framework, the TMLE framework and the e-Learning maturity model. Authorization of the developed model was further supported by the feedback received and verified over Structural Equation Modeling (SEM) from 200 respondents of JKUAT University, Kenya.

In their study, Aini and Nur (2016) focused on the system's effectiveness and efficiencies. The method used is a questionnaire where the questions were sent through email randomly to the students at higher education institutions in Malaysia. There were about 200 questionnaires, and only 150 respondents have answered the questionnaire. The data was analyzed using frequency methods to identify the value and percentage with mean, mode, median and standard deviation. Additional analysis using linear regression was also carried out. The research was to identify the relationship of the variables. The outcome of the research indicates that the effectiveness and efficiency of the LMS significantly influence students' satisfaction. For students' satisfaction, the institution must identify the capabilities of LMS that will be used and the expenses the institution must invest in the system. The effectiveness and efficiencies of the system can determine and help solve potential problems.

Kasim (2016) highlighted various budding LMS platforms, like Tutor, Moodle, Blackboard and Success factors which have been working as a catalyst in enriching the teaching-learning process. After undergoing a comparative study based on certain specific qualities of selected LMS providers on the sample institutions, particular features were encapsulated like user-friendliness, easy to handle, learn, flexible approach and readiness to use. This paper also provides some conclusions on the selection of the platform to be used. The study commenced by the researchers acted as a torchbearer for HEIs to decide and choose the best suitable LMS platform.

National Education Policy, 2021 and Higher Educational Institutes in India
The government-driven National Education Policy, 2021 is also keenly looking forward to supporting innovations through technology designed in the curriculum of HEIs to support skill, upskill and reskill. HEI will serve as a platform to build new instructional materials prepared primarily for professional education. Keeping an eye on the latest learning modules based on machine learning, digitalization, artificial learning, a supportive platform like SWAYAM, DIKSHA is used for its transmission. Various tools for two-way audio and video have been designed, particularly during a pandemic for online teaching and learning.

The technological revolution has made many changes in our lives. The constitution of human life now rests on Information and Communication Technology (ICT) and has deeply filled education system's roots worldwide (Bhattacharya and Sharma, 2007). Every society has building blocks in cultural, socio-economic and political upliftment, which acts as a torchbearer for designing education pathways (Bordoloi, 2018). Previous literature suggested that health and education are essential supportive pillars (Romer, 1990; Mankiw et al., 1992; and The World Bank, 2017). Fast Recovery, post Covid-19, would lay a strong educational infrastructure instead of closures, which can alleviate the human capital deficit crisis in the long run. Hence, learning continuity is an essential construct for further development (World Bank, 2021). Many rely on HEI support for the functional skills of the younger generation, which makes it necessary to develop effective knowledge sharing platforms. Education fosters equitable growth parameters and helps in developing human capital in the domain of science, medicine, arts and humanities, which can further invent and innovate new learning methods for generating a self-sustainable society and economy (Bordoloi, 2018)

The Transition from Face-to-Face Learning to Virtual Learning
Since 1950, we have focused on the democratization of the education system, but the distant and online modes of learning became vital during this pandemic. Digital innovations acted like a vaccine for the smooth conducting of classes in the absence of face-to-face interactions, and digital boards made it interesting (Joshi et al., 2020).

The current global pandemic scenario has caused vast devastation, putting a pause to our lives, which led to the initiation of generating a new online teaching methodology for bringing the world closer (Tharoor and Saran, 2020). A recent study conducted by UNESCO, 2020 estimated that Covid-19 has brought a halt to the learners' society constituting 1.77 billion across 177 countries with the temporary closure of educational institutions. According to OECD (2020) report, along with the health crisis, India has been struggling with a learning crisis too.

Covid-19 has taught us that face-to-face classroom learning pedagogy is traditional while online teaching is novel. Even the educational institutions have come out in support of Ministry of Human Resource and Development (MHRD) guidelines and instructed teachers to organize online video conferencing, webinars, seminars, moot court competitions, even online examinations etc. Knowledge-sharing platforms like Google Classroom, Handouts, and video conferencing used over Zoom, Skype, Webex, and Meet Links have transformed our education system (Joshi et al., 2020). Considering the present situation, adopting digital strategies further would assist in having a centralized curriculum throughout the country (Degnarain, 2020). Across the globe, various academicians and educational institutions have fostered and adopted learning technologies, which were not readily acceptable earlier. Still, previous studies show online teaching tools in the education sector (Mutsvunguma, 2019). Usage of the e-learning platform is readily acceptable globally with its widespread use, multi teaching aids and quick delivery pattern, remote and limitless learning, self-driven learning, quick examination, results and feedback (Mwalumbwe and Mtebe, 2017; and Ratheeswari, 2018). Various LMS tools like MOODLE also gained popularity across South African universities before the pandemic (Bagarukayo and Kalema, 2015; Letseka et al., 2018; Van de Heyde and Siebrits, 2019; and Mhlanga and Molo, 2020).

Madalina and Cristina (2016), in their paper, critically analyzed LMS in higher education. LMS platform has added color to the canvas of learning for imparting teaching-learning in universities and institutions. It has occupied a pivotal role in HEIs. The paper has highlighted the suitable LMS tools available for universities. The paper is divided into four segments. The first section describes the various modern LMS platforms available compared to traditional teaching methods and how it creates value by differential teaching methods. The second part of the paper describes the comparative analysis of LMS based on their features, capabilities and required technical support. And the last segment elaborates the results, post discussion of literature and research methodology used.

Nur and Afiza (2016) examined the basic constructs related to LMS, which accelerates scholastic performance. Based on quantitative data collected from a sample of 20 respondents from a Malaysian university, a research instrument was used that contained 12-item. The results show a positive correlation between a well-structured LMS platform that motivates scholars to utilize and increase its academic results. Furthermore, an inference from the research advises teachers to teach creative and innovative methods, effectively using LMS, which helps develop learners' interests.

Fletcher and Susan (2013) proposed a conceptual e-learning framework based on Andragogy theory, Transformative learning theory, and Media synchronicity theory. The conceptual e-learning framework supports self-directed learning. E-learning based on this framework has the potential to outperform not only current LMS such as Blackboard but also traditional FtF learning for adult education and with different and better outcomes. Early testing of the concept showed increased learners' online activity, innovation, and creativity.

Ahmad et al. (2010) pointed out certain factors that guide students while learning Calculus at their university over a centralized mathematical platform named Portal of Learning Calculus (POLCA). Researchers have explored identified five factors mainly, the students' technology competencies, the design of POLCA, the role of lecturers, access to POLCA and attitude towards the usage of POLCA among students. The results displayed that the uppermost mean denotes students' technology-based learning capacity (M = 3.27) followed by the design of POLCA (M = 2.61), POLCA usage perspective (M = 2.51), the role of lecturers (M = 2.44) and access to the portal (M = 2.36). Research findings also showed a strong relationship between the design of POLCA, the role of the lecturer and assessee to POLCA with the attitude towards using POLCA.

Research Model Development
The present study is based on the conceptual model framed by Ozka e-learning assessment model, which has six dimensions (i.e., system quality, service quality, content quality, learner perspective, instructor attitude, and supportive issues) to measure the utility of LMS. The rationale behind developing a research model is to popularize the adoption of LMS in various HEIs in Chennai city (Figure 1).

System Quality
The term 'system quality' refers to the performance of a system that incorporates salient features like usability, availability and response time. Therefore, system quality is the prudent feature of an information system. For example, ease of use, system flexibility, system reliability, ease of learning, intuitiveness, sophistication, and response time. Ease of use is the degree to which the users believe that they need to invest less effort to use the system by using LMS. In addition, the quality of Information System needs to be flexible enough for the user to use the system (Radha et al., 2019).

Service Quality
Service quality is the difference between customers' assumptions to perceptions of service accomplishment. Therefore, the service quality of LMS refers to the ability of the learning platform to meet users' expectations compared to the services offered. Information Quality Information quality has been linked with nine characteristics: accuracy, precision, currency, output timeliness, reliability, completeness, conciseness, format, and relevance. Past studies on the usage of technology to the satisfaction derived from it advocate that information quality has a remarkable influence on users' satisfaction (Saikumari et al., 2018).

Learner Perspective
The learner perspective is another critical dimension of the success of LMS. In other words, the learner perspective refers to how the learner looks at LMS and what he/she gets from LMS. It includes learner attitudes toward LMS, learner's computer anxiety, self-efficiency, enjoyable experience, interaction with other students and teachers.

Instructor Attitude
In LMS, the role and attitude of the instructor plays a vital role because they are going to guide the learner to learn through LMS and create awareness about various features of LMS. Instructor attitude includes different characteristics of the instructor like responsiveness, enjoyment, availability, self-efficiency, promptness, usefulness, fairness, communication ability, and encouraging interaction between students, Supportive Issues Supportive issues are the issues that may affect the success of LMS. The issues may be related to the environment, changes in technology or concepts (i.e., trends), and ethical issues. The issues about LMS should be prevented or sorted out then and there to enhance user satisfaction, which will increase LMS success rate in HEIs.

Earlier literature supported that the success of LMS is influenced by system quality, service quality, content quality, learners' perspective, and instructor attitude (Bagarukayo and Kalema, 2015; Kasim, 2016; Letseka et al., 2018; and Rashida, 2018).

The following hypothesis was formulated based on the above-presented conceptual model in Figure 1.

H1: System quality has a significant positive effect on the success of LMS.

H2: Service quality has a significant positive effect on the success of LMS.

H3: Content quality has a significant positive effect on the success of LMS.

H4: Learner perspective has a significant positive effect on the success of LMS.

H5: Instructor attitude has a significant positive effect on the success of LMS.

H6: Supportive issues are having a significant adverse effect on the success of LMS.

The above-mentioned hypothetical relationships are examined through the SEM approach.

Methodology
According to Ozkan and Koseler (2009), HELAM has been developed to evaluate e-learning through six dimensions with two important issues, namely, (1) social issues: a perspective (the perspective of) student (7 factors), the attitude of the teaching staff (9 factors) and (2) Technical Issues: the quality of the System (11 factors), quality of information (4 factors), quality of service (11 factors) as well as a supporting Factor (4 factors). This study used a descriptive research design, which describes the users' perspective towards the success of the LMS used in various HEIs in Chennai city. The sample population refers to the users' (i.e., students and teaching faculty) of LMS in various HEIs located in Chennai city. The authors surveyed the users from various universities located in Chennai city. There are around twelve deemed-to-be universities in Chennai, and their names are listed in Table 1. Out of these twelve universities, only five have implemented LMS in their institutions.

The authors adopted a stratified random sampling technique to know the users' satisfaction towards the LMS adopted by those institutions. From each institution, 50 samples were collected from students of various departments, and the final sample size of the study is 250. The Google Form, which carries questions related to chosen dimensions of users' satisfaction towards LMS, was circulated through email and WhatsApp. The Google Form had a total of 30 questions, out of which six items are demographic related questions (i.e., name, university name, gender, education, program, year of the study) and rest 24 items are related to six dimensions of LMS evaluation, namely, system quality (4 items), service quality (4 items), content quality (4 items), learner perspective (4 items), instructor attitude (4 items) and supportive issues (4 items). The SPSS 22.0 and AMOS 22.0 was used to analyze the data collected through Google Forms.

Demographic Profile
Table 2 presents the user's demographic profile related to the research context using frequency analysis. Out of the 250 sampled users, a majority (63.20%) are males, and the remaining (36.80%) are females. A majority (51.20%) of them are pursuing undergraduate level courses. In contrast, around one-third (33.60%) of them are pursuing post-graduation, and the rest (15.20%) are pursuing M.Phil/PhD from the selected HEIs in Chennai city. In addition, 39.20% of them are pursuing engineering programs, slightly less than one-third (30.00%) of them are pursuing management courses, whereas 15.20% of them are pursuing arts and science courses, and another 15.60% of them are pursuing other courses (law, visual communication, architecture, etc.). Slightly more than one-third (35.60%) of them are pursuing third year, while 31.20% are in the second year. However, 10.40% of them are pursuing their first year, and 22.80% are in the final year of their programs.

Results and Discussion
The authors have analyzed the conceptual model of the research using the SEM approach using IBM AMOS 20.0 software. Figure 2 presents the SEM of the success of LMS. From the SEM model, it is identified that all the factors of LMS such as system quality, service quality, content quality, learner perspective, and instructor attitude have a significant positive effect on the success of LMS. However, the factor 'supportive issues' is having a significant negative impact on the success of LMS.

The increase in number of problems under supportive issues would decrease the success of LMS, so the HEI should promptly prevent or resolve the problems. All these factors have significant loading (more than 0.5) on its latent variable (i.e., success of LMS). It is also found that all the hypothetical relationships mentioned in the conceptual model are significant at a 1% level.

It is also identified that content quality is having the highest positive effect (0.84) on the success of LMS, so it is declared that content quality is a key factor that enhances the success of LMS, which is followed by system quality (0.79), service quality (0.68), learner perspective (0.63), instructor attitude (0.61), and supportive issues (-0.55).

The model fitness indices of the above-illustrated model are Chi-square (2.564), p-value (0.341), GFI (0.932), AGFI (0.927), RMR (0.021), and RMSEA (0.28). All these values fall within the range of defined range. Consequently, the research study model fits the primary data.

Conclusion
Based on the outcome of the study, it is established that the quality of LMS enhances the quality of learning in HEIs. Therefore, the LMS developers and policymakers of HEIs should focus on content quality to enhance the success of LMS. The LMS in higher educational institutions supports students' learning, assessment, and evaluation. Therefore, every dimension of the LMS is essential to ensure its success to deliver maximum benefits to the higher educational institution. Strengthening of digital infrastructure will act as a support function to smoothen LMS further. Moving in pace with other countries, we need to adopt a radical approach towards classroom-based teaching-learning to virtual learning. Though we say that the traditional teaching mode since ancient times has been face-to-face, living in this digitalized era, adopting a virtual learning platform as LMS is the new normal.

References

1. Ahmad Fauzi M A, Rohani A T, Wan M W J et al. (2010), "Factors Influencing Students' Use a Learning Management System Portal: Perspective from Higher Education Students", International Journal of Education and Information Technologies, Vol. 4, No. 2, pp. 100-108.
2. Aini Zuriyati Abdul Kadir and Nur Sukinah Aziz (2016), "Learning Management System of Higher Education Institution", Indian Journal of Science and Technology, Vol. 9, No. 9, pp. 1-5.
3. Bagarukayo E and Kalema B M (2015), "Evaluation of eLearning Usage in South African Universities: A Critical Review", International Journal of Education and Development Using Information and Communication Technology, Vol. 11, pp. 168-183.
4. Bhattacharya I and Sharma K (2007), "India in the Knowledge Economy: An Electronic Paradigm", Asian Journal of Distance Education, Vol. 5, No. 1, pp. 40-53.
5. Bordoloi R (2018), "Transforming and Empowering Higher Education Through Open and Distance Learning in India", Asian Association of Open Universities Journal, Vol. 13, No. 1, pp. 24-36.
6. Chao R J and Chen Y H (2009), "Evaluation of the Criteria and Effectiveness of Distance e-Learning with Consistent Fuzzy Preference Relations", Expert Systems with Applications, Vol. 36, No. 7, pp.10657-10662.
7. COL (2020), Guidelines on Distance Education During COVID-19, COL, Burnaby.
8. Degnarian N (2020), "Five Ways Blockchain Can Unblock, The Coronavirus Medical Supply Chain", Forbes. Available at: https//:www.forbes.com/nishandegnarian/2020/03/22/5-ways-blockchain-can-unblock-thecoronavirus-medical-supply-chain/#25d72dd11380
9. Fletcher H Glancy and Susan K Isenberg (2013), "A Conceptual Learner-Centered e-Learning Framework", Journal of Higher Education Theory and Practice, Vol. 13, No. 3, pp. 22-35.
10. Joshi A, Vinay M and Bhaskar P (2020),"Impact of Coronavirus Pandemic on the Indian Education Sector: Perspectives of Teachers on Online Teaching and Assessments", Interactive Technology and Smart Education, Vol. 18, No. 2, pp. 205-226.
11. Karagoz E, Oral LO, Kaya O H and Tecim V (2017), "LMS Selection Process for Effective Distance Education System in Organizations", EBEEC Conference Proceedings, The Economies of Balkan and Eastern Europe Countries in the Changed World (2016), Vol. 2017, pp. 347-356.
12. Kasim F Khalid (2016), "Choosing the Right Learning Management System (LMS) for the Higher Education Institution Context: A Systematic Review", International Journal of Emerging Technologies in Learning, Vol. 11, No. 6, pp. 55-61.
13. Kennedy and Elijah (2017), "A Model for Evaluating E-Learning Systems Quality in Higher Education in Developing Countries", International Journal of Education and Development Using Information and Communication Technology, Vol. 13, No. 2, pp. 185-204.
14. Letseka M, Letseka M M and Pitsoe V J (2018), "The Challenges of E-learning in South Africa", Trends in E-learning. Mahmut Sinecen, IntechOpen, DOI: 10.5772/intechopen.74843. Available from: https://www.intechopen.com/chapters/59935
15. Madalina Croitoru and Cristina-Nicoleta Dinu (2016), "A Critical Analysis of Learning Management Systems in Higher Education", Economy Informatics, Vol. 16, No. 1, pp. 5-18.
16. Mankiw N G, David R and David W (1992), "A Contribution to the Empirics of Economic Growth", Quarterly Journal of Economics, Vol. 107, No. 2, pp. 407-438.
17. Mhlanga D and Moloi T (2020), "Covid-19 and the Digital Transformation of Education: What Are We Learning on 4IR in South Africa?", Education Sciences, Vol. 10, No. 7, p. 180.
18. Mutsvunguma G (2019), "Institutional Repositories as Platforms for Open Access in South African Universities: The Case of University of KwaZulu-Natal", (Doctoral dissertation).
19. Mwalumbwe I and Mtebe JS (2017),"Using Learning Analytics to Predict Students Performance in Moodle Learning Management System: A Case of Mbeya University of Science and Technology", The Electronic Journal of Information Systems in Developing Countries, Vol. 79, No. 1, pp. 1-13.
20. Nur Sakinah Binti Dulkaman and Afiza Mohamad Ali (2016), "Factors Influencing the Success of Learning Management System (LMS) on Students' Academic Performance", International Young Scholars Journal of Language, Vol. 1, No. 1, pp. 36-45.
21. OECD (2020), "The Impact of Covid-19 on Student Equity and Inclusion: Supporting Vulnerable Students During School Closures and School Re-Openings" available at https//: www.oecd.org/coronavirus/policy-responses/the-impact-of-covid-19-on-student-equity-and-inclusion-supporting-vulnerable-students-during-school-closures-and-school-re-operning-d593b5cb8/
22. Ozkan S and Koseler R (2009), "Multi-Dimensional Evaluation of E-Learning Systems in the Higher Education Context: An Empirical Investigation of a Computer Literacy Course", 39th ASEE/IEEE Frontiers in Education Conference, IEEE Xplore, pp. 1-6.
23. Radha S, Michael Mariadhas J, Subramani A K and Akbar Jan N (2019), "Role of E-Learning and Digital Media Resources in Employability of Management Students", The Online Journal of Distance Education and e-Learning, Vol. 7, No. 2, pp. 116-123.
24. Rashida MF (2018), "Learning Management System (LMS) in Higher Education Institutions", Journal of Information Systems & Information Technology, Vol. 3, No. 2, pp.15-23.
25. Ratheeswari K (2018), "Information Communication Technology in Education", Journal of Applied and Advanced Research, Vol. 3, No. 1, pp. 45-47.
26. Romer P M (1990), "Endogenous Technological Change", Journal of Political Economy, Vol. 96, October, pp. S71-S102.
27. Rosenberg M J (2001), E-Learning: Strategies for Delivering Knowledge in the Digital Age, McGraw-Hill.
28. Saikumari V, Subramani A K and Akbar Jan N (2018), "Training and Organizational Performance: The Mediating Role of E-Learning in Information Technology Industry - An Empirical Study", The Online Journal of Distance Education and e-Learning, Vol. 6, No. 6, pp. 77-83.
29. Tharoor S and Saran S (2020), The New World Disorder and the Indian Imperative, Aleph Book Company.
30. Van de Heyde V and Siebrits A (2019), "The Ecosystem of E-Learning Model for Higher Education", South African Journal of Science, Vol. 115, Nos. 5&6, available at https://sajs.co.za/article/view/5808
31. World Bank (2017), available at https://thedocs.worldbank.org/en/doc/908481507403754670-0330212017/original/ AnnualReport2017WBG. Pdf
32. World Bank (2021), available at https://www.worldbank.org/en/news/immersive-story/2021/01/22/urgent-effective-action-required-to-quell-the-impact-of-covid-19-on-education-worldwide
33. Zhang D, Zhao JL, Zhou L and Nunamaker JF (2004), "Can e-Learning Replace Classroom Learning? Communications of the ACM", Vol. 47, No. 5, pp. 75-79.