Introduction
The world is currently undergoing many changes caused by coronavirus pandemic that originated in China in December of 2019. The Covid-19 virus spreads through close contact with an infected person or contaminated surfaces. As a result, strict restrictions were adopted in China and other parts of the world, which include restricting movements, delays in opening schools, and stringent isolation measures (Cao et al., 2020). These strategies significantly affected the learning because experts suggested using it would accelerate the rates of infection amongst school children and students.
Many learning institutions around the world adopted online learning methods to facilitate continuity of education. The growth of technology, the Internet, and communication tools significantly improved the education sector as they led to the emergence of e-learning. According to Findik-Coşkunçay et al. (2018, pp.1), e-learning is technology-based education where the learning materials are sent via remotely to the learners using computer networks. Therefore, the increased use of computers and smartphones amongst the students and instructors supported the seamless integration of e-learning into institutions during the Covid-19 pandemic. Therefore, students have continued to learn using a wide array of online applications and computing resources despite the strict measures adopted in various countries in response to coronavirus.
Learning Management Systems
Students learning using e-learning interacts with different media in different classes uploaded by lecturers. A school’s online learning system might be supporting more than 50 courses offered to hundreds of students who use them at different times of the day. Therefore, the media and other learning materials have to be managed well for e-learning to perform as intended. In that case, learning management systems (LMS) are used. Ohliati and Abbas (2019), defined LMS as an application used in managing online learning systems, enabling interaction between learners and instructors, as well as distributing learning materials. Therefore, LMS is essential in facilitating teaching and learning activities by storing and organizing learning resources.
LMS significantly influences the learning process. Students interact with learning materials via LMS, which means that it has to be easy to use and engaging to enable learners to navigate classes efficiently. As noted by Ohliati and Abbas (2019), the quality of information, services, and systems provided by learning institutions affect the students’ satisfaction level towards LMS. Additionally, perceived usefulness, availability of communication channels, ease of use, and flexibility influence the acceptance and actual usage of the LMS. As a result, schools should invest in high-quality systems, information, course designs, and adaptable courses in LMS to boost users’ satisfaction, which significantly affects their usage and acceptance levels.
Importance of E-Learning
Currently, many learning institutions, students, and parents are experiencing the main importance of e-learning with everything going on around the world. On the onset of coronavirus, schools were ordered by the governments to lockdown and find alternatives to class-based learning. Therefore, e-learning was adopted because it offers the flexibility of location and time (Uprichard, 2020). In traditional-based education, classes are offered in a fixed site and time, which is often between 9 am and 5 pm. Conversely, learners can access e-learning platforms at any time of the day from different locations. As a result, schools can still finish the syllabus despite the stay-at-home orders that were introduced after the coronavirus. The learners apply their time management skills to meet the training needs created by lecturers. In such a case, it means that learners can do something during the day and study at night or when they are free, as long as they read and finish up the assigned tasks.
E-learning classes are more accessible than face-to-face courses. People with better connection and decent devices can successfully apply to study e-learning classes. For instance, Uprichard (2020) indicated that over 93% of households are connected to the Internet, which means that they can participate in learning, especially now, when social distancing rules were imposed. Additionally, e-learning is more accessible to many people around the world than face-to-face classes. Therefore, learners who went back to their home countries after the pandemic can still access learning and finish their courses. Learners also study at their own pace, and they can use the available resources to revise concepts they did not grasp in the first attempt.
E-learning integrates multiple resources, tools, and approaches that facilitate the learning process. Regmi and Jones (2020) argue that e-learning uses different structured frameworks that align with course requirements and helps in boosting learners’ experience. Instructors can also integrate interactive media and learning simulation tools that enable students to acquire better technical skills. The researchers further posit that e-learning is essential in studies that need an in-depth understanding of context and practice, which made it one of the acceptable approaches among healthcare professionals (Regmi & Jones, 2020). Learners can access learning materials before and after the class that gives them a more elaborate idea about the concepts being taught. Additionally, access to video materials is essential in improving the acquisition of skills and addressing new concepts.
Barriers of E-Learning
Several factors limit the success of e-learning. Naveed et al. (2017) and Uprichard (2020) identified technical difficulties as the main barrier in the implementation of e-learning. The success of e-learning relies on the availability of better connection, qualified technical support, and computer systems. Therefore, the lack of any of these resources significantly inhibits the adoption of e-learning. For instance, the use of outdated or obsolete software applications such as Windows XP denies students from accessing learning materials. Additionally, such systems are easy targets for hackers, which was witnessed in 2017 during the WannaCry ransom attack that targeted outdated technology (Uprichard, 2020). Therefore, many students fail to access learning materials due to technical failure. Furthermore, some courses are not accessible with mobile devices that restrict the majority of students who do not have computer systems from learning. Instructors also face challenges when trying to design learning activities that match learners’ needs. Failing to incorporate interactive and engaging content would result in poor satisfaction and low performance in class.
Learners’ poor motivation and expectations also influence success in online courses. The desire for the students to succeed in class determines the efforts they put into achieving their goals. Motivational factors are either internal or external. The study by Regmi and Jones (2020) indicated the internal factors as poor perception, poor engagement, high levels of anxiety, lack of self-discipline, low self-esteem, as well as poor communication between the students and teachers. These factors reduce students’ level of attention or interest in online classes. External factors such as poor designs, lack of clarity or purpose of the course, poor education management policy, financial independence, limited knowledge in technology, and lack of learning space also restrict the use of e-learning. For the time that students are at home, some are expected to perform house chores or run other errands that might disrupt their learning process. Additionally, lack of space or support within their homes might lower their will to dedicate time to learning.
Social interactions are an essential part of the learning process. In face-to-face learning, students might engage in discussions that help in improving information retention and subsequent success in class. Learners also get a one-on-one meeting with instructors where they get more help should have a challenge in class. Conversely, these meaningful social interactions are not present in e-learning (Ng & Baharom, 2018). This inhibits communication, especially when the students feel the need to clarify something during class. As a result, a lack of social presence negatively influences students’ satisfaction with online tasks, which leads to poor learning performance and experiences.
Factors Influencing Success of E-Learning
The overall design of online courses influences students’ satisfaction in class, thus affecting their success in class. Other researchers have argued that perceived usefulness, ease of use, service quality, Internet, subject norm, and self-efficacy as factors influencing the use of LMS. These factors are explained in this section.
Perceived Usefulness
This aspect represents the beliefs people hold that using a particular system would impact their performance. Parameters measuring perceived usefulness include how the systems affect the performance of people that include the ability to accomplish tasks at a short time, increased productivity, overall usability, and improved study (Ohliati & Abbas, 2019). Students and institutions are likely to adopt LMSs that add value to the learners.
Perceived Ease of Use
This factor represents the confidence people have that the system can be free of effort. This means that if the learners think that the system looks easy to use, then they consider it more useful (Findik-CoĹźkunçay et al., 2018). Perceived ease of use is measured using various elements such as the ability of a system to meet users’ expectations, increased performance, improved user interaction, easy to use, and flexibility.
Service Quality
The quality of services when delivering learning affects the adoption of LMS. Several service quality indicators are used to measure user satisfaction levels. They include the ability to analyze and monitor performance easily, quickly identify risks and problems, reliability, usability, functionality, and other factors that improve users’ satisfaction (Ohliati & Abbas, 2019). Responding to clients’ needs on time would help in improving service quality, thus leading to increased contentment, and people are more likely to use such systems.
Internet Quality
Students need to have computers or mobile devices with better connection all the time to access online courses. Internet quality assesses the speed at which the students access class roll books, report attendance, watch video lectures, or ask questions (Joo et al., 2016). Lack of the Internet disrupts the learning process as they cannot use LMS.
Subject Norm
This aspect explores the external pressure from the social environment, encouraging people to use LMS. Students might be influenced by their peers to use a particular LMS. In some cases, students are required by the instructors or institutions to use a specific system, which is not the subjective norm.
Self-efficacy
This factor describes the confidence individuals have on their abilities to perform certain activities. Self-efficacy influences the attitudes people have towards an object and behavioral intentions (Findik-Coşkunçay et al., 2018). Therefore, students are likely to adopt a system that they can easily navigate or use.
References
Cao, W., Fang, Z., Hou, G., Han, M., Xu, X., Dong, J., & Zheng, J. (2020). The psychological impact of the COVID-19 epidemic on college students in China. Psychiatry Research, 112934. Web.
Findik-CoĹźkunçay, D., AlkiĹź, N., & Ă–zkan-Yildirim, S. (2018). A structural model for students’ adoption of learning management systems: An empirical investigation in the higher education context. Journal of Educational Technology & Society, 21(2), 13-27. Web.
Joo, Y. J., Kim, N., & Kim, N. H. (2016). Factors predicting online university students’ use of a mobile learning management system (m-LMS). Educational Technology Research and Development, 64(4), 611-630. Web.
Naveed, Q. N., Qureshi, M. R. N., Alsayed, A. O., Muhammad, A., Sanober, S., & Shah, A. (2017). Prioritizing barriers of E-Learning for effective teaching-learning using fuzzy analytic hierarchy process (FAHP). 2017 4th IEEE International Conference on Engineering Technologies and Applied Sciences (ICETAS) (pp. 1-8). Web.
Ng, H., & Baharom, S. S. (2018). An analysis on adult learners’ satisfaction in online education programmes. International Journal of Interactive Mobile Technologies (iJIM), 12(7), 70-85. Web.
Ohliati, J., & Abbas, B. S. (2019). Measuring students’ satisfaction in using learning management system. International Journal of Emerging Technologies in Learning (iJET), 14(04), 180-189. Web.
Regmi, K., & Jones, L. (2020). A systematic review of the factors–enablers and barriers–affecting e-learning in health sciences education. BMC Medical Education, 20, 1-18. Web.
Uprichard, K. (2020). E-learning in a new era: Enablers and barriers to its implementation in nursing. British Journal of Community Nursing, 25(6), 272-275. Web.