EHUK13048 - R1 - IEEE Version1

Virtual Learning Environment Name Institutional Affiliation Student No. Date Abstract- Over the past few years, there has been a meteoric rise in the popularity of online education platforms. Around the world, universities are utilizing e-learning systems to supplement traditional classroom instruction. We have embraced e-learning technologies in our higher education institutions. However, despite the widespread implementation of these systems, significant obstacles remain in the way of their practical application. This research aimed to examine the factors influencing eLearning system usability in UK higher education institutions. The research aimed to do two things: assess the current state of online education and identify any usability problems that may be slowing down its spread through academic institutions. In this study, researchers looked at one public university's experience using the online learning platform Moodle. I. INTRODUCTION There has been a shift in perspective toward e-learning platforms as legitimate educational tools. E-learning systems allow the incorporation of technology into classroom instruction [6]. Computers are now helpful in many fields, including business and academia. Many people are turning to online education because of its many advantages. When appropriately used, e-learning systems can cut down on expenses for both teachers and students while increasing efficiency in the classroom. They can also help students become more uniform in their knowledge acquisition, and lecturers become more effective in their work. E-value learning lies in its ability to facilitate "learning anywhere, at any time" by furnishing a variety of tools and venues for engagement, content mastery, and independent study. An insufficiently equipped e-learning system can cause learner frustration, anxiety, and confusion, which can lessen their interest in the material being presented. Most e-learning systems fail to gain widespread use because of their poor usability. Learners' opinions on their eLearning experience are affected by the system's usability; if the system is poorly designed, students will struggle to master its content. Conceptual Framework Hypotheses H 0 : The statistics show an e-learning system's learnability and usability are imperfect. H 01 : The user experience of an e-learning framework is not statistically different from its friendliness to users.

II. LITERATURE REVIEW Electronic learning environments (VLEs) are computer-based instructional strategies. Distributing educational content to students is vital to any online education platform. This software facilitates online learning by allowing teachers and students to share materials, hold discussions, keep a roster, monitor attendance, and manage other aspects of their interactions within a virtual classroom. An example of e-learning made possible through technology is using a Learning Management System (LMS). It supplements classroom instruction E- learning relies heavily on learning management systems (LMSs), which are software platforms that combine traditional classroom training, online education, and HR administration [1]. A Learning Management System (LMS) aims to make online learning opportunities available in a flexible, independent fashion. Students assigned a course through the LMS can access it from any internet-connected device with a web browser. The LMS will then monitor the student's actions and provide up-to-date news stories for each curriculum and each student [2]. A few examples of popular LMSs are Available in multiple languages, WebCT, Blackboard, and desire2learn. Users of the Moodle online learning platform were the focus of this research. a) The need to evaluate the e-learning system The overarching goal of Evaluating Learning is to ascertain whether or not a performance and business goals were attained due to the learning that took place. Summative Evaluation is another term for this. E-learning system evaluations serve four primary functions: they confirm the value of training as an organizational tool, justify the costs of training, facilitate the development of more effective training strategies, and inform the selection of training methods [3]. The purpose of the eLearning testing process in this research is to inform improvements to both the training and the eLearning system designs. b) Usability of E-learning System Various definitions of usability have emerged, each focusing on one or more of its subcomponents, such as learnability, memorability, errors, or efficiency [4]. Though learnability is directly related to efficiency, the focus on efficiency tends to be on users with expert knowledge. Errors deal with the more severe consequences of mistakes that aren't covered by efficiency, while memorability focuses on casual users. According to another definition, E-learning system usability comprises five quantifiable human factors: performance speed, learning time, retention over time, error rate, and the frequency with which users make mistakes. c) User-Based Evaluation of usability of e-learning systems Presently, the complete form of Evaluation is user-based Evaluation, which evaluates usability by selecting samples of actual users [5]. The research used a suitable method called a "system inquiry," in which users were asked to share their thoughts and

es cy 35% 65% 100 % Totals Frequen cy 19 22 41 % 46% 54% 100 % IV. FINDINGS AND DISCUSSION Eight respondents (or 60.67%) held a Master's degree, making up the largest share of the faculty; another 11 (or 13.33%) held a degree, and the remaining 13 (or 0.67%) held a Doctorate. The majority of the respondents worked as lecturers (7 people, or 46.67%), accompanied by senior lecturers (3 people, or 20%) and assistant lecturers (3 people, or 3.33%). The group helped during the entire process. TABLE II: RESPONSE TO E-LEARNING SYSTEMS E-learning Systems Yes No Wikipedia 40% 60% Moodle 100% 0% WebCT 5% 95% Blackboard 5% 95% Participants' Prior E-Learning Experience: All respondents indicated that they had used an online learning system, which means that every respondent has some familiarity with online education. According to the data, the most popular features are submitting assignments (97.5%), taking a quiz (100%), and participating in a forum (95.5%). Factors hindering the implementation of e-learning systems While respondents generally agreed that a lack of computer access is a barrier to the widespread adoption of e-learning, a vast majority (92%). There was near-unanimous agreement among respondents that a lack of computers was a barrier to e-learning, with only 2% disagreeing. None of the respondents (100%) agreed with the statements that the reasons for not using an e-learning platform were due to a lack of interest, a lack of knowledge about its accessibility, legal concerns, plagiarism, or the course not being a good fit for it. TABLE III: E-LEARNING SYSTEMS IMPLEMENTATION HINDERANCE Factors Yes No Lack of computers 98% 2% Course quality concerns 8% 92% Other factors 0 100 % Hypotheses testing a) Hypothesis 1: No discernible correlation exists between an e-learning system's learnability and usability. b) Null Hypothesis: The usability of an e- learning system is not influenced by factors related to learnability. c) Alternative Hypothesis: An e-learning platform's effectiveness is impacted by various learnability factors.

The linear regression results show that "Learning to Use e-Learning" is the most crucial factor in terms of learnability. With a p-value of 0.044 for "system is easy," p=0.701 for "exploring new modules by trial and error," and a whopping 0.009 for "Easy to be skillful," "Easy to Upload / Download" is statistically significant. FIG I: REGRESSION MODEL RESULTS Thus, we accept the alternative hypothesis and reject the null that there is no significant dissimilarity between both the current educational factors and the performance of the e-learning system. It implies that now the learnability factors substantially impact the efficiency of an e-learning system. The efficiency with which a system can be used is diminished if it is challenging to master. Learnability was identified as a problem area in a survey of usability issues in e-learning systems. Because of this, usability improves with ease of learning. TABLE IV: REGRESSION MODEL RESULTS Mode ls Sig. normal 0.001 Computers 0.007 Ones accessed on LAN and WAN 0.006 Both "Interaction with LMS clear" and "Accessing Menus and Commands easily" were shown to be statistically significant at the p=0.007 and p=0.002 levels, respectively. According to the Pearson correlation, the intuitiveness of an online course has a direct effect on its effectiveness. As there is a clear separation between the needs of the consumer and the practicality of e-learning systems, this finding contradicts the hypothesis. As can be seen in the table below, this means that the effectiveness of e-learning systems depends on how user-friendly they are. TABLE V: REGRESSION MODEL RESULTS V.CONCLUSION AND RECOMMNEDATIONS Conclusion The goal of the research was to find out how well an online education system works in practice at one university in the UK [8]. Usability research has looked at a wide range of topics, including learnability, acceptance testing, technological capabilities, user experience policy, culture, and gender. Many participants in the study agreed that the system's ability to be learned was a major factor in the e-learning platform's overall usability. Ease of use, module discovery via trial and error, system expertise, and the capacity for users to upload and download content were all measured. A large majority of respondents agreed that both e-learning as well as e-learning systems were challenging to master. The results are consistent with the

Hamam, H. and Alotaibi, F. (2021). Prioritising Organisational Factors Impacting Cloud ERP Adoption and the Critical Issues Related to Security, Usability, and Vendors: A Systematic Literature Review. Sensors , 21(24), p.8391. doi:10.3390/s21248391. [4] Hirschey, J., Bane, S., Mansour, M., Sperber, J., Agboola, S., Kvedar, J. and Jethwani, K. (2019). Evaluating the Usability and Usefulness of a Mobile App for Atrial Fibrillation Using Qualitative Methods: Exploratory Pilot Study. JMIR Human Factors , 5(1), p.e13. doi:10.2196/humanfactors.8004. [5] Torelli, G., Rossi Alvarez, A., Nagavarapu, S., Pruttianan, A., del Rio, R. and Nguyen, B. (2018). Lextant Usability Impact Score: A New, Objective Approach to Indexing Usability Issues. Proceedings of the Human Factors and Ergonomics Society Annual Meeting , 62(1), pp.1992–1996. doi:10.1177/1541931218621451. [6] Wallace, A. (2014). Social Learning Platforms and the Flipped Classroom. International Journal of Information and Education Technology , 4(4), pp.293–296. doi:10.7763/ijiet.2014.v4.416. [7] Moreno, V., Cavazotte, F. and Alves, I. (2016). Explaining university students’ effective use of e-learning platforms. British Journal of Educational Technology , 48(4), pp.995–1009. doi:10.1111/bjet.12469. [8] Lomas, L. (2006). The locus of power in UK universities. Active Learning in Higher Education , 7(3), pp.243–255. doi:10.1177/1469787406071214.