THE IMPORTANCE OF USING CLOUD COMPUTING SERVICES AND TECHNOLOGIES IN TRACKING STUDENTS' BEHAVIOR WHILE USING ASYNCHRONOUS E-LEARNING PLATFORMS
DOI:
https://doi.org/10.70672/1yy84k29Keywords:
Asynchronous e-learning, cloud computing, Principal Component Analysis (PCA), Analysis of Variance (ANOVA)Abstract
The problems that different aspects of teaching and learning provide to the education industry are continuous. Teachers and students together always struggle to increase their knowledge due to ongoing technological breakthroughs in education. In order to remain on track and maintain students’ engagement during the COVID-19 epidemic, several educational institutions were compelled to quickly implement such technologies. Students that participate in asynchronous e-learning are by themselves throughout the process of learning. The main effects of this loneliness are dissatisfaction and lack of motivation, which increase the dropout rate. Monitoring a student's behavior while they are learning enables timely intervention. However, the amount of information offered to teachers in the online courses could be excessive. This study has shown the impact of cloud computing and its function in tracking students' behavior throughout the asynchronous e-learning process. We compile student data and perform a questionnaire survey on the relevance of the cloud in asynchronous e-learning. To simplify the components and improve the outcomes, Principal Component Analysis (PCA) was applied. The findings are analyzed using descriptive statistical analysis and Analysis of Variance (ANOVA). The research demonstrates how technology use and improved internet infrastructure have a significant positive influence on learning, enabling studying at anytime and anyplace.
References
Rashid, A. and Chaturvedi, A., 2019. Cloud computing characteristics and services: a brief review. International Journal of Computer Sciences and Engineering, 7(2), pp.421-426.
Abdel-Basset, M., Mohamed, M. and Chang, V., 2018. NMCDA: A framework for evaluating cloud computing services. Future Generation Computer Systems, 86, pp.12-29.
Agarwal, A., Hasan, R., Naidu, V.R., Saqib, M., Srinivas, S. and Jesrani, K., 2021, January. Educational association mining on the use of media platforms for e-learning. In 2021 2nd International Conference on Computation, Automation and Knowledge Management (ICCAKM) (pp. 309-314). IEEE.
Hou, L., Liu, Q., Nebhen, J., Uddin, M. and Chaudhary, A., 2022. Implementation of Cloud Computing Protocol in E-Learning for Future Wireless Systems. Wireless Communications and Mobile Computing, 2022.
Kebede, A. and Bhattacharya, S., 2022. Student Engagement Awareness Dashboard for Asynchronous E-learning Environment. In ICT Systems and Sustainability (pp. 737-749). Springer, Singapore.
Alajmi, Q.A., Kamaludin, A., Arshah, R.A. and Al-Sharafi, M.A., 2018. The effectiveness of cloud-based e-learning towards quality of academic services: an Omanis’ expert view. International Journal of Advanced Computer Science and Applications, 9(4).
Adeshola, I. and Agoyi, M., 2022. Examining factors influencing e-learning engagement among university students during covid-19 pandemic: A mediating role of “learning persistence”. Interactive Learning Environments, pp.1-28.
Shahroury, F., 2022. E-Learning During COVID-19 Epidemic: Experience of a University from Jordan. Academy of Strategic Management Journal, 21(4S), pp.1-6.
Azlan, C.A., Wong, J.H.D., Tan, L.K., Huri, M.S.N.A., Ung, N.M., Pallath, V., Tan, C.P.L., Yeong, C.H. and Ng, K.H., 2020. Teaching and learning of postgraduate medical physics using Internet-based e-learning during the COVID-19 pandemic–A case study from Malaysia. Physica Medica, 80, pp.10-16.
Alfaro, L., Rivera, C., Luna-Urquizo, J., Castañeda, E., Zuniga-Cueva, J. and RiveraChavez, M., 2021, March. New Trends in e-Technologies and e-Learning. In 2021 IEEE World Conference on Engineering Education (EDUNINE) (pp. 1-6). IEEE.
Kausar, S., Huahu, X., Ullah, A., Wenhao, Z. and Shabir, M.Y., 2020. Fog-assisted secure data exchange for examination and testing in E-learning system. Mobile Networks and Applications, pp.1-17.
Nadrljanski, M., Vukić, Đ. and Nadrljanski, D., 2018, May. Multi-agent systems in elearning. In 2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) (pp. 0990-0995). IEEE.
Li, F., Lu, H., Hou, M., Cui, K. and Darbandi, M., 2021. Customer satisfaction with bank services: The role of cloud services, security, e-learning and service quality. Technology in Society, 64, p.101487.
Man, M., Azhan, M.H.N. and Hamzah, W.M.A.F.W., 2019. Conceptual Model for Profiling Student Behavior Experience in e-Learning. International Journal of Emerging Technologies in Learning, 14(21).
Najm, Y.A., Alsamaraee, S. and Jalal, A.A., 2022. Cloud computing security for e-learning during COVID-19 pandemic. Indonesian Journal of Electrical Engineering and Computer Science, 27(3), pp.1610-1618.
Xiong, L. and Li, M., 2021. Behavioral modeling based on cloud computing and target user recommendation for English cloud classroom. Microprocessors and Microsystems, 80, p.103587.
Kawamura, R., Shirai, S., Takemura, N., Alizadeh, M., Cukurova, M., Takemura, H. and Nagahara, H., 2021. Detecting Drowsy Learners at the Wheel of e-Learning Platforms With Multimodal Learning Analytics. IEEE Access, 9, pp.115165-115174.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Malaysian Journal of Industrial Technology
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Journal of Engineering Technology (JET) is an open-access journal that follows the Creative Commons Attribution-Non-commercial 4.0 International License (CC BY-NC 4.0)
