The investigation of the Effect of using E-learning in Database Course by using Moodle
DOI:
https://doi.org/10.65405/dqz5w072Keywords:
E-learning; Database; Teaching; MoodleAbstract
Despite the proliferation of E-learning in education world-wide, this methodology is not implemented on Libyan context. therefore, there is a need to investigate the effect of deploying eLearning methodology in higher education. The aim purpose of this study is to develop E-learning database by using Moodle open source (learning management system). The secondary purpose is to compare the effects of two different modes of teaching (E-learning, and traditional classroom) on student achievement used in database course at (High institute of medical technology Abosalim ).
A study was developed to examine student’s achievement in database course by comparing results of final test for both modes of delivery. The sample was (16 students at classroom mode and 15 students at E-learning mode).The final results showed that the mean difference between the test of the two groups by using the T.test was that the E-learning group obtained a higher achievement of statistical significance than the traditional education group at the significance level (P <0.05). These results indicate that database E-learning course is well-designed and can be very effective for students' achievements.
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1- Pucel, D., & Stertz, T. Effectiveness of and student satisfaction with web-based compared to traditional in-service teacher education courses. Journal of Industrial Teacher Education, 2005. 42(1), 7-23. Retrieved from Ebscohost database.
2- Lim, Jon and Karol, Johnathan : Student Achievement, Satisfaction and Instructional Delivery Modes, TRE- Systems,Miami, USA, 2002 .
3- Dougiamas, Martin and Taylor, Peter: Interpretive nalysis an internet-based course constructed using a new courseware tool called moodle, Curtin University of Technology, Perth,Australia,2001.
4- Yu.H and Jianbo. F. Design and Implementation of the Framework for Adaptive E-learning System. In Wang, Fu, Joseph Fong, Liming Zhang, and Victor Lee (Editors), Hybrid Learning and Education, Lecture Notes in Computer Science, volume 5685,2009, pages 140–149.
5- Fallon, Carol, Jeanne M. Dams, and Sharon Brown. E-learning Standards: A Guide to Purchasing, Developing, and Deploying Standards-Conformant E-Learning:First Edition. St Lucie Press,2002.
6- Varlamis ,.Koohang.A, and Ioannis .A. The Present and Future of Standardsfor E-learning Technologies. Interdisciplinary Journal of Knowledge and Learning Objects, 2006,p 2, 59–76
7- Kopecký, K. E-learning nejen pro pedagogy. Olomouc: Hanex,2006.
8- CBT. Czech Airlines,2009. Retrieved December 7, 2014 from
http://www.csa.cz/cs/posadky/pos_vycvik_posadek/pos_cbt.htm
9- Meerts, J. Course management systems (CMS),2003. Retrieved December 8, 2014 from http://net.educause.edu/ir/library/pdf/DEC0302.pdf
10- Meerts, J. Course management systems (CMS),2003. Retrieved December 8, 2014 from http://net.educause.edu/ir/library/pdf/DEC0302.pdf
11- Dalla, L. O. B., Karal, Ö., Degirmenci, A., EL-Sseid, M. A. M., Essgaer, M., & Alsharif, A. (2025). Edge Intelligence for Real-Time Image Recognition: A Lightweight Neural Scheduler Via Using Execution-Time Signatures on Heterogeneous Edge Devices. Scientific Journal for Publishing in Health Research and Technology, 74-85.
12- Mnyanyi, C. B. F., & Mbwette, T. S. A. Open and distance learning in professional development in third world countries. Paper presented at Maastricht‘s 23rd International Conference on Distance Education, 2009.
13- Hoven, K. A study on the potential of information and communication technologies in university education in Tanzania. A case study of the University of Dar es Salaam. Master of art thesis. The Netherlands: Nijmegen University,2000.
14- Joyce, B., & Showers, B. Student achievement through staff development: Fundamentals of school renewal (2nd ed.),1995. White Plains, NY: Longman.
15- Meyer-Peyton, L. Elements of a successful distributed learning program. In L. K. Lau (Ed.), Distance learning technologies: Issues, trends and opportunities. Hersey & London: IDEA Group Publishing,2002.
16- Paulson, J.W, Succi, G. and Eberlein, A. An Empirical Study of Open-Source and Closed-Source Software Products. IEEE Transactions on Software Engineering,2004. 30 (4), 246-256
17- GNU Licences Website. [Accessed: 20 August 2014]. Available at: https://gnu.org/licenses/gpl.html
18- Osman, M., Elghaffi, F., Dalla, L. B., Karal, Ö., & Rashid, T. (2026). A New Approach for Low-Latency, High-Accuracy Anomaly Detection at the Edge: Benchmarking Quantized Autoencoders, LSTMs, and Lightweight Transformers on RT-IoT2022 Time-Series Traffic. Wadi Alshatti University Journal of Pure and Applied Sciences, 110-121.
19- Aydin, C.C and Tirkes, G.S. Open Source Learning Management Systems in E-learning and Moodle. IEEE EDUCON Education Engineering,2010.p, 593-600.
20- Degirmenci, A., & Karal, O. (2022). Efficient density and cluster based incremental outlier detection in data streams. Information Sciences, 607, 901-920.
21- Kakasevski, G., Mihajlov, M., Arsenovski, S. and Chungurski, S. Evaluating Usability in Learning Management System Moodle. Proceedings of the ITI 2008 30th International Conference on Information Technology Interfaces,2008
22- Hatipoğlu, Ş., Belgrat, M. A., Degirmenci, A., & Karal, Ö. (2021, October). Prediction of unemployment rates in Turkey by k-Nearest Neighbor regression analysis. In 2021 Innovations in Intelligent Systems and Applications Conference (ASYU) (pp. 1-5). IEEE.
23- Webopedia Website. [Accessed: 23 August 2013]. Available at: http://www.webopedia.com/TERM/P/plug_in.html
24- Liu, J. Comparative Study of Open-Source E-learning Management Platform. Proceedings of International Conference on Computational Intelligence and Software Engineering,2009.p, 1-4.
25- Ben Dalla, L. O. F., Medeni, T. D., Medeni, I. T., & Ulubay, M. (2025). Enhancing Healthcare Efficiency at Almasara Hospital: Distributed Data Analysis and Patient Risk Management. Economy: Strategy and Practice, 19(4), 54–72. https://doi.org/10.51176/1997-9967-2024-4-54-72
26- Dalla, L. O. F. B. (2020). Modeling by using Generic Modeling Environment (GME) Domain specific modeling language (DSL) for agile software development (ASD) types.
27- Бен Далла Л., Медени Т.Д., Медени И.Т., Улубай М. Повышение эффективности здравоохранения в больнице Алмасара: анализ распределенных данных и управление рисками для пациентов. Economy: strategy and practice. 2024;19(4):54-72. https://doi.org/10.51176/1997-9967-2024-4-54-72
28- Dalla, L. O. F. B. (2020). IT security Cloud Computing. . In 2020 IT security Cloud Computing Applications Conference (ITSCC) (pp. 1-10). IEEE. https://doi.org/10.16377/ITSCC 50717.2020.9259880
29- Degirmenci, A., & Karal, O. (2022). iMCOD: Incremental multi-class outlier detection model in data streams. Knowledge-Based Systems, 258, 109950. https://doi.org/10.1016/j.knosys.2022.109950
30- Dalla, L. O. F. B. (2020). Lean Software Development Practices and Principles in Terms of Observations and Evolution Methods to increase work environment productivity. International Journal of Engineering and Modern Technology, 6(1), 23-45.
31- Dougiamas, M. & Taylor, P. Moodle: Using Learning Communities to Create an Open Source Course Management System. In D. Lassner & C. McNaught, Proceedings of 32- World Conference on Educational Multimedia, Hypermedia and Telecommunications 2003, 171-178
32- MOODLE Website. [Accessed: 10 December 2014]. Available at: https://moodle.net/stats/
33- Mahmoodzadeh, A., Nejati, H. R., Mohammadi, M., Ibrahim, H. H., Rashidi, S., & Rashid, T. A. (2022). Forecasting tunnel boring machine penetration rate using LSTM deep neural network optimized by grey wolf optimization algorithm. Expert Systems with Applications, 209, 118303.
34- Moodle Website. [Accessed: 10 December 2014]. Available at: http://docs.moodle.org/dev/Plugins
35- Rashid, T. A., & Ahmad, H. A. (2016). Lecturer performance system using neural network with Particle Swarm Optimization. Computer Applications in Engineering Education, 24(4), 629-638.
36- Karal, Ö., & Dalla, L. O. F. B.(2025). Lung Nodule Characterization in CT Scans Using Hybrid 3D Attention U-Net Segmentation and Transfer Learning-Based Classification Approach.
37- Monperrus, M. et al. What should developers be aware of? An empirical study on the directives of API documentation. Empirical Software Engineering,2012. 17 (6), 703-737.
38- Dalla, L. O. B., Karal, Ö., & Degirmenciyi, A. (2025). Leveraging LSTM for Adaptive Intrusion Detection in IoT Networks: A Case Study on the RT-IoT2022 Dataset implemented On CPU Computer Device Machine. 5th International Conference on Engineering, Natural and Social Sciences, April 15-16, 2025: Konya, Turkey, 2025. Published by All Sciences Academy. https://www.icensos.com/
39- Karal, Ö. (2020, October). Performance comparison of different kernel functions in SVM for different k value in k-fold cross-validation. In 2020 innovations in intelligent systems and applications conference (ASYU) (pp. 1-5). IEEE.
40- Ben Dalla, L, O, F. (2021).Literature review (LR) on the powerful of Research methodology processes life cycle. In 2021 The Powerful of Research Methodology Processes Life Cycle Conference (TPRMPLCC) (pp. 1-10). IEEE. https://doi.org/10.16543/TPRMPLCC 50717.2020.92876580
41- Yalman, Y., Uyanık, T., Atlı, İ., Tan, A., Bayındır, K. Ç., Karal, Ö., ... & Guerrero, J. M. (2022). Prediction of voltage sag relative location with data-driven algorithms in distribution grid. Energies, 15(18), 6641.
42- Ben Dalla, L, O, F. (2021). Literature review (LR) on the dominant of Research methodology
43- Muttaqi, M., Degirmenci, A., & Karal, O. (2022, September). US accent recognition using machine learning methods. In 2022 Innovations in Intelligent Systems and Applications Conference (ASYU) (pp. 1-6). IEEE.
44- Ben Dalla, L., Medeni, T. M., Agila, A. A., & Medeni, İ. M. (2024). Architectural Synergy: Investigating the Role of Artificial Neural Networks in Enabling Deep Learning. The International Journal of Engineering & Information Technology (IJEIT), 12(1), 96-103.
45- Agila, et al., (2024). Diabetes Prediction Using a Support Vector Machine (SVM) and visualize the results by using the K-means algorithm
46- Dalla, L. O. F. B. (2020). The Influence of hospital management framework by the usage of Electronic healthcare record to avoid risk management (Department of Communicable Diseases at Misurata Teaching Hospital: Case study).
47- Dalla, L. O. F. B. (2020). Dorsal Hand Vein (DHV) Verification in Terms of Deep Convolutional Neural Networks with the Linkage of Visualizing Intermediate Layer Activations Detection. International Journal of Engineering and Modern Technology E-ISSN 2504-8848 P-ISSN 2695-2149 Vol 6 No 2 2020 www.iiardpub.org
48- Dalla, L. O. F. B. (2020). Convolutional Neural Network Baseline Model Building for Person Re-Identification. International Journal of Engineering and Modern Technology E-ISSN 2504-8848 P-ISSN 2695-2149 Vol. 6 No. 3 2020 www.iiardpub.org
49- Hamarashid, H. K., Saeed, S. A., & Rashid, T. A. (2022). A comprehensive review and evaluation on text predictive and entertainment systems. Soft Computing, 26(4), 1541-1562.
50- Rashid, T. A., & Aziz, N. K. (2016). Student academic performance using artificial intelligence. ZANCO Journal of Pure and Applied Sciences, 28(2).
51- DALLA, L. B. (2020). The Sustainable Efficiency of Modeling a Correspondence Undergraduate Transaction Framework by using Generic Modeling Environment (GME. Ben Dalla. International Journal of Engineering and Modern Technology E-ISSN 2504-8848 P-ISSN 2695-2149 . Vol 6 No 1 2020 www.iiardpub.org
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