A Proposed Model for E-learning Adaptability Measurement During COVID-19 Pandemic Using Data Mining Techniques


  • Ibrahim Nasir Mahmood Basra University of Oil and Gas
  • Mustafa Ali Abuzaraida Misurata University




E-Learning, Computer Aided Learning, Data Mining, E-learning Adaptation Model, Web Based Learning


E-learning became the main medium of education in the world for the past two years. COVID-19 virus has pushed all the universities and academic institutions to utilize and activate E-learning platforms and systems. The sudden and urgent transformation from the regular traditional learning system to E-learning system has involved many challenges and limitations. Therefore, the need to evaluate and enhance the current E-learning mechanism in Iraq became very urgent and critical need. The target level was students at higher education institutes which include university students in Basra city. The data collected based on students’ evaluation and opinions about E-learning based on their interaction and usage during two years under COVID-19 spread era. This research involved applying data mining techniques to sample dataset and utilizing the obtained results as feedback for a proposed model suggested by the authors to measure adaptability. The proposed model is derived from the idea of the Technology Acceptance Model (TAM) with focus on the positivity as the main factor to measure adaptability. The results of the research showed approximate adaptation level of 52% which is very close compared to the actual situation in real life which involve limitations and challenges faced by Iraqi students.

Author Biographies

Ibrahim Nasir Mahmood, Basra University of Oil and Gas

Ibrahim Nasir Mahmood is a lecturer in computer science field working at Basra University of Oil and Gas, Basra, Iraq. He received his BSc degree in Software Engineering on 2008. He holds Master’s degree in Computer Science from University of Bridgeport, CT, USA. He received his Master’s degree with Academic Achievement Award and Honors on 2013. Ibrahim is a member of the UPE International Computing Society. He works at the Department of Chemical Engineering and Oil Refinery in the Faculty of Oil and Gas Engineering, Basra University of Oil and Gas. His research interests include data mining, data science, machine learning, IoT, E-learning, and Algorithms. The author can be reached through his official email address which is: ibrahim.mahmood@buog.edu.iq

Mustafa Ali Abuzaraida, Misurata University

Dr. Mustafa Ali Abuzaraida is associated professor. He obtained his master
degree in (Intelligent System) from University Utara Malaysia (UUM) in 2006 and
a Ph.D. in (Computer Science) from International Islamic University Malaysia (IIUM)in 2015. His research interest is on Image processing, Data science, Data mining, Artificial intelligence application, and Natural Language Processing (NLP) mainly on text normalization and sentiment analysis and recognizing online handwritten text. He is a former international lecturer at University Utara Malaysia, and currently, he is working at Faculty of Information technology, Misurata University Libya as associate professor. The author can be reached through his official email address which is: abuzaraida@it.misuratau.edu.ly




How to Cite

Mahmood, I. N., & Abuzaraida, M. A. (2023). A Proposed Model for E-learning Adaptability Measurement During COVID-19 Pandemic Using Data Mining Techniques. International Journal of Interactive Mobile Technologies (iJIM), 17(01), pp. 74–95. https://doi.org/10.3991/ijim.v17i01.35731