Ismaili Jalal, El Moutaouakil Karim
School of Technology, Moulay Ismail University of Meknes, Meknes, Morocco.
Engineering Sciences Laboratory, Multidisciplinary Faculty of Taza, Sidi Mohamed Ben Abdellah University, Fez, Morocco.
SN Comput Sci. 2023;4(3):290. doi: 10.1007/s42979-023-01726-z. Epub 2023 Mar 28.
Distance Learning (D-learning), as an alternative educational solution for students who cannot attend in-person classes, has been deployed during the COVID-19 pandemic to deliver the promises promoted long ago by technology and education experts. For many professors and students, the shift was a first as they had to resume their classes fully online despite not being academically competent to do so. This research paper examines the D-learning scenario introduced by Moulay Ismail University (MIU). It is based on the intelligent Association Rules method to identify relations between different variables. The significance of the method lies in its ability to assist in drawing relevant and accurate conclusions for decision-makers on how to rectify and adjust the adopted D-learning model in Morocco and elsewhere. The method also tracks the most probable future rules that govern the behavior of the population under study vis-à-vis D-learning; once these rules are outlined, the training quality can be dramatically improved by adopting better-informed strategies. The study concludes that most recurrent D-learning issues reported by students systematically interrelate with ownership of gadgets and that once specific procedures are implemented, reports concerning the D-learning experience at MIU are likely to be more comforting.
远程学习(D-learning)作为无法参加面授课程的学生的一种替代性教育解决方案,在新冠疫情期间得到了应用,以兑现技术和教育专家早就提出的承诺。对于许多教授和学生来说,这种转变是首次经历,因为他们不得不完全在线上恢复课程,尽管他们在学术上并不具备这样做的能力。本研究论文考察了穆莱·伊斯梅尔大学(MIU)引入的远程学习情况。它基于智能关联规则方法来识别不同变量之间的关系。该方法的重要性在于其能够协助决策者得出关于如何纠正和调整摩洛哥及其他地区所采用的远程学习模式的相关且准确的结论。该方法还追踪最有可能支配所研究人群在远程学习方面行为的未来规则;一旦勾勒出这些规则,通过采用更明智的策略,培训质量可得到显著提高。研究得出结论,学生报告的大多数反复出现的远程学习问题与设备拥有情况系统性地相互关联,并且一旦实施特定程序,关于穆莱·伊斯梅尔大学远程学习体验的报告可能会更令人欣慰。