@article{benabdellah2023moroccan,
  title = {Moroccan Case Study:  Comparison and Analysis of Two  Prediction Techniques Applied to Grades},
  author = {Naoual CHAOUNI BENABDELLAH and Karima MOUMANE and Ahmed ZELLOU and   Kenza DOUIFIR},
  year = 2023,
  url = {https://ibimapublishing.com/articles/IBIMABR/2023/293513/},
  journal = {IBIMA Business Review},
  volume = 2023,
  pages = 17,
  doi = 10.5171/2023.293513,
  abstract = {In case of special difficult conditions of teaching and learning, Schools can adopt online learning. Different platforms and modes can be adopted to study online as synchronous mode, and asynchronous mode. This paper is about to discuss the program case grades where they were urged to switch to learning management systems and asynchronous tools such as teams, meetings, and others during the pandemic. The objective is to analyze and predict grades to decide whether the online mode need to stands. Data description was conducted to compare before and after the Covid state of scored evolution. Data was gathered for five promotions starting from the third semester to the sixth. Only the grades of the third semester were considered in the prediction process. As a methodology of the study, a description process of data was conducted after the preprocessing stage where data was normalized and transformed. Then the new prediction was applied. It was compared to other studies. The results were discussed according to the case.  Furthermore, two types of predictions were considered to analyze the grades obtained by attending in presence courses and grades obtained using online learning. These techniques are: exponential smoothing and time-series regression. The first one was applied to the overall modules that are at our disposal. And the second one was processed to modules of the third semester. This is to compare module 3.5 and the elements it compasses. The findings are that here is an overall increase in the average grades in the three upcoming years prediction. The focus is to analyze deeply the results of module 3.5. This module concerns software engineering. Results show in both applications of the serial smoothing and the time series regression that the prediction is going to be constant. This means that grades are not going to change. This result needs to be confronted with reality and to the grades of 2025.},
  keywords = {Prediction, online course, exponential smoothing, and time-series regression.},
  note = Article ID: 293513
}