Abstract

E-learning has been widely adopted as an important tool for distance education, especially in these days of pandemic Covid-19. However, several problems/challenges have been re-ported in different processes of e-learning that need to be ad-dressed for effective use of e-learning. These problems/challenges include development of student focused contents, giving learner partial control, addressing different learning styles, etc . Recently, several efforts have been made to solve e-learning process problems using dynamic programming techniques. Dynamic pro-gramming techniques divide a problem situation into several sub-problems and dynamically solves each sub-problem based on student needs. Thus it allows student focused customization at each step and provides adaptive e-learning to support students with different capabilities. The objective of this study is to review different e-learning problems and challenges and how those can be addressed using dynamic programming techniques. We conclude by highlighting the importance of different dynamic programming techniques for different processes of e-learning.

Highlights

  • Developments in information and communication technology (ICT) have introduced E-learning programs which can be employed efficiently as an alternative to allow users to learn and teach new technologies and courses

  • Dynamic programming is a method of optimization depends on the precept of optimality realize by Richard Bellman

  • It is considered one of the solutions and methods that have contributed to solving many problems in various fields, especially in e-learning

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Summary

Introduction

Developments in information and communication technology (ICT) have introduced E-learning programs which can be employed efficiently as an alternative to allow users to learn and teach new technologies and courses. E-Learning online courses are available 24/7, regardless of the time of day, accessible and reliable educational resources to students in geographically spread regions and time zones. This type of delivery enables the portability of training (i.e., tablet/iPad, laptop, cell phone for files or video assessments and links to webinars, etc.), allowing for easy learning on the go, with the growth of networks, mobile use, and learning via computers or laptops [2]. A growing number of researchers are inspecting and studying dynamic programming (DP) algorithm-based learning systems to solve and fix stochastic ideal control problems, arguing that DP provides the proper basis for combining planning results into real-time reactive dominance techniques, as well as for learning these techniques when the managed system is incompletely understood. The fifth section is a comparative analysis that concludes the studies presented in this paper, and the final section concludes the article

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