Abstract
Adaptive e-learning system is widely accepted system in which learners get information as per their own preferences either hidden or expressed. Hence, adaptive learning process maximizes learning and helps learners to achieve the course targets successfully in a lesser time and in a very cost-effective manner. It has immense capability to diagnose complete learner’s behavior as well as provide suitable course recommendations, automated personalized contents, and due guidance for learning path as per requirements detected from the choices made by the learner. In this chapter, a brief introduction to adaptive and personalized e-learning system is presented. This chapter also discusses the detailed idea of educational data mining in e-learning domain, an adaptive e-learning system followed by the challenges and motivation for choosing such kind of research issue. This chapter clearly identifies what, why and how solution of the problem can be derived and given the detailed idea about the processes. The chapter highlights the requirement of changes from stereotyped e-learning to adaptive personalized e-learning system. Finally, the chapter provides an introduction to all about the fundamentals concepts and related work of adaptive e-learning applications and logical structure for the processing of adapting learning contents.
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Sweta, S. (2021). Adaptive E-Learning System. In: Modern Approach to Educational Data Mining and Its Applications. SpringerBriefs in Applied Sciences and Technology(). Springer, Singapore. https://doi.org/10.1007/978-981-33-4681-9_2
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