Educational Data Mining Techniques with Modern Approach

Abstract

Reviewing by and large more than 150 research papers, studies minutely observed the different learning styles, their detection methodologies, related frameworks and models, aggregation processes. The data mining techniques used in these studies had revealed the contemporary applications, different possibilities, and scope to reduce shortcomings in adaptive e-learning. The journey of development of adaptive e-learning system has been explained in terms of milestones snapshoot, relevant data extracted, linked processes explored, theories and concepts discussed, interactive logged data studied, and valuable ingredients chosen. These efforts have been introduced to develop the new improvised noble system to identify learning style preferences and providing complete adaptation to the learner. Soft computing tools in data mining domain have been deeply discussed with its advantages like similar functioning of the human brain and limitations in specific application areas. The research-related information in this chapter hovers around mainly two broad perspectives: One is educational data mining and another one is personalized adaptive e-learning system. We reviewed the literature related to adaptive e-learning within the ambit of educational data mining relevant to the proposed work. Here, we discussed the approaches used to investigate adaptive e-learning system in measurable units and extracted valuable information in terms of personalized adaptive e-learning. Also in this chapter aimed to discuss vivid and updated snapshots of the present state of researches.