Performance Based Adaptive Personalized eLearning System

Abstract

Step by step eLearning is developing pattern in industry. To the extent, learning technique is concerned it has been seen that conventional learning strategy, for example, instructor and learner as well as chalk and duster swings too inventive learning. Because of innovation in technology each one started learning by utilizing web. If learner is asking for particular learning material sometimes they are not getting relevant result. So there is need to acquire certain data of learner. This data incorporates their learning style, foundation learning, Knowledge level, learning interest, age and so forth. This proposed system tends to use retrieve, reuse, revise and retain phases of CBR. For construction of customized eLearning there has been identification of various list of features. In light of list of features there has been task of assignment of priorities according to need of it. Before retrieval process standardization of features set process is carried out. Job of K-nearest neighbour strategy to recognize impeccable k factor for better examination. Because of dynamically incremental dataset this work identifies which classification algorithm has more suitable for the dataset. Eventually eLearning saves time, enhance learning experience and provides academic success.

Mapping Research Themes and Future Directions in Learning Style Detection Research: A Bibliometric and Content Analysis

“…In cluster 3, denoted by the color blue, the research theme centers around machine learning and artificial intelligence in the context of adaptive learning. This cluster primarily focuses on adaptive learning approaches utilizing diverse machine learning algorithms, such as decision tree (Dutsinma and Temdee, 2020), k-means (Yusoff, Najib Bin Fathi and ., 2018), knn (Shekapure and Patil, 2019), and deep learning (Zhang et al, 2021c). These algorithms play a crucial role in analyzing student data and delivering personalized learning experiences tailored to the unique needs of individual learners.…”