03932oam 2200541 450 991048421080332120220221111140.0981-334-681-710.1007/978-981-33-4681-9(CKB)4100000011728481(DE-He213)978-981-33-4681-9(MiAaPQ)EBC6462830(PPN)253254132(EXLCZ)99410000001172848120210624d2021 uy 0engtxtrdacontentcrdamediacrrdacarrierModern approach to educational data mining and its applications /Soni Sweta1st ed. 2021Gateway East, Singapore :Springer,[2021]©20211 online resourceSpringer Briefs in Computational Intelligence,2191-530X981-334-680-9 Educational Data Mining in E-Learning System -- Adaptive E-Learning System -- Educational Data Mining Techniques with Modern Approach -- Learning Style with Cognitive Approach -- Framework with Stakholders in Adaptive E-Learning System -- Personalization Based on Learning Preference -- Recommender System to Enhancing Efficacy of E-Learning System.This book emphasizes that learning efficiency of the learners can be increased by providing personalized course materials and guiding them to attune with suitable learning paths based on their characteristics such as learning style, knowledge level, emotion, motivation, self-efficacy and many more learning ability factors in e-learning system. Learning is a continuous process since human evolution. In fact, it is related to life and innovations. The basic objective of learning to grow, aspire and develop ease of life remains the same despite changes in the learning methodologies. Introduction of computers empowered us to attain new zenith in knowledge domain, developed pragmatic approach to solve life’s problem and helped us to decipher different hidden patterns of data to get new ideas. Of late, computers are predominantly used in education. Its process has been changed from offline to online in view of enhancing the ease of learning. With the advent of information technology, e-learning has taken centre stage in educational domain. In e-learning context, developing adaptive e-learning system is buzzword among contemporary research scholars in the area of Educational Data Mining (EDM). Enabling personalized systems is meant for improvement in learning experience for learners as per their choices made or auto-detected needs. It helps in enhancing their performance in terms of knowledge, skills, aptitudes and preferences. It also enables speeding up the learning process qualitatively and quantitatively. These objectives are met only by the Personalized Adaptive E-learning Systems in this regard. Many noble frameworks were conceptualized, designed and developed to infer learning style preferences, and accordingly, learning materials were delivered adaptively to the learners. Designing frameworks help to measure learners’ preferences minutely and provide adaptive learning materials to them in a way most appropriately.SpringerBriefs in Computational Intelligence,2625-3704.EducationData processingData Mininggnd(DE-588)4428654-5Pädagogikgnd(DE-588)4044302-4E-Learninggnd(DE-588)4727098-6EducationData processing.Data MiningPädagogikE-Learning371.334rvkDW 4400rvkSweta Soni981441MiAaPQMiAaPQUtOrBLWBOOK9910484210803321Modern approach to educational data mining and its applications2240105UNINA