Modern approach to educational data mining and its applications / Soni Sweta.
Sweta, Soni, author.
2021
LB1028.43
Available Online

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Title Modern approach to educational data mining and its applications / Soni Sweta.
Author Sweta, Soni, author.
ISBN 9789813346819 (electronic bk.)
9813346817 (electronic bk.)
9789813346802
9813346809
DOI https://doi.org/10.1007/978-981-33-4681-9
Published Singapore : Springer, [2021]
Language English
Description 1 online resource (xxvii, 93 pages) : illustrations (chiefly color)
Other Standard Identifiers 10.1007/978-981-33-4681-9 doi
Call Number LB1028.43
Dewey Decimal Classification 371.33/4
Summary 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.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Digital File Characteristics text file
PDF
Source of Description Online resource; title from PDF title page (SpringerLink, viewed March 9, 2021).
Series SpringerBriefs in applied sciences and technology. Computational intelligence. 2625-3704
Available in Other Form Print version: 9813346809
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
All Resources
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.

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