Modern Approach to Educational Data Mining and Its Applications

Häftad, Engelska, 2021

Del i serien SpringerBriefs in Applied Sciences and Technology

622 kr

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Beskrivning

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.

Produktinformation

Utgivningsdatum:2021-01-23
Mått:155 x 235 x 8 mm
Vikt:201 g
Format:Häftad
Språk:Engelska
Serie:SpringerBriefs in Applied Sciences and Technology
Antal sidor:93
Förlag:Springer Verlag, Singapore
ISBN:9789813346802

Utforska kategorier

Systemvetenskap och AI inom Data och IT
Databaser inom Data och IT
Artificiell intelligens inom Data och IT

Mer om författaren

Dr. Soni Sweta received her Master of Technology degree from Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, in 2011. She successfully completed her Ph.D. degree in the area of Soft Computing and Data Mining in Computer Science & Engineering from Birla Institute of Technology Mesra, Ranchi, in 2018. She has published more than 12 research papers in high-impact peer-reviewed international journals, 2 papers in national journals and 4 book chapters. Her research areas are soft computing, artificial intelligence, machine learning, data science and data mining. From 2004 to 2010, she has worked as Assistant Professor and Visiting Faculty in Computer Science & Engineering departments of different engineering colleges including MLB College; SNGPG College; Scope Engineering College, Bhopal; NSIT Patna; and CIPET Lucknow. She is presently working as Assistant Professor in Amity University Jharkhand, Ranchi, India.

Innehållsförteckning

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.