Modern Approach to Educational Data Mining and Its Applications
Springer Verlag, Singapore
978-981-334-680-2 (ISBN)
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.
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.
Erscheinungsdatum | 29.01.2021 |
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Reihe/Serie | SpringerBriefs in Applied Sciences and Technology | SpringerBriefs in Computational Intelligence |
Zusatzinfo | 34 Illustrations, color; 4 Illustrations, black and white; XXVII, 93 p. 38 illus., 34 illus. in color. |
Verlagsort | Singapore |
Sprache | englisch |
Maße | 155 x 235 mm |
Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
Sozialwissenschaften ► Pädagogik | |
Technik | |
Schlagworte | adaptive e-learning • Adaptive Framework • Cognitive Factor • Data Science • educational data mining • Intelligent system • Learning Analytics • Learninggap • Learning Preferences • machine learning • recommendation system |
ISBN-10 | 981-334-680-9 / 9813346809 |
ISBN-13 | 978-981-334-680-2 / 9789813346802 |
Zustand | Neuware |
Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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