Utilizing Educational Data Mining Techniques for Improved Learning: Emerging Research and Opportunities

Utilizing Educational Data Mining Techniques for Improved Learning: Emerging Research and Opportunities

Chintan Bhatt, Priti Srinivas Sajja, Sidath Liyanage
Indexed In: SCOPUS
Release Date: August, 2019|Copyright: © 2020 |Pages: 166
DOI: 10.4018/978-1-7998-0010-1
ISBN13: 9781799800101|ISBN10: 1799800105|EISBN13: 9781799800125
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Description & Coverage
Description:

Modern education has increased its reach through ICT tools and techniques. To manage educational data with the help of modern artificial intelligence, data and web mining techniques on dedicated cloud or grid platforms for educational institutes can be used. By utilizing data science techniques to manage educational data, the safekeeping, delivery, and use of knowledge can be increased for better quality education.

Utilizing Educational Data Mining Techniques for Improved Learning: Emerging Research and Opportunities is a critical scholarly resource that explores data mining and management techniques that promote the improvement and optimization of educational data systems. The book intends to provide new models, platforms, tools, and protocols in data science for educational data analysis and introduces innovative hybrid system models dedicated to data science. Including topics such as automatic assessment, educational analytics, and machine learning, this book is essential for IT specialists, data analysts, computer engineers, education professionals, administrators, policymakers, researchers, academicians, and technology experts.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Artificial Intelligence
  • Automatic Assessment
  • Behavioral Patterns
  • Big Data
  • Data Mining
  • Educational Analytics
  • Ethics
  • Higher Education
  • Learning Analytics
  • Machine Learning
  • Massively Open Online Courses (MOOCs)
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Editor/Author Biographies
Chintan Bhatt (Ph.D.) is currently working as an Assistant Professor in Computer Engineering department, Chandubhai S. Patel Institute of Technology, CHARUSAT. He is a member of IEEE, EAI, ACM, CSI, AIRCC and IAENG (International Association of Engineers). His areas of interest include Internet of Things, Data Mining, Web Mining, Networking, Security Mobile Computing, Big Data and Software Engineering. He has more than 5 years of teaching experience and research experience, having good teaching and research interests. He has chaired a track in CSNT 2015 and ICTCS 2014. He has been working as Reviewer in Wireless Communications, IEEE (Impact Factor-6.524) and Internet of Things Journal, IEEE, Knowledge-Based Systems, Elsevier (Impact Factor-2.9) Applied Computing and Informatics, Elsevier and Mobile Networks and Applications, Springer. He has delivered an expert talk on Internet of Things at Broadcast Engineering Society Doordarshan, Ahmedabad on 30/09/2015. He has been awarded Faculty with Maximum Publication in CSIC Award and Paper Presenter Award at International Conference in CSI-2015, held at New Delhi.
Priti Srinivas Sajja (b.1970) has been working at the Post Graduate Department of Computer Science, Sardar Patel University, India since 1994 and presently holds the post of Professor. She received her M.S. (1993) and Ph.D (2000) in Computer Science from the Sardar Patel University. Her research interests include knowledge-based systems, soft computing, multiagent systems, and software engineering. She has produced 186 publications in books, book chapters, journals, and in the proceedings of national and international conferences out of which five publications have won best research paper awards. She is author of Essence of Systems Analysis and Design (Springer, 2017) published at Singapore and co-author of Intelligent Techniques for Data Science (Springer, 2016); Intelligent Technologies for Web Applications (CRC, 2012) and Knowledge-Based Systems (J&B, 2009) published at Switzerland and USA, and four books published in India. She is supervising work of a few doctoral research scholars while seven candidates have completed their Ph.D research under her guidance. She has served as Principal Investigator of a major research project funded by University Grants Commission, India.

Sidath R Liyanage graduated from University of Kelaniya with BSc Honours in Statistics and Computer Science in 2005, he completed Master of Philosophy in Computer Engineering from University of Peradeniya in 2009 and received PhD from National University of Singapore in 2013. His research interests are in Brain Computer Interfaces, Data Science and applications of Machine Learning and pattern recognition. He has published over 40 publications.He is the Head of Department and a Senior Lecturer attached to Department of Software Engineering, Faculty of Computing and Technology, University of Kelaniya . He is a member of IEEE and a Council member of Sri Lanka Association for Artificial Intelligence.

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