Educational Data Mining

This book is devoted to the Educational Data Mining arena. It highlights works that show relevant proposals, developments, and achievements that shape trends and inspire future research.

Educational Data Mining

This book is devoted to the Educational Data Mining arena. It highlights works that show relevant proposals, developments, and achievements that shape trends and inspire future research. After a rigorous revision process sixteen manuscripts were accepted and organized into four parts as follows: · Profile: The first part embraces three chapters oriented to: 1) describe the nature of educational data mining (EDM); 2) describe how to pre-process raw data to facilitate data mining (DM); 3) explain how EDM supports government policies to enhance education. · Student modeling: The second part contains five chapters concerned with: 4) explore the factors having an impact on the student's academic success; 5) detect student's personality and behaviors in an educational game; 6) predict students performance to adjust content and strategies; 7) identify students who will most benefit from tutor support; 8) hypothesize the student answer correctness based on eye metrics and mouse click. · Assessment: The third part has four chapters related to: 9) analyze the coherence of student research proposals; 10) automatically generate tests based on competences; 11) recognize students activities and visualize these activities for being presented to teachers; 12) find the most dependent test items in students response data. · Trends: The fourth part encompasses four chapters about how to: 13) mine text for assessing students productions and supporting teachers; 14) scan student comments by statistical and text mining techniques; 15) sketch a social network analysis (SNA) to discover student behavior profiles and depict models about their collaboration; 16) evaluate the structure of interactions between the students in social networks. This volume will be a source of interest to researchers, practitioners, professors, and postgraduate students aimed at updating their knowledge and find targets for future work in the field of educational data mining.

More Books:

Educational Data Mining
Language: en
Pages: 468
Authors: Alejandro Peña-Ayala
Categories: Technology & Engineering
Type: BOOK - Published: 2013-11-08 - Publisher: Springer

This book is devoted to the Educational Data Mining arena. It highlights works that show relevant proposals, developments, and achievements that shape trends and inspire future research. After a rigorous revision process sixteen manuscripts were accepted and organized into four parts as follows: · Profile: The first part embraces three
Modern Approach to Educational Data Mining and Its Applications
Language: en
Pages: 93
Authors: Soni Sweta
Categories: Technology & Engineering
Type: BOOK - Published: 2021-01-22 - Publisher: Springer Nature

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
Utilizing Educational Data Mining Techniques for Improved Learning: Emerging Research and Opportunities
Language: en
Pages: 166
Authors: Bhatt, Chintan, Sajja, Priti Srinivas, Liyanage, Sidath
Categories: Education
Type: BOOK - Published: 2019-08-02 - Publisher: IGI Global

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,
Handbook of Educational Data Mining
Language: en
Pages: 535
Authors: Cristobal Romero, Sebastian Ventura, Mykola Pechenizkiy, Ryan S.J.d. Baker
Categories: Business & Economics
Type: BOOK - Published: 2010-10-25 - Publisher: CRC Press

Handbook of Educational Data Mining (EDM) provides a thorough overview of the current state of knowledge in this area. The first part of the book includes nine surveys and tutorials on the principal data mining techniques that have been applied in education. The second part presents a set of 25
Data Mining and Learning Analytics
Language: en
Pages: 320
Authors: Samira ElAtia, Donald Ipperciel, Osmar R. Zaïane
Categories: Computers
Type: BOOK - Published: 2016-09-06 - Publisher: John Wiley & Sons

Addresses the impacts of data mining on education and reviews applications in educational research teaching, and learning This book discusses the insights, challenges, issues, expectations, and practical implementation of data mining (DM) within educational mandates. Initial series of chapters offer a general overview of DM, Learning Analytics (LA), and data