(Wiley Series on Methods and Applications in Data Mining) 1st Edition
by Samira ElAtia (Editor), Donald Ipperciel (Editor), Osmar R. Zaïane (Editor)
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 collection models in the context of
educational research, while also defining and discussing data mining’s
four guiding principles― prediction, clustering, rule association, and
outlier detection. The next series of chapters showcase the pedagogical
applications of Educational Data Mining (EDM) and feature case studies
drawn from Business, Humanities, Health Sciences, Linguistics, and
Physical Sciences education that serve to highlight the successes and
some of the limitations of data mining research applications in
educational settings. The remaining chapters focus exclusively on EDM’s
emerging role in helping to advance educational research―from
identifying at-risk students and closing socioeconomic gaps in
achievement to aiding in teacher evaluation and facilitating peer
conferencing. This book features contributions from international
experts in a variety of fields.
- Includes case studies where data mining techniques have been effectively applied to advance teaching and learning
- Addresses
applications of data mining in educational research, including: social
networking and education; policy and legislation in the classroom; and
identification of at-risk students
- Explores Massive Open Online
Courses (MOOCs) to study the effectiveness of online networks in
promoting learning and understanding the communication patterns among
users and students
- Features supplementary resources including a primer on foundational aspects of educational mining and learning analytics
Data Mining and Learning Analytics: Applications in Educational Research
is written for both scientists in EDM and educators interested in using
and integrating DM and LA to improve education and advance educational
research.