Title Statements
- Full title :Data mining and learning analytics : applications in educational research / edited by Samira ElAtia, Donald Ipperciel, Osmar R. Zaiane.
Summary
"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."--Publisher's description.
Read More ↓Edition Statements
- Publication Date:2016
Publication Statements
- Publisher(s):John Wiley & Sons, Inc
- Place of Publication:Hoboken, New Jersey
- Language:eng
- Publication Date:2016
The Physical Object
- Description:xxviii, 283 pages : : illustrations ; : 24 cm.
Edition Identifiers
- ISBN:9781118998236, 1118998235
- oclc:ocn952199814
- LC Classification:LB1028.43
- Dewey Decimal:370.72/7
Table of Contents
Part I. At the intersection of two fields: EDM -- Educational process mining: A tutorial and case study using Moodle data sets / Christóbal Romero, Rebeca Cerezo, Alejandro Bogarín, and MIguel Sánchez-Santillán -- On big data and text mining in the humanities / Geoffrey Rockwell and Bettina Berendt -- Finding predictor in higher education / David Eubanks, William Evers Jr., and Nancy Smith -- Educational data mining: A MOOC experience / Ryan S. Baker, Yuan Wang, Luc Paquette, Vincent Aleven, Octav Popsecu, Jonathan Sewall, Carolyn Rosé, Gaurav Singh Tomar, Oliver Ferschke, Jing Zhang, Michael J. Cennamo, Stephanie Ogden, Therese Condit, José Diaz, Scott Crossley, Danielle S. McNamara, Denise K. Comer, Collin F. Lynch, Rebecca Brown, Tiffany Barnes, and Yoav Bergner -- Data mining and action research / Ellina Chernobilsky, Edith Ries, and Joanna Jasmine -- Part II. Pedagogical applications of EDM -- Design of an adaptive learning system and educational data mining / Zhiyong Liu and NIck Cercone -- The "Geometry" of naïve Bayes: Teaching probabilities by "drawing" them / Giorgio Maria Di Nunzio -- Examining the learning networks of a MOOC / Meaghan Brugha and Jean-Paul Restoule -- E…
Read More ↓Subjects
Writers
More from this Series
No reviews yet. Be the first to rate this work.
Files & Downloads
-
Data Mining and Learning Analytics: Applications …
PDF · 6.2 MB · updated
Rate & Review