Data mining and learning analytics : applications in educational research / edited by Samira Elatia, Donald Ipperciel, Osmar R. Zaiane.

Format:

Book

Contributor:

ElAtia, Samira, 1973- editor.

Ipperciel, Donald, 1967- editor.

Zaïane, Osmar, editor.

Series:

Wiley series on methods and applications in data mining.

Wiley Series on Methods and Applications in Data Mining

THEi Wiley ebooks

Language:

English

Subjects (All):

Data mining.

Education--Research--Statistical methods.

Education.

Educational statistics--Data processing.

Educational statistics.

Physical Description:

1 online resource (314 pages)

Edition:

First edition

Place of Publication:

Hoboken, New Jersey : Wiley, 2016.

System Details:

Access using campus network via VPN at home (THEi Users Only).

text file

Summary:

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.

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

Exploring the usefulness of adaptive elearning laboratory environments in teaching medical science / Thuan Thai and Patsie Polly

Investigating co-occurrence patterns of learners' grammatical errors across proficiency levels and essay topics based on association analysis / Yutaka Ishii

Part III. EDM and educational research

Mining learning sequences in MOOCs: Does course design constrain students' behaviors or do students shape their own learning? / Lorenzo Vigentini, Simon McIntyre, Negin Mirriahi, and Dennis Alonzo

Understanding communication patterns in MOOCs: Combining data mining and qualitative methods / Rebecca Eynon, Isis Hjorth, Taha Yasseri, and Nabeel Gillani

An example of data mining: Exploring the relationship between applicant attributes and academic measures of success in a pharmacy program / Dion Brocks and Ken Cor

A new way of seeing: Using a data mining approach to understand children's views of diversity and "difference" in picture books / Robin A. Moeller and Hsin-liang Chen

Data mining with natural language processing and corpus linguistics: Unlocking access to school children's language in diverse contexts to improve instructional and assessment practices / Alison L. Bailey, Anne Blackstock-Bernstein, Eve Ryan, and Despina Pitsoulakis.

Notes:

Description based upon print version of record.

Includes bibliographical references at the end od each chapters and index.

Description based on print version record.

ISBN:

9781118998212

1118998219

9781118998229

1118998227

9781118998205

1118998200

OCLC:

958565541