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

Format:

Book

Contributor:

ElAtia, Samira, 1973-

Ipperciel, Donald, 1967-

Zaïane, Osmar.

Wiley InterScience (Online service)

Series:

Wiley series on methods and applications in data mining

Wiley Series on Methods and Applications in Data Mining

Language:

English

Subjects (All):

Education--Research--Statistical methods.

Education.

Educational statistics--Data processing.

Educational statistics.

Data mining.

Education--Research.

Physical Description:

1 online resource (314 pages).

polychrome

Place of Publication:

Somerset : Wiley, 2016.

System Details:

text file

Contents:

TITLE PAGE ; COPYRIGHT PAGE ; CONTENTS; NOTES ON CONTRIBUTORS; INTRODUCTION: EDUCATION AT COMPUTATIONAL CROSSROADS; PART I AT THE INTERSECTION OF TWO FIELDS: EDM ; CHAPTER 1 EDUCATIONAL PROCESS MINING: A TUTORIAL AND CASE&STUDY USING MOODLE DATA SETS; 1.1 BACKGROUND; 1.2 DATA DESCRIPTION AND&PREPARATION; 1.2.1 Preprocessing Log Data; 1.2.2 Clustering Approach for&Grouping Log Data; 1.3 WORKING WITH&ProM; 1.3.1 Discovered Models; 1.3.2 Analysis of&the&Models' Performance; 1.4 CONCLUSION; ACKNOWLEdGMENTS; REFERENCES; CHAPTER 2 ON BIG DATA AND&TEXT MINING IN&THE&HUMANITIES

2.1 BUSA AND&THE&DIGITAL TEXT2.2 THESAURUS LINGUAE GRAECAE AND&THE&IBYCUS COMPUTER AS&INFRASTRUCTURE; 2.2.1 Complete Data Sets; 2.3 COOKING WITH&STATISTICS; 2.4 CONCLUSIONS; REFERENCES; CHAPTER 3 FINDING PREDICTORS IN&HIGHER EDUCATION; 3.1 CONTRASTING TRADITIONAL AND COMPUTATIONAL METHODS; 3.2 PREDICTORS AND&DATA EXPLORATION; 3.3 DATA MINING APPLICATION: AN&EXAMPLE; 3.4 CONCLUSIONS; REFERENCES; CHAPTER 4 EDUCATIONAL DATA MINING: A&MOOC EXPERIENCE; 4.1 BIG DATA IN&EDUCATION: THE&COURSE; 4.1.1 Iteration 1: Coursera; 4.1.2 Iteration 2: edX; 4.2 COGNITIVE TUTOR AUTHORING TOOLS; 4.3 BAZAAR

4.4 WALKTHROUGH4.4.1 Course Content; 4.4.2 Research on&BDEMOOC; 4.5 CONCLUSION; ACKNOWLEDGMENTS; REFERENCES; CHAPTER 5 DATA MINING AND ACTION RESEARCH; 5.1 PROCESS; 5.2 DESIGN METHODOLOGY; 5.3 ANALYSIS AND&INTERPRETATION OF&DATA; 5.3.1 Quantitative Data Analysis and&Interpretation; 5.3.2 Qualitative Data Analysis and&Interpretation; 5.4 CHALLENGES; 5.5 ETHICS; 5.6 ROLE OF&ADMINISTRATION IN&THE&DATA COLLECTION PROCESS; 5.7 CONCLUSION; REFERENCES; PART II PEDAGOGICAL APPLICATIONS OF EDM ; CHAPTER 6 DESIGN OF&AN&ADAPTIVE LEARNING SYSTEM AND&EDUCATIONAL DATA&MINING

6.1 DIMENSIONALITIES OF&THE&USER MODEL IN&ALS6.2 COLLECTING DATA FOR&ALS; 6.3 DATA MINING IN&ALS; 6.3.1 Data Mining for&User Modeling; 6.3.2 Data Mining for&Knowledge Discovery; 6.4 ALS MODEL AND&FUNCTION ANALYZING; 6.4.1 Introduction of&Module Functions; 6.4.2 Analyzing the&Workflow; 6.5 FUTURE WORKS; 6.6 CONCLUSIONS; ACKNOWLEDGMENT; REFERENCES; CHAPTER 7 THE "GEOMETRY" OF NAÏVE&BAYES: TEACHING PROBABILITIES BY "DRAWING"&THEM; 7.1 INTRODUCTION; 7.1.1 Main Contribution; 7.1.2 Related Works; 7.2 THE GEOMETRY OF&NB CLASSIFICATION; 7.2.1 Mathematical Notation; 7.2.2 Bayesian Decision Theory

7.3 TWO-DIMENSIONAL PROBABILITIES7.3.1 Working with&Likelihoods and&Priors Only; 7.3.2 De-normalizing Probabilities ; 7.3.3 NB Approach; 7.3.4 Bernoulli Naïve Bayes; 7.4 A NEW DECISION LINE: FAR FROM&THE&ORIGIN; 7.4.1 De-normalization Makes (Some) Problems Linearly Separable ; 7.5 LIKELIHOOD SPACES, WHEN LOGARITHMS MAKE A&DIFFERENCE (OR A&SUM); 7.5.1 De-normalization Makes (Some) Problems Linearly Separable ; 7.5.2 A New Decision in&Likelihood Spaces; 7.5.3 A Real Case Scenario: Text Categorization; 7.6 FINAL REMARKS; REFERENCES; CHAPTER 8 EXAMINING THE&LEARNING NETWORKS OF&A&MOOC

Notes:

Electronic reproduction. Hoboken, N.J. Available via World Wide Web.

Description based upon print version of record.

8.1 REVIEW OF&LITERATURE

Other Format:

Print version: ElAtia, Samira Data Mining and Learning Analytics : Applications in Educational Research

ISBN:

9781118998205

1118998200

9781118998229

1118998227

Publisher Number:

40026454143

Access Restriction:

Restricted for use by site license.