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

Mitwirkende(r):

Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Reihen: Wiley Series on Methods and Applications in Data MiningVerlag: Hoboken, New Jersey : John Wiley & Sons, Inc, 2017Beschreibung: 1 Online-Ressource (314 pages)ISBN:

1118998227
1118998200
9781118998229
9781118998205
1118998219
1118998235
9781118998212
9781118998236

Schlagwörter:

370.72/7 23

LOC-Klassifikation:

LB1028.43

DOI: DOI: 10.1002/9781118998205Online-Ressourcen:

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Zusammenfassung: 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; REFERENCESZusammenfassung: 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; REFERENCESZusammenfassung: 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; 8.1 REVIEW OF€LITERATUREZusammenfassung: 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; REFERENCESPPN: PPN: 100276596XPackage identifier: Produktsigel: ZDB-35-UBC | ZDB-35-WIC

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