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

データ種別	電子ブック
出版者	(Hoboken, New Jersey : John Wiley & Sons, Inc)
出版年	[2017]
大きさ	1 online resource (314 pages)
著者標目	ElAtia, Samira 1973- Ipperciel, Donald 1967- Za�iane, Osmar

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URL	巻　次	配架場所	請求記号	登録番号	コメント	刷　年	状　態	利用注記	ISBN	予約	請求メモ
URL		射水-電子	007	EB0005183	Wiley Online Library: Complete oBooks				9781118998205

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一般注記	Print version record 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 NA�IVE�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 Na�ive 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�LITERATURE Includes bibliographical references and index 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 John Wiley and Sons Wiley Online Library: Complete oBooks HTTP:URL=https://onlinelibrary.wiley.com/doi/book/10.1002/9781118998205
件　名	LCSH:Education -- Research -- Statistical methods 全ての件名で検索 LCSH:Educational statistics -- Data processing 全ての件名で検索 LCSH:Data mining MESH:Data Mining CSHF:Statistique de l'�education -- Informatique 全ての件名で検索 CSHF:Exploration de donn�ees (Informatique) FREE:EDUCATION -- Research 全ての件名で検索 FREE:COMPUTERS -- Databases -- Data Mining 全ての件名で検索 FREE:Data mining FREE:Education -- Research -- Statistical methods 全ての件名で検索 FREE:Educational statistics -- Data processing 全ての件名で検索 FREE:Learning analytics
分　類	LCC:LB1028.43 DC23:370.72/7
書誌ID	EB00004473
ISBN	9781118998205