| 000 | 09049cam a2200853 i 4500 | ||
|---|---|---|---|
| 001 | ocn958565541 | ||
| 003 | OCoLC | ||
| 005 | 20240523125539.0 | ||
| 006 | m o d | ||
| 007 | cr cnu---unuuu | ||
| 008 | 160917s2017 nju ob 001 0 eng d | ||
| 040 |
_aEBLCP _beng _erda _epn _cEBLCP _dN$T _dIDEBK _dDG1 _dN$T _dYDX _dNOC _dCCO _dOCLCF _dNRC _dOCLCQ _dDG1 _dOCLCQ _dCDN _dOCLCQ _dCOO _dVT2 _dLWU _dDG1 _dDEBSZ _dZ5A _dOCLCQ _dMERUC _dZCU _dICG _dOCLCQ _dOCLCA _dOCLCQ _dU3W _dOCLCQ _dDKC _dOCLCQ _dOCLCO _dSGP _dOCLCQ _dOCLCO _dOCLCL _dOCLCQ |
||
| 019 |
_a958454447 _a960831610 _a960832518 _a961150695 _a961152054 _a961308232 _a961309066 _a961826240 _a965393320 _a965431337 _a965735779 _a965988670 _a972959029 _a973137247 |
||
| 020 |
_a9781118998205 _q(electronic bk.) |
||
| 020 |
_a1118998200 _q(electronic bk.) |
||
| 020 |
_a9781118998229 _q(electronic bk.) |
||
| 020 |
_a1118998227 _q(electronic bk.) |
||
| 020 | _z1118998235 | ||
| 020 | _z1118998219 | ||
| 020 | _z1118998200 | ||
| 020 | _z9781118998236 | ||
| 020 |
_z9781118998212 _q(epub) |
||
| 029 | 1 |
_aAU@ _b000062136818 |
|
| 029 | 1 |
_aCHBIS _b011150610 |
|
| 029 | 1 |
_aCHNEW _b000945653 |
|
| 029 | 1 |
_aCHVBK _b480258139 |
|
| 029 | 1 |
_aDEBSZ _b485069628 |
|
| 029 | 1 |
_aGBVCP _b100276596X |
|
| 035 |
_a(OCoLC)958565541 _z(OCoLC)958454447 _z(OCoLC)960831610 _z(OCoLC)960832518 _z(OCoLC)961150695 _z(OCoLC)961152054 _z(OCoLC)961308232 _z(OCoLC)961309066 _z(OCoLC)961826240 _z(OCoLC)965393320 _z(OCoLC)965431337 _z(OCoLC)965735779 _z(OCoLC)965988670 _z(OCoLC)972959029 _z(OCoLC)973137247 |
||
| 037 |
_a953995 _bMIL |
||
| 050 | 4 |
_aLB1028.43 _b.D385 2017eb |
|
| 072 | 7 |
_aEDU _x037000 _2bisacsh |
|
| 072 | 7 |
_aCOM _x021030 _2bisacsh |
|
| 082 | 0 | 4 |
_a370.72/7 _223 |
| 049 | _aMAIN | ||
| 245 | 0 | 0 |
_aData mining and learning analytics : _bapplications in educational research / _cedited by Samira ElAtia, Donald Ipperciel, Osmar R. Zaiane. |
| 264 | 1 |
_aHoboken, New Jersey : _bJohn Wiley & Sons, Inc., _c[2017] |
|
| 300 | _a1 online resource (314 pages) | ||
| 336 |
_atext _btxt _2rdacontent |
||
| 337 |
_acomputer _bc _2rdamedia |
||
| 338 |
_aonline resource _bcr _2rdacarrier |
||
| 588 | 0 | _aPrint version record. | |
| 505 | 0 | _aTITLE 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. | |
| 505 | 8 | _aCHAPTER 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. | |
| 505 | 8 | _aCHAPTER 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. | |
| 505 | 8 | _aCHAPTER 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. | |
| 504 | _aIncludes bibliographical references and index. | ||
| 520 | _aAddresses 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. | ||
| 590 |
_aJohn Wiley and Sons _bWiley Online Library: Complete oBooks |
||
| 650 | 0 |
_aEducation _xResearch _xStatistical methods. |
|
| 650 | 0 |
_aEducational statistics _xData processing. |
|
| 650 | 0 | _aData mining. | |
| 650 | 2 | _aData Mining | |
| 650 | 6 |
_aStatistique de l'�education _xInformatique. |
|
| 650 | 6 | _aExploration de donn�ees (Informatique) | |
| 650 | 7 |
_aEDUCATION _xResearch. _2bisacsh |
|
| 650 | 7 |
_aCOMPUTERS _xDatabases _xData Mining. _2bisacsh |
|
| 650 | 7 |
_aData mining _2fast |
|
| 650 | 7 |
_aEducation _xResearch _xStatistical methods _2fast |
|
| 650 | 7 |
_aEducational statistics _xData processing _2fast |
|
| 653 | _aLearning analytics. | ||
| 700 | 1 |
_aElAtia, Samira, _d1973- _1https://id.oclc.org/worldcat/entity/E39PCjFdcy7c4ghVq9wyMwHWcP |
|
| 700 | 1 |
_aIpperciel, Donald, _d1967- _1https://id.oclc.org/worldcat/entity/E39PBJvHbJ8JhTHRkKq99HjKVC |
|
| 700 | 1 | _aZa�iane, Osmar. | |
| 758 |
_ihas work: _aData mining and learning analytics (Text) _1https://id.oclc.org/worldcat/entity/E39PCFR6wJbJRG3mkMmhg89TBP _4https://id.oclc.org/worldcat/ontology/hasWork |
||
| 776 | 0 | 8 |
_iPrint version: _aElAtia, Samira. _tData Mining and Learning Analytics : Applications in Educational Research. _dSomerset : Wiley, �2016 _z9781118998236 |
| 856 | 4 | 0 | _uhttps://onlinelibrary.wiley.com/doi/book/10.1002/9781118998205 |
| 938 |
_aEBL - Ebook Library _bEBLB _nEBL4675499 |
||
| 938 |
_aEBSCOhost _bEBSC _n1351385 |
||
| 938 |
_aProQuest MyiLibrary Digital eBook Collection _bIDEB _ncis32858445 |
||
| 938 |
_aYBP Library Services _bYANK _n13174150 |
||
| 938 |
_aYBP Library Services _bYANK _n13160003 |
||
| 994 |
_a92 _bINLUM |
||
| 999 |
_c12386 _d12386 |
||