000 03763nam a2200505Ia 4500
001 2336
008 230305s2017 xx 000 0 und d
020 _a9783319065199
041 _aeng
245 0 _aBig Data and Learning Analytics in Higher Education Current Theory and Practice
260 _a
_bSpringer,
_c2017
300 _axx, 272 pages : llustrations (some color) ; 24 cm
500 _acurrent theory and practice
505 _aChapter 1: Overview of Big Data and Analytics in Higher Education
_rChapter 2: Thoughts on Recent Trends and Future Research Perspectives in Big Data and Analytics in Higher Education--
_rChapter 3: Big Data in Higher Education: The Big Picture--
_rChapter 4: Preparing the Next Generation of Education Researchers for Big Data in Higher Education--
_rChapter 5: Managing the Embedded Digital Ecosystems (EDE) Using Big Data Paradigm--
_rChapter 6: The Contemporary Research University and the Contest for Deliberative Space--
_rPart II: LEARNING ANALYTICS--
_rChapter 7: Ethical Considerations in Adopting a University- and System-Wide Approach to Data and Learning Analytics--
_rChapter 8: Big Data, Higher Education and Learning Analytics: Beyond Justice, Towards an Ethics of Care--
_rChapter 9: Curricular and Learning Analytics: A Big Data Perspective--
_rChapter 10: Implementing a Learning Analytics Intervention and Evaluation Framework: What Works?--
_rChapter 11: GraphFES: A Web Service and Application for Moodle Message Board Social Graph Extraction--
_rChapter 12: Toward an Open Learning Analytics Ecosystem--
_rChapter 13: Predicting Four-Year Student Success from Two-Year Student Data--
_rChapter 14: Assessing Science Inquiry Skills in an Immersive, Conversation-Based Scenario--
_rChapter 15: Learning Analytics of Clinical Anatomy e-Cases.--
520 _aThis book focuses on the uses of big data in the context of higher education. The book describes a wide range of administrative and operational data gathering processes aimed at assessing institutional performance and progress in order to predict future performance, and identifies potential issues related to academic programming, research, teaching and learning​. Big data refers to data which is fundamentally too big and complex and moves too fast for the processing capacity of conventional database systems. The value of big data is the ability to identify useful data and turn it into useable information by identifying patterns and deviations from patterns​.
590 _bIncludes bibliographical references index.
630 _aLB - Theory and practice of education
_9933
650 _aBig data
_95432
650 _a Analytics
_92554
650 0 _aTrends
_98874
650 0 _aHigher education
_97088
650 _a Research
_98394
650 _a Embedded Digital Ecosystems (EDE)
_910218
650 _a Data Paradigm
_910219
650 _a Ethical Considerations
_910220
650 _a Justice
_96921
650 _a Care
_910221
650 _a Ethics
_910222
650 _a Curricular
_910223
650 _a Evaluation
_93857
650 _a Moodle
_910224
650 _a GraphFES
_910225
650 _a Ecosystem
_910226
650 _a Skills
_94151
650 _a Clinical Anatomy e-Cases
_910227
650 _a e-Cases
_910228
700 _aDaniel, Ben Kei
_eAuthor
_910229
856 _uhttps://books.google.es/books?id=hpHqDAAAQBAJ&lpg=PP1&dq=Big%20Data%20and%20Learning%20Analytics%20in%20Higher%20Education%20Current%20Theory%20and%20Practice&hl=es&pg=PP1#v=onepage&q=Big%20Data%20and%20Learning%20Analytics%20in%20Higher%20Education%20Current%20Theory%20and%20Practice&f=false
902 _a541
905 _am
912 _a2017-01-01
942 _a1
953 _d2018-10-29 16:29:56
999 _c2245
_d2245