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100 1 _aK G, Srinivasa.
_eauthor.
_0(orcid)0000-0003-1022-8431
_1https://orcid.org/0000-0003-1022-8431
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_92061
245 1 2 _aA Beginner’s Guide to Learning Analytics
_h[electronic resource] /
_cby Srinivasa K G, Muralidhar Kurni.
250 _a1st ed. 2021.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2021.
300 _aXIII, 326 p. 40 illus., 38 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aAdvances in Analytics for Learning and Teaching,
_x2662-2130
505 0 _aChapter 1 -- Introduction to Learning Analytics -- 1.1. Introduction to Learning Analytics -- 1.2. Learning analytics: A new and rapidly developing field -- 1.3. Benefits and Challenges of learning analytics -- 1.4. Ethical Concerns with Learning Analytics -- 1.5. Use of Learning analytics -- 1.6. Conclusion -- 1.7. Review Questions -- Chapter 2 Educational Data Mining & Learning Analytics -- 2.1. Introduction -- 2.2. Educational Data Mining (EDM) -- 2.3. Educational Data Mining & Learning analytics -- 2.4. Educational Data Mining & Learning analytics Applications -- 2.5. Conclusion -- 2.6. Review Questions -- Chapter 3.-Preparing for Learning Analytics -- 3.1. Introduction -- 3.2. Role of Psychology in Learning analytics -- 3.3. Architecting the learning analytics environment -- 3.4. Major Barriers for adopting Learning Analytics.-3.5. Case Studies -- 3.6. Conclusion -- 3.7. Review Questions -- Chapter 4. Data requirements for Learning analytics -- 4.1. Introduction -- 4.2. Types of data used for Learning Analytics -- 4.3. Data Models used to represent usage data for Learning analytics -- 4.4. Data Privacy maintenance in Learning analytics -- 4.5. Case Studies -- 4.6. Conclusion -- 4.7. Review Questions -- Chapter 5. Tools for Learning Analytics -- 5.1. Introduction -- 5.2. Popular Learning Analytics Tools -- 5.3. Choosing a Tool -- 5.4. Strategies to Successfully Deploy a Tool -- 5.5. Exploring Learning Analytics Tools -- 5.6. Case Studies -- 5.7. Developing a Learning analytics Tool -- 5.8. Conclusion -- 5.9. Review Questions.-Chapter 6 -- Other Technology Approaches to Learning Analytics -- 6.1. Introduction -- 6.2. Big Data & Learning Analytics -- 6.3. Data Science & Learning Analytics -- 6.4. AI & Learning Analytics -- 6.5. Machine Learning & Learning Analytics -- 6.6. Deep Learning & Learning Analytics -- 6.7. Case Studies -- 6.8. Conclusion -- 6.9. Review Questions -- Chapter 7 -- Learning Analytics in Massive Open Online Courses -- 7.1 Introduction to MOOCs -- 7.2. From MOOCs to Learning analytics -- 7.3. Integrating Learning analytics with MOOCs -- 7.4. Benefits of applying Learning Analytics in MOOCs -- 7.5. Major Concerns of implementing Learning Analytics in MOOCs -- 7.6. Limitation of Applying Learning Analytics in MOOCs -- 7.7. Tools that support Leaning analytics in MOOCs -- 7.8. Case Studies -- 7.9. Conclusion -- 7.10. Review Questions -- Chapter 8 -- The Pedagogical perspective of Learning Analytics -- 8.1. Introduction to Pedagogy -- 8.2. Learning Analytics based Pedagogical Framework -- 8.3. Pedagogical Interventions -- 8.4. Learning Analytics based Pedagogical Models -- 8.5. Case studies -- 8.6. Conclusion -- 8.7. Review Questions -- Chapter 9. Moving Forward -- 9.1. Self-Learning and Learning analytics -- 9.2. Lifelong learning and learning analytics -- 9.3. Present and future trend of learning analytics in the world -- 9.4. Measuring 21st Century Skills using Learning analytics -- 9.5. Moving Forward -- 9.6. Smart Learning analytics -- 9.7. Case Studies -- 9.8. Conclusion -- 9.9. Review Questions.-Chapter 10 -- Case Studies -- 10.1. Recommender systems using learning analytics -- 10.2. Learning Analytics in Higher Education -- 10.3. Other Evidences on the use of Learning Analytics -- Chapter 11. Problems.
520 _aThis book A Beginner’s Guide to Learning Analytics is designed to meet modern educational trends’ needs. It is addressed to readers who have no prior knowledge of learning analytics and functions as an introductory text to learning analytics for those who want to do more with evaluation/assessment in their organizations. The book is useful to all who need to evaluate their learning and teaching strategies. It aims to bring greater efficiency and deeper engagement to individual students, learning communities, and educators. Covered here are the key concepts linked to learning analytics for researchers and practitioners interested in learning analytics. This book helps those who want to apply analytics to learning and development programs and helps educational institutions to identify learners who require support and provide a more personalized learning experience. Like chapters show diverse uses of learning analytics to enhance student and faculty performance. It presents a coherent framework for the effective translation of learning analytics research for educational practice to its practical application in different educational domains. This book provides educators and researchers with the tools and frameworks to effectively make sense of and use data and analytics in their everyday practice. This book will be a valuable addition to researchers’ bookshelves.
650 0 _aEducational technology.
650 0 _aEducation—Data processing.
_91492
650 1 4 _aDigital Education and Educational Technology.
650 2 4 _aComputers and Education.
_91495
700 1 _aKurni, Muralidhar.
_eauthor.
_0(orcid)0000-0002-3324-893X
_1https://orcid.org/0000-0002-3324-893X
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_4http://id.loc.gov/vocabulary/relators/aut
_92062
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030702571
776 0 8 _iPrinted edition:
_z9783030702595
776 0 8 _iPrinted edition:
_z9783030702601
830 0 _aAdvances in Analytics for Learning and Teaching,
_x2662-2130
_92063
856 4 0 _uhttps://doi.org/10.1007/978-3-030-70258-8
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