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Data Analytics and Adaptive Learning
Research Perspectives
Taschenbuch von Patsy D. Moskal (u. a.)
Sprache: Englisch

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Beschreibung
Data Analytics and Adaptive Learning offers new insights into the use of emerging data analysis and adaptive techniques in multiple learning settings. In recent years, both analytics and adaptive learning have helped educators become more responsive to learners in virtual, blended, and personalized environments. This set of rich, illuminating, international studies spans quantitative, qualitative, and mixed-methods research in higher education, K-12, and adult/continuing education contexts. By exploring the issues of definition and pedagogical practice that permeate teaching and learning and concluding with recommendations for the future research and practice necessary to support educators at all levels, this book will prepare researchers, developers, and graduate students of instructional technology to produce evidence for the benefits and challenges of data-driven learning.
Data Analytics and Adaptive Learning offers new insights into the use of emerging data analysis and adaptive techniques in multiple learning settings. In recent years, both analytics and adaptive learning have helped educators become more responsive to learners in virtual, blended, and personalized environments. This set of rich, illuminating, international studies spans quantitative, qualitative, and mixed-methods research in higher education, K-12, and adult/continuing education contexts. By exploring the issues of definition and pedagogical practice that permeate teaching and learning and concluding with recommendations for the future research and practice necessary to support educators at all levels, this book will prepare researchers, developers, and graduate students of instructional technology to produce evidence for the benefits and challenges of data-driven learning.
Über den Autor

Patsy D. Moskal is Director of the Digital Learning Impact Evaluation in the Research Initiative for Teaching Effectiveness at the University of Central Florida, USA.

Charles D. Dziuban is Director of the Research Initiative for Teaching Effectiveness at the University of Central Florida, USA.

Anthony G. Picciano is Professor of Education Leadership at Hunter College and Professor in the PhD program in Urban Education at the City University of New York Graduate Center, USA.

Inhaltsverzeichnis

Section 1: Introduction 1. Data Analytics and Adaptive Learning: Increasing the Odds Section 2: Analytics 2. What We Want Versus What We Have: Transforming Teacher Performance Analytics to Personalize Professional Development 3. System-Wide Momentum 4. A Precise and Consistent Early Warning System for Identifying At-Risk Students 5. Predictive Analytics, Artificial Intelligence and the Impact of Delivering Personalized Supports to Students from Underserved Backgrounds 6. Predicting Student Success with Self-regulated Behaviors: A Seven-year Data Analytics Study on a Hong Kong University English Course 7. Back to Bloom: Why Theory Matters in Closing the Achievement Gap 8. The Metaphors We Learn By: Toward a Philosophy of Learning Analytics Section 3: Adaptive Learning 9. A Cross-Institutional Survey of the Instructor Use of Data Analytics in Adaptive Courses 10. Data Analytics in Adaptive Learning for Equitable Outcomes 11. Banking on Adaptive Questions to Nudge Student Responsibility for Learning in General Chemistry 12. 3-Year Experience with Adaptive Learning: Faculty and Student Perspectives 13. Analyzing Question Items with Limited Data 14. When Adaptivity and Universal Design for Learning are Not Enough: Bayesian Network Recommendations for Tutoring Section 4: Organizational Transformation 15. Sprint to 2027: Corporate Analytics in the Digital Age 16. Academic Digital Transformation: Focused on Data, Equity and Learning Science Section 5: Closing 17. Future Technological Trends and Research - Tony Picciano

Details
Erscheinungsjahr: 2023
Fachbereich: Didaktik/Methodik/Schulpädagogik/Fachdidaktik
Genre: Erziehung & Bildung, Importe
Rubrik: Sozialwissenschaften
Medium: Taschenbuch
Inhalt: Einband - flex.(Paperback)
ISBN-13: 9781032154701
ISBN-10: 1032154705
Sprache: Englisch
Einband: Kartoniert / Broschiert
Redaktion: Moskal, Patsy D.
Dziuban, Charles D.
Picciano, Anthony G.
Hersteller: Routledge
Verantwortliche Person für die EU: preigu, Ansas Meyer, Lengericher Landstr. 19, D-49078 Osnabrück, mail@preigu.de
Maße: 229 x 152 x 20 mm
Von/Mit: Patsy D. Moskal (u. a.)
Erscheinungsdatum: 25.08.2023
Gewicht: 0,53 kg
Artikel-ID: 126847891
Über den Autor

Patsy D. Moskal is Director of the Digital Learning Impact Evaluation in the Research Initiative for Teaching Effectiveness at the University of Central Florida, USA.

Charles D. Dziuban is Director of the Research Initiative for Teaching Effectiveness at the University of Central Florida, USA.

Anthony G. Picciano is Professor of Education Leadership at Hunter College and Professor in the PhD program in Urban Education at the City University of New York Graduate Center, USA.

Inhaltsverzeichnis

Section 1: Introduction 1. Data Analytics and Adaptive Learning: Increasing the Odds Section 2: Analytics 2. What We Want Versus What We Have: Transforming Teacher Performance Analytics to Personalize Professional Development 3. System-Wide Momentum 4. A Precise and Consistent Early Warning System for Identifying At-Risk Students 5. Predictive Analytics, Artificial Intelligence and the Impact of Delivering Personalized Supports to Students from Underserved Backgrounds 6. Predicting Student Success with Self-regulated Behaviors: A Seven-year Data Analytics Study on a Hong Kong University English Course 7. Back to Bloom: Why Theory Matters in Closing the Achievement Gap 8. The Metaphors We Learn By: Toward a Philosophy of Learning Analytics Section 3: Adaptive Learning 9. A Cross-Institutional Survey of the Instructor Use of Data Analytics in Adaptive Courses 10. Data Analytics in Adaptive Learning for Equitable Outcomes 11. Banking on Adaptive Questions to Nudge Student Responsibility for Learning in General Chemistry 12. 3-Year Experience with Adaptive Learning: Faculty and Student Perspectives 13. Analyzing Question Items with Limited Data 14. When Adaptivity and Universal Design for Learning are Not Enough: Bayesian Network Recommendations for Tutoring Section 4: Organizational Transformation 15. Sprint to 2027: Corporate Analytics in the Digital Age 16. Academic Digital Transformation: Focused on Data, Equity and Learning Science Section 5: Closing 17. Future Technological Trends and Research - Tony Picciano

Details
Erscheinungsjahr: 2023
Fachbereich: Didaktik/Methodik/Schulpädagogik/Fachdidaktik
Genre: Erziehung & Bildung, Importe
Rubrik: Sozialwissenschaften
Medium: Taschenbuch
Inhalt: Einband - flex.(Paperback)
ISBN-13: 9781032154701
ISBN-10: 1032154705
Sprache: Englisch
Einband: Kartoniert / Broschiert
Redaktion: Moskal, Patsy D.
Dziuban, Charles D.
Picciano, Anthony G.
Hersteller: Routledge
Verantwortliche Person für die EU: preigu, Ansas Meyer, Lengericher Landstr. 19, D-49078 Osnabrück, mail@preigu.de
Maße: 229 x 152 x 20 mm
Von/Mit: Patsy D. Moskal (u. a.)
Erscheinungsdatum: 25.08.2023
Gewicht: 0,53 kg
Artikel-ID: 126847891
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