Systematic Reviews in Educational Research, Olaf Zawacki-Richter; Michael Kerres; Svenja Beden

Автор: Creswell, John W. Creswell, J. David
Название: Research Design: Qualitative, Quantitative, and Mixed Methods Approaches, 5 ed.
ISBN: 1506386768 ISBN-13(EAN): 9781506386768
Издательство: Sage Publications
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Цена: 17519.00 р.
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Описание: The bestseller that pioneered the comparison of qualitative, quantitative, and mixed methods research design continues in its Fifth Edition to help students and researchers prepare their plan or proposal for a scholarly journal article, dissertation or thesis.

Название: Educational design research
ISBN: 0415396352 ISBN-13(EAN): 9780415396356
Издательство: Taylor&Francis
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Цена: 8420.00 р.
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Описание: Provides a synthesised assessment of the use of development research in education, looking at four main elements. This work provides background information including origins, definitions of development research, description of applications and benefits and risks associated with studies of this kind.

Автор: Todd Ruecker
Название: Navigating challenges in qualitative educational research :
ISBN: 036717362X ISBN-13(EAN): 9780367173623
Издательство: Taylor&Francis
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Цена: 6889.00 р.
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Описание: This book provides guidance and lessons from when research doesn`t go as planned. It includes narratives from researchers that provide real world experiences of how they navigated challenges, as well as their considerations in doing so.

Автор: Bradley Efron and Trevor Hastie
Название: Computer Age Statistical Inference
ISBN: 1107149894 ISBN-13(EAN): 9781107149892
Издательство: Cambridge Academ
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Цена: 9029.00 р.
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Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.