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portada Innovative Learning Analytics for Evaluating Instruction: A big Data Roadmap to Effective Online Learning
Type
Physical Book
Publisher
Author
Year
2021
Language
English
Pages
154
Format
Hardcover
ISBN13
9781032000183
Edition No.
1
Categories

Innovative Learning Analytics for Evaluating Instruction: A big Data Roadmap to Effective Online Learning

Theodore W. Frick; Rodney D. Myers; Cesur Dagli; Andrew F. Barrett (Author) · Routledge · Hardcover

Innovative Learning Analytics for Evaluating Instruction: A big Data Roadmap to Effective Online Learning - Theodore W. Frick; Rodney D. Myers; Cesur Dagli; Andrew F. Barrett

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Synopsis "Innovative Learning Analytics for Evaluating Instruction: A big Data Roadmap to Effective Online Learning "

Innovative Learning Analytics for Evaluating Instruction covers the application of a forward-thinking research methodology that uses big data to evaluate the effectiveness of online instruction. Analysis of Patterns in Time (APT) is a practical analytic approach that finds meaningful patterns in massive data sets, capturing temporal maps of students’ learning journeys by combining qualitative and quantitative methods. Offering conceptual and research overviews, design principles, historical examples, and more, this book demonstrates how APT can yield strong, easily generalizable empirical evidence through big data; help students succeed in their learning journeys; and document the extraordinary effectiveness of First Principles of Instruction. It is an ideal resource for faculty and professionals in instructional design, learning engineering, online learning, program evaluation, and research methods.

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