Name: Innovative Learning Analytics for Evaluating Instruction: A big Data Roadmap to Effective Online Learning (en Inglés)
Price: 62.32 USD
Availability: InStock
Author: Theodore W. Frick; Rodney D. Myers; Cesur Dagli; Andrew F. Barrett
ISBN: 9781032000183

portada Innovative Learning Analytics for Evaluating Instruction: A big Data Roadmap to Effective Online Learning (en Inglés)

Innovative Learning Analytics for Evaluating Instruction: A big Data Roadmap to Effective Online Learning (en Inglés)

Formato

Libro Físico

Editorial

Routledge

Autor

Theodore W. Frick; Rodney D. Myers; Cesur Dagli; Andrew F. Barrett

Año

2021

Idioma

Inglés

N° páginas

154

Encuadernación

Tapa Dura

ISBN13

9781032000183

N° edición

Categorías

Educación

Innovative Learning Analytics for Evaluating Instruction: A big Data Roadmap to Effective Online Learning (en Inglés)

Theodore W. Frick; Rodney D. Myers; Cesur Dagli; Andrew F. Barrett (Autor) · Routledge · Tapa Dura

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Reseña del libro "Innovative Learning Analytics for Evaluating Instruction: A big Data Roadmap to Effective Online Learning (en Inglés)"

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.