Innovative Learning Analytics for Evaluating Instruction - A Big Data Roadmap to Effective Online Learning (Hardcover)

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.

General

Imprint:	Taylor & Francis
Country of origin:	United Kingdom
Release date:	July 2021
First published:	2022
Authors:	Theodore W. Frick • Rodney D. Myers • Cesur Dagli • Andrew F. Barrett
Dimensions:	216 x 138 x 16mm (L x W x T)
Format:	Hardcover
Pages:	132
ISBN-13:	978-1-03-200018-3
Categories:	Books > Social sciences > Psychology > Psychological methodology > Psychological testing & measurement Books > Social sciences > Education > Higher & further education > Open learning & distance education
LSN:	1-03-200018-X
Barcode:	9781032000183

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