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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.
This is a digital product.
Additional ISBNs
103200018X, 1032077352, 1003176348, 9781032000183, 9781032077352, 9781003176343
Innovative Learning Analytics for Evaluating Instruction: A Big Data Roadmap to Effective Online Learning 1st Edition is written by Theodore W. Frick; Rodney D. Myers; Cesur Dagli; Andrew F. Barrett and published by Routledge. The Digital and eTextbook ISBNs for Innovative Learning Analytics for Evaluating Instruction are 9781000454772, 1000454770 and the print ISBNs are 9781032000183, 103200018X. Additional ISBNs for this eTextbook include 103200018X, 1032077352, 1003176348, 9781032000183, 9781032077352, 9781003176343.
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