Fr. 34.50

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

Inglese · Tascabile

Spedizione di solito entro 3 a 5 settimane

Descrizione

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Innovative Learning Analytics for Evaluating Instruction covers the application of a research methodology that uses big data to evaluate the effectiveness of online instruction. It is an ideal resource for faculty and professionals in instructional design, learning engineering, online learning, program evaluation, and research methods.


Sommario

1. Learning Journeys in Education 2. Overview of the Big Study 3. The Indiana University Plagiarism Tutorials and Tests 4. More Details of the Big Study 5. Analysis of Patterns in Time as a Research Methodology 6. Using Analysis of Patterns in Time for Formative Evaluation of a Learning Design 7. Analysis of Patterns in Time with Teaching and Learning Quality Surveys 8. Analysis of Patterns in Time as an Alternative to Traditional Approaches

Info autore

Theodore W. Frick is Professor Emeritus in the Department of Instructional Systems Technology in the School of Education at Indiana University Bloomington, USA.
Rodney D. Myers is Instructional Consultant in the School of Education at Indiana University Bloomington, USA.
Cesur Dagli is Research Analyst in the Office of Analytics & Institutional Effectiveness at Virginia Polytechnic Institute and State University, USA.
Andrew F. Barrett is Co-founder of ScaleLearning, Inc. and leads the Learning Technology team at Shopify, Inc., Canada

Riassunto

Innovative Learning Analytics for Evaluating Instruction covers the application of a research methodology that uses big data to evaluate the effectiveness of online 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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