Innovative Learning Analytics for Evaluating Instruction

Regular price €25.99
Quantity:
Ships in 10-20 days
Delivery/Collection within 10-20 working days
Shipping & Delivery
A01=Andrew F. Barrett
A01=Cesur Dagli
A01=Rodney D. Myers
A01=Theodore W. Frick
advanced online learning evaluation
Age Group_Uncategorized
Age Group_Uncategorized
analysis of patterns in time
Author_Andrew F. Barrett
Author_Cesur Dagli
Author_Rodney D. Myers
Author_Theodore W. Frick
automatic-update
big data
Big Study
Category1=Non-Fiction
Category=JMBT
Category=JNM
Category=JNQ
Client Id
COP=United Kingdom
CT
Delivery_Pre-order
DOI Theory
e-learning
educational data mining
educational research methods
eq_bestseller
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
first principles of instruction
formative assessment strategies
GA
GA Report
GA Tool
Google analytics
how to recognise plagiarism
Innovation Decision Process
innovative research
instructional design theory
instructional effectiveness
La Method
landmark research
Language_English
learning analytics
learning journeys
mastery learning
measuring learning achievement
mixed methods research
Model Verification
MOOC
Non-direct Instruction
Non-negative Matrix Factorization
online learning
Oregon Trail
PA=Not yet available
Peer Feedback Activities
Perceptual Fidelity
PHP Script
practical research
Price_€20 to €50
PS=Forthcoming
Quantitative Research
softlaunch
Standard Likert Scale
Student Engagement
Student Learning Journeys
student performance metrics
temporal data analysis
Temporal Maps
UG Student
Urchin Software
Webpage URL

Product details

  • ISBN 9781032077352
  • Weight: 453g
  • Dimensions: 138 x 216mm
  • Publication Date: 08 Oct 2024
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
  • Language: English
Secure checkout Fast Shipping Easy returns

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.

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

More from this author