Innovative learning analytics for evaluating instruction : a big data roadmap to effective online learning / Theodore W. Frick, Rodney D Myers, Cesur Dagli and Andrew F. Barrett.

Format:

Book

Author/Creator:

Frick, Theodore W., author.

Language:

English

Subjects (All):

Big data.

Educational evaluation--Data processing.

Educational evaluation.

Physical Description:

1 online resource (150 pages)

Edition:

1st ed.

Place of Publication:

New York ; London : Routledge, 2022.

Summary:

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.

Contents:

Cover

Half Title

Title Page

Copyright Page

Table of Contents

Foreword

Preface

Chapter Summaries

List of Tables, Figures, and Maps

1 Learning Journeys in Education

Metaphor of a Journey: The Oregon Trail

The State-Trait Approach to Measurement: Quantitative Methods

Individual Episodic Stories: Qualitative Methods

Qualitative Temporal Mapping that is Quantifiable and Generalizable: A Third Alternative for Educational Research Methods

The Larger Problem in Educational Research

References

2 Overview of the Big Study

A Tale of Two Learning Journeys

Learning Journey #1: Sam's Case

Learning Journey #2: Melinda's Case

Design and Structure of IPTAT Using First Principles of Instruction

Problem-Centered Principle

Activation Principle

Demonstration Principle

Application Principle

Integration Principle

Results from 936,417 Learning Journeys through IPTAT in the Big Study in 2019 and 2020

Activation Results

Demonstration Results

Overall Unique Pageviews

What Does All This Mean?

3 The Indiana University Plagiarism Tutorials and Tests

Introduction

Major Redesign of IPTAT in 2015

Authentic Problems Principle

Certification Tests

Summary of Changes to the Newly Designed IPTAT in 2015

What's the Same?

Usage of IPTAT from 2019 and 2020

Minimalists

Traditionalists

Dabblers

Registrants

User-Developer Feedback Loop

What About COVID?

4 More Details of the Big Study

Discovery of Google Analytics for Doing APT

Important Concepts for Doing Analysis of Patterns in Time

Two Fundamental Ways of Temporal Segmenting: Prediction and Retrodiction.

Temporal Segmenting by Quarters One at a Time

Retrodictive APT Queries

Endpoint Condition Defined

Users Who Passed

Users Who Have Not Passed

Apply the Endpoint Condition to the GA Audience Reporting Tool (UA)

Using GA to Find Matches of Pageviews within Segments

Wash, Rinse, and Repeat, then Combine

Some Key Issues We Identified and Resolved to do APT of IPTAT Data Streams Created by GA

Can You Do APT with GA4?

Who Are the Registered IPTAT Users in 2019 and 2020 (from Our MySQL Database at IU)?

Summary

5 Analysis of Patterns in Time as a Research Methodology

APT of Direct Instruction and Academic Learning Time: Joint Event Occurrences

Linear Models Approach

APT Approach

APT of Teacher-Student Interaction in Class: Frequency of Sequential Events

APT of Asynchronous Online Discussion: Sequential Patterns of Comments

APT Outside of Education

Moneyball

Google Analytics

6 Using Analysis of Patterns in Time for Formative Evaluation of a Learning Design

Simulation Fidelity

Evaluation of Fidelity

Using APT for Model Verification

The Diffusion Simulation Game

Applying the APT Procedure to the DSG

Data Analysis and Results

Conclusion

7 Analysis of Patterns in Time with Teaching and Learning Quality Surveys

APT of Course Evaluations

The Goal: Creating a Table from a Spreadsheet

Formation of TALQ Scales

Transferring MOO-TALQ Survey Responses to a Spreadsheet

Creating Spreadsheet Formulas for Each TALQ Scale

Creating Further Derived Scores for Scale Agreement (Yes or No)

Creating a Table for the Combinations of Categories

8 Analysis of Patterns in Time as an Alternative to Traditional Approaches

Making Inductive Inferences with APT.

Big Data in Education

Approaches to Big Data

Methods Used to Analyze Big Data

Learning Analytics and Instructional Design

The Value of Theory to Guide Educational Research

Extending APT

Epilogue

Abbreviations and Symbols

Index.

Notes:

Includes bibliographical references and index.

Description based on print version record.

ISBN:

1-00-317634-8

1-003-17634-8

1-000-45470-3

9781003176343

OCLC:

1259588293