Learning Analytics

From Research to Practice

  • Johann Ari Larusson
  • Brandon White

Table of contents

  1. Front Matter
    Pages i-xii
  2. Johann Ari Larusson, Brandon White
    Pages 1-12
  3. Preparing for Learning Analytics

    1. Front Matter
      Pages 13-13
    2. Abelardo Pardo
      Pages 15-38
    3. John T. Behrens, Kristen E. DiCerbo
      Pages 39-60
    4. Ryan Shaun Baker, Paul Salvador Inventado
      Pages 61-75
  4. Learning Analytics for Learning Communities

    1. Front Matter
      Pages 77-77
    2. Matthew D. Pistilli, James E. Willis III, John P. Campbell
      Pages 79-102
    3. Andrew E. Krumm, R. Joseph Waddington, Stephanie D. Teasley, Steven Lonn
      Pages 103-119
  5. Learning Analytics for Teachers and Learners

  6. Back Matter
    Pages 191-195

About this book

Introduction

In education today, technology alone doesn't always lead to immediate success for students or institutions. In order to gauge the efficacy of educational technology, we need ways to measure the efficacy of educational practices in their own right. Through a better understanding of how learning takes place, we may work toward establishing best practices for students, educators, and institutions. These goals can be accomplished with learning analytics.

Learning Analytics: From Research to Practice updates this emerging field with the latest in theories, findings, strategies, and tools from across education and technological disciplines. Guiding readers through preparation, design, and examples of implementation, this pioneering reference clarifies LA methods as not mere data collection but sophisticated, systems-based analysis with practical applicability inside the classroom and in the larger world.

Case studies illustrate applications of LA throughout academic settings (e.g., intervention, advisement, technology design), and their resulting impact on pedagogy and learning. The goal is to bring greater efficiency and deeper engagement to individual students, learning communities, and educators, as chapters show diverse uses of learning analytics to:

  • Enhance student and faculty performance.
  • Improve student understanding of course material.
  • Assess and attend to the needs of struggling learners.
  • Improve accuracy in grading.
  • Allow instructors to assess and develop their own strengths.
  • Encourage more efficient use of resources at the institutional level.

Researchers and practitioners in educational technology, IT, and the learning sciences will hail the information in Learning Analytics: From Research to Practice as a springboard to new levels of student, instructor, and institutional success.

Keywords

Data Mining and Education Knowledge Assessment in Education LA and Education Learning Analytics and Education Learning Analytics in CSCL Predicitve Modeling and Education

Editors and affiliations

  • Johann Ari Larusson
    • 1
  • Brandon White
    • 2
  1. 1.Center for Digital Data, Analytics and Adaptive Learning at PearsonBostonUSA
  2. 2.Dept. of EnglishUniversity of California BerkeleyBerkeleyUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4614-3305-7
  • Copyright Information Springer Science+Business Media New York 2014
  • Publisher Name Springer, New York, NY
  • eBook Packages Humanities, Social Sciences and Law
  • Print ISBN 978-1-4614-3304-0
  • Online ISBN 978-1-4614-3305-7
  • About this book