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Learning Analytics in Education: Experts Explain How To Use Data To Understand and Increase Learner Success

Oct. 11, 2018

New technologies, better measures and more data, all related to learning, hold the promise of helping educators increase their students’ success. The relatively new field of learning analytics has developed to help educators understand and use the increasing amounts of evidence from learners’ experiences. How can educators harness access to greater data to improve learning on a large scale?

Learning Analytics in Education is a new book written by a broad range of experts who explain their methods, describe examples, and point out new underpinnings for the field. The collected essays show how learning analytics can improve the chances of success for all learners through deeper understanding of the academic, social-emotional, motivational, identity and meta-cognitive context each learner uniquely brings.

The collection was edited by four noted educational experts:

  • David Niemi, vice president of measurement and evaluation at Kaplan, Inc., the global educational services company well-known for using advanced learning science and learning engineering methods in it programs and products.
  • Roy Pea, the David Jacks Professor of Learning Sciences and Education at the Stanford Graduate School of Education.
  • Bror Saxberg, vice president of learning science at the Chan Zuckerberg Initiative, and formerly Kaplan, Inc.’s chief learning officer.
  • Richard Clark, Emeritus Professor of Educational Psychology and Technology at the University of Southern California Rossier School of Education, and a member of Kaplan, Inc.’s learning science advisory board.

In one chapter of the book, lead editor Niemi and co-editors Clark and Saxberg:

  • Describe the problem of persistence to explore how data and learning analytics can help inform motivational interventions and other tactics to reach learners at risk of dropping out of high school or college.
  • Present statistics to illustrate the extent of the problem. Eighty-four percent (84%) of high-income students go to college, compared with 41% of low-income students. Each class of high-school dropouts costs the nation more than $200 billion in lost wages, tax revenues as well as in spending for social-support programs. (Source: National Educational Association). Half of student dropouts from online courses are due to the quality of institutional support.
  • Offer tactics for how analytics can be used to evaluate and improve academic persistence.

“At Kaplan, we’ve been invested in using learning science and data analytics for several years to help us design courses and refine instructional methods to help students achieve better outcomes,” explains Niemi.  “Educators today face accelerating change as education undergoes a fundamental transformation driven by the replacement of traditional analog tools by digital systems and expansive data inputs.”  He adds, “Understanding how to use these new streams of available data to best guide student learning is the essential point of the book.”

Learning Analytics in Education provides an essential framework, as well as guidance and examples, for a wide range of professionals interested in the future of learning. If you are already involved in learning analytics, or otherwise trying to use an increasing density of evidence to understand learners’ progress, these leading thinkers in the field may give you new insights. If you are engaged in teaching at any level, or training future teachers/faculty for this new, increasingly technology-enhanced learning world, and want some sense of the potential opportunities (and pitfalls) of what technology can bring to your teaching and students, these forward-thinking leaders can spark your imagination.

If you are involved in research around uses of technology, improving learning measurements, better ways to use evidence to improve learning, or in more deeply understanding human learning itself, you will find additional ideas and insights from some of the best thinkers in the field here. If you are involved in making administrative or policy decisions about learning, you will find new ideas (and dilemmas) coming your way from inevitable changes in how we design and deliver instruction, how we measure the outcomes, and how we provide feedback to students, teachers, developers, administrators, and policy-makers.

For educators, researchers, administrators, business leaders, and policy makers, Learning Analytics in Education will serve as a guide and reference to understanding measurement and learning analytics in our rapidly changing digital world.

About the Lead Editor:

David Niemi is Vice President of Measurement and Evaluation at Kaplan, Inc., where he oversees efforts to improve the quality of measurement across all education units, evaluate the effectiveness of curricula and instruction, and study the impact of innovative products and strategies.

Previously he was Vice President Evaluation and Research, at K12 Inc., where he directed assessment development and validation, evaluation of products and services, and research studies used to drive curriculum development. He has been a co-principal investigator for a number of large-scale assessment research projects funded by the U.S. Department of Education and the National Science Foundation and has collaborated on Department of Defense training studies. As a researcher and professor at UCLA and the University of Missouri, respectively, he has also managed assessment research and development studies in school districts across the U.S. and has trained thousands of teachers and other professionals to design and use assessments more effectively.

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Press contacts:

VSK Public Relations, LLC
Valerie Silverman Kerr
Office: 914-806-6647
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