In a recent essay titled Innovating Education with MOOC/FLIP, Princeton University professor Mung Chiang thoughtfully discusses Massive Online Open Courses (MOOCs) and some related innovations that are presenting educators with dilemmas and bringing to the surface pressures for possible change in traditional higher educational structures. Chiang sketches some of the recent history of these rapidly developing phenomena and shares some of his experiences developing and teaching a MOOC around computer and social networks. The core of Chiang’s essay—the ten questions focusing on opportunity and challenges—deals with some of the most important tensions surrounding MOOCs today. Read more ›
Jeanne Marie Iorio & Susan Matoba Adler’s (2013) commentary “Take a Number, Stand in Line, Better Yet, Be a Number Get Tracked: The Assault of Longitudinal Data Systems on Teaching and Learning” takes aim at a number of issues, including the growth in educational data in state databases and the unique numbers to identify and collect the records for students and teachers saying:
Statewide longitudinal databases are becoming sources for decision-making by policymakers, administrators, and teachers. These databases are tracking children and teachers, reducing the performance of children and the work of teachers to numbers. We call for an end to the obsession with the quantitative and hope for a rethinking of assessment and teaching practices that trust children and teachers as capable and critical to learning, teaching, and assessment.
The authors also question an organization called The Data Quality Campaign (DQC) linking the DQC to a litany of concerns about how collecting and using data is changing education. I agree with Iorio and Adler this is an important topic. In a new book titled “Assessing the Educational Data Movement” published by Teachers College Press (Piety, 2013) I explore this time of change in American education and look specifically at relationships between different organizations involved in promoting the use of educational data. Read more ›
“Phil Piety’s book employs insights from the learning sciences to illuminate policies and practices for using information to improve American education. His analyses reveal deeply-held convictions by educators concerning uses of data and why some of the test-based policies of the educational data movement—including No Child Left Behind and value-added models for teacher evaluation—have turned out more challenging in practice than in theory. Piety highlights our need to understand the multi-layered social nature of education, recognize a number of fundamental characteristics of educational data, and to integrate design-based principles for enhancing the socio-technical activity we call schooling.”
—Roy Pea, David Jacks Professor of Education and Learning Sciences, Stanford University
“Unquestionably there has been a dramatic change in the collection and use of education data within a relatively short period of time. This critically important book highlights what constitutes the education data movement describing the vernacular of what every education researcher, practitioner, and policymaker needs to be aware of. Cautiously optimistic about the future, Piety points out the challenges educators will face as they struggle with their ever increasingly complex datasets and how they can be made useful for measuring learning, teacher quality, and organizational change.”
—Barbara Schneider is the John A. Hannah Chair and University Distinguished Professor in the College of Education at Michigan State University, and president of the American Educational Research Association, 2013-14.
“Everyone who wants to gain a better understanding of how data is transforming education should read this book. Piety’s analysis is comprehensive and covers every dimension of the American education system. He impressively connects the dots among the numerous institutions and actors that comprise the data movement. This book is a triumph.”
—Darrell West, Vice President and Director of the Center for Technology Innovation, Brookings Institution
“Piety brings a fresh perspective to ‘the educational data movement,’ situating its emergence historically, linking it to developments in various institutional fields, and framing it as a ‘sociotechnical revolution.’ Essential reading! Both proponents and opponents of the ‘data movement’ will learn from this book.”
—James P. Spillane, Spencer T. & Ann W. Olin Professor in Learning & Organizational Change, Northwestern University
For better or worse, many educational decisions that were once handled on a personal level by teachers or administrators now increasingly rely upon data and information. To be successful in this era, educators need to understand this broad sociotechnical revolution and how it is realigning traditional roles and responsibilities. In this book, the author draws on his unique background in learning sciences, education policy, and information systems to provide valuable insights for both policy and practice. The text discusses many current topics including technology-rich methods of teacher evaluation, big data and analytics, longitudinal data systems, open educational resources, blended and personalized learning models, and new designs for teaching.
This comprehensive book:
• Examines the social and historical context of the educational data movement as it unfolds across educational levels.
• Synthesizes different research traditions from inside and outside of education.
• Assesses the successes, challenges, and potential of data analytics.
• Helps educators and innovators design technology-rich solutions for greater student success.
• Discusses the catalytic role that foundations have played in making education a more informational and evidence-based practice.
Philip J. Piety is a national expert in educational data, founder of Ed Info Connections, a benefit corporation serving to improve the information educators’ use, and a faculty affiliate of Johns Hopkins University.
Excerpt from the book Assessing the Educational Data Movement to be published in April, 2013
One of the issues to emerge in policy discourse and from funders as the educational data movement was taking hold involved personalized learning. While education has seen pendulum swings around standardization versus personalization for decades, what is new is the idea of using data and information to drive individual attention to student needs. While other fields are routinely using datasets about specific customers, and others like those customers, to present more relevant options and services, the classical model is still largely focused on providing the same options to students irrespective of what information about those students might suggest. What has been done in other fields is to use data about individuals to help segment and divide a large market into smaller groups to which services can be targeted. Of course, students within a classroom and teachers within a school are already part of a small group. It is possible that there are others like those students or those teachers in different locations that that data can provide some opportunities to see what types of approaches and tools work well with different students and teachers that have similar characteristics. Read more ›
Another excerpt from my forthcoming book: The Educational data movement: crossing boundaries, searching for student success
The classical model of teaching centers on the role of the teacher as manager of the classroom, conveyer and evaluator of knowledge. In this model, teachers direct everything that happens for all the students inside a classroom. Once the door is closed, teachers usually decide what order the information will be taught, which students will sit together or work together, and how to gauge and measure student understanding. The classical model of teaching is part of a traditional school design where all of the staff are arranged in a way that supports teachers in this classical role. Schools that have specialists—usually reading, math, and special education—use those specialists to augment the traditional classroom teachers. Read more ›
This is an extract from one of the chapters of my upcoming book titled: The Educational Data Movement: Crossing Boundaries, Searching for Student Success.
One of the greatest challenges of our time—of research, of school leadership, and now of measurement—is to define teaching or what teaching should be. The educational data movement occurs at time when there is great uncertainty about what it means to teach. The types of changes that education is going through, as other fields have before, impact jobs and roles and organizational structures. During this time, there has been a quest to describe the job of teachers in ways that can be used to compare teaching with other types of professions. The definition of teaching is an important factor in how we consider teachers using data in their jobs. Is their work mechanical to transmit knowledge or are they knowledge workers and knowledge creators? These are the kinds of questions that highlight what makes education different from other fields. Read more ›
Big data is a new term that can imply both new forms data and new analytic techniques. While big data is routine for many businesses and some sciences, it is new to education. Two characteristics of big data (in addition to lots of data) are that different kinds of information – some more structured than others – are used together and that the data focus is developing deep understandings of systems and context rather than only on outcomes. Organizations that leverage big data are often able to understand those they serve, and their environment better; to isolate and focus on their external and internal challenges and monitor their efforts. In American education, there is hope that big data tools can be a lever for change. Read more ›
In recent months there has been increasing attention to the need for education technologists who can focus on the many large and not so large datasets that are proliferating in education. Some have called for exploration into the educational data sciences and asked about how to prepare this new type of professional. Many questions are emerging about this important area. What classes should they take? Can this be a college major or should it be a professional certification? How is this different from educational statistics? Read more ›
Why should regular educational researchers, those working with science or social studies or emerging literacy pay attention to the changes in education around data. I can think of three reasons. Read more ›