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Data mining is a powerful tool being used by educational institutions to support student success, but often students do not know what data are being collected and how their privacy is being protected. This post explored the tension between privacy and data mining.
Teachers know that motivation matters. It is central to student learning; it helps determine how engaged students are in their work, how hard they work, and how well they persevere in the face of challenges. Though we hear mostly about the “achievement gap” between demographic groups, researchers have also identified…
Training observers is increasingly important for quality observation of teachers. This report examines research on observer training and investigates how five districts are preparing observers to conduct accurate, reliable, and useful observations.
In education, we often talk of confronting complicated problems, when they are truly complex problems. The difference between complicated and complex truly matters in how we works towards our end goals. It is time we approach complex problems as complex.
To reach increasingly high academic demands, we must better support student engagement. In “Motivation Matters," writers Susan Headden and Sarah McKay define key terms, discuss research findings, and explain promising approaches to boosting student motivation.
This report summarizes new psychological and behavioral research around building motivation and shows how teachers can increase motivation by encouraging positive behaviors, improving their academic mindsets, and enhancing their sense of connectedness.
Trying to improve practice is part of most educators practices, but what if we moved from trying to get better to getting better at getting better. Improvement science offers a method and set of tools to systematically build the know-how to reach our goals
Since 2008, Carnegie has been working to find a better way of learning how to improve. We have learned a great deal by doing, including that this work is a continuous improvement task. We invite you to join in on this ongoing process.
Improvement science relies on an understanding of the problem before creating solutions. Groups have found three key things helped them gain clarity on the problems and make the knowledge explicit, helping them design solutions with users, data, and will in mind.
Senior lecturer Marshall Ganz closing keynote at the 2016 Carnegie Summit on Improvement in Education focused on a framework for social action. Drawing on his own experience in social movements, Ganz talked of combining the power of the heart, head, and hands.
Using ideas borrowed from improvement science, Learning to Improve presents a process of disciplined inquiry that can be combined with the use of networks to identify, adapt, and successfully scale up promising interventions in education.
Improvement leaders share their personal experiences leading improvement at a Fall 2013 Carnegie Convening. What results are they most proud of? What were their biggest challenges? How did they overcome them? What would they do differently?
Using Improvement Science to Accelerate Learning and Address Problems of Practice Carnegie advocates for the use of improvement science to accelerate how a field learns to improve. Improvement science deploys rapid tests of change to guide the development, revision and continued fine-tuning of new tools, processes, work roles and relationships.
For many years, educational researchers have worked with program designers and implementers in pursuit of what has been called fidelity of implementation. Simply put, this has involved the application of numerous tools and procedures designed to ensure that implementers replicate programs exactly as they were designed and intended. There is…
This paper, by Carnegie President Anthony S. Bryk and Louis Gomez of the Northwestern University School of Education, was drawn from a presentation given by Bryk at the American Enterprise Institute for Public Policy Research on Oct. 25, 2007.
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