Introduction to Data Wise: A Collaborative Process to Improve Learning & Teaching

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Description

Educators have an ever-increasing stream of data at their fingertips, but knowing how to use this data to improve learning and teaching — how to make it less overwhelming, more useful, and part of an effective collaborative process — can be challenging. Based on the book Data Wise: A Step-by-Step Guide to Using Assessment Results to Improve Teaching and Learning, this course describes a clear, 8-step process for using a wide range of data sources to improve instruction. You will see what this disciplined way of working with colleagues can look and feel like in a school setting. You will also have the opportunity to share insights and experiences about school improvement with educators from around the world. Introduction to Data Wise is open to all but is especially valuable for teachers and school and district leaders, as well as policymakers, and educational entrepreneurs who are dedicated to improving outcomes for students. There are several ways you could take this course: Participate on your own. Enroll with a few colleagues as part of a study group. Formally integrate it into professional development in your workplace. It is a self-paced course. You can go through the essential materials in a day or take several weeks to allow for reflection. There will be one month of active course facilitation, which will include discussion board moderation, office hours, and other live events. This course provides an introduction to a rich portfolio of books, resources, training, and support developed by the Data Wise Project at the Harvard Graduate School of Education. The Data Wise Project works in partnership with teachers and school and system leaders to develop and field-test resources that support collaborative school improvement. We encourage you to explore these resources as you chart a course for using data to improve learning and teaching for all students.

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Category of Education Education

University

Harvard University

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