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

Course details

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. In this course, you will: Understand what the Data Wise Improvement Process is and how it can help you improve teaching and learning. Build skills in looking at a wide range of data sources, including test scores, student work, and teaching practice. Identify next steps in supporting a culture of collaborative data inquiry in your setting. 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. HarvardX requires individuals who enroll in its courses on edX to abide by the terms of the edX honor code. HarvardX will take appropriate corrective action in response to violations of the edX honor code, which may include dismissal from the HarvardX course; revocation of any certificates received for the HarvardX course; or other remedies as circumstances warrant. No refunds will be issued in the case of corrective action for such violations. Enrollees who are taking HarvardX courses as part of another program will also be governed by the academic policies of those programs. HarvardX pursues the science of learning. By registering as an online learner in an HX course, you will also participate in research about learning. Read our research statement to learn more. Harvard University and HarvardX are committed to maintaining a safe and healthy educational and work environment in which no member of the community is excluded from participation in, denied the benefits of, or subjected to discrimination or harassment in our program. All members of the HarvardX community are expected to abide by Harvard policies on nondiscrimination, including sexual harassment, and the edX Terms of Service. If you have any questions or concerns, please contact harvardx@harvard.edu and/or report your experience through the edX contact form. Updated on 17 September, 2019