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Big Data for Education

Offered By: Harvard University via edX

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Big Data Courses Education & Teaching Courses

Course Description

Overview

Did you know that students taught for a single year in high school by a great teacher earn an average of $50,000 more over the course of their lifetime? Education can increase or decrease a child’s likelihood of economic mobility. In the Big Data For Education professional certificate series, teachers and educational administrations can take a data-driven approach to education, learning how to use data to improve instruction and creating long-term value for their students.

In the first course, Big Data Solutions to Economic and Social Problems, you will examine the historical evidence identifying the characteristics that lead to improved outcomes. You will see some of the benefits of big data and how it can be used to measure mobility related to K-12 education and see how test scores, student performance, class size, and funding can affect a student's future economic status.

In the second course, Introduction to Data Wise: A Collaborative Process to Improve Learning & Teaching, you will learn how to parse the multiple data streams available to educators to improve learning and teaching. You will also have the opportunity to share insights and experiences about school improvement with educators from around the world and learn what is involved in using data to build a culture of collaborative inquiry.

Big Data for Education is geared to help teachers and administrators understand how to use data to better teach students and build a more equitable future.


Syllabus

Courses under this program:
Course 1: Big Data Solutions for Social and Economic Disparities

Join Harvard University Professor Raj Chetty in this online course to understand how big data can be used to measure mobility and solve social problems.



Course 2: Introduction to Data Wise: A Collaborative Process to Improve Learning & Teaching

Learn what is involved in using data wisely to build a culture of collaborative inquiry.




Courses

  • 1 review

    10 weeks, 1-2 hours a week, 1-2 hours a week

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    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.


Taught by

Kathryn Parker Boudett, Raj Chetty and Abby Hiller

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