OER at scale for academics, software engineers and education designers

Educational content should be open.

Open Ed Graph provides you with mapped collections of topics, learning outcomes and learning assessments, so you can easily reuse educational resources.

Our mapped data are modeled as graph structures where rich linkages in the data are explicitly exposed.

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OER at scale

Open Ed Graph goes beyond traditional Open Educational Resources — it provides resources at scale for those building next-gen educational applications.

We focus on reusability, updatability and performance. We handle the labor-intensive tasks of cataloging resources, updating them and formatting them so you can focus on designing great educational tools.

Our collections have been deployed in various student-facing and instructor-facing applications. While some collections have been authored by instructors and subject-matter experts, other collections contain student and peer contributions.

Each collection is annotated with the last time of update, where the collection has been used, and any published work associated with it.



Related publications:

Willcox K. and Huang, L., Network models for mapping educational data, Design Science, Vol. 3, e18, 2017. Network models for mapping educational data

Miller, H., Willcox, K. and Huang, L., Crosslinks: Improving Course Connectivity Using Online Open Educational Resources, in The Bridge, The National Academy of Sciences, Volume 46, Number 3, pp. 38-44, Fall 2016.

Willcox K. and Huang, L., Mapping Unbundled Open Education Resources: Pathways Through the Chaos, in FutuOER, The Future of Open Educational Resources, published October 2016.

Willcox K. and Huang, L., Mapping the CDIO Curriculum with Network Models, in Proceedings of the 13th International CDIO Conference, University of Calgary, Calgary, Canada, June 18-22, 2017.

Seering, J., Huang, L. and Willcox, K., Mapping Outcomes in an Undergraduate Aerospace Engineering Program. American Society for Engineering Education, 12th Annual Conference & Exposition, June 2015.


Our work is licensed under the Creative Commons CC BY license. This allows you, the user, to remix and adapt the content. If you use our work, you must attribute us. Read the terms of the license.

Our work is licensed under CC BY

How do I get access?

To get access to our APIs, you'll need to register your name, email and organizational affiliation.

For questions, contact us at mapping-lab@mit.edu.

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