How To Find Open Content Needles in the OER Haystack

[Blaine Victor Morrow]

One of the challenges to widespread OER adoption is that of finding everything that's available and discovering what's out there. I've tried in other posts to point to repositories and directories, but the problem hasn't gone away simply because lots of folks are starting collections. Or has it?

One of the most hopeful signs of significant progress is the Learning Registry, which comes from the United States Department of Education in conjunction with the U.S. Department of Defense. This directory gathers K-adult digital educational content from federal, state, district, and non-government sources. I like the approach: if you contribute content, you register it, and the index/search engine allows searches by subject, grade level, and other criteria. The registry is "in the cloud" in the sense that it can be embedded on and searched from multiple Web sites.

The developers and partners in this venture are excited and enthusiastic (always a good thing). For example, they host things like "The Learning Registry Plugfest" ("Do you have metadata or paradata that describes your learning resources that you want to get into the Learning Registry? Do you have data about how learning resources relate to, or align with, the Common Core or state curricular standards that you want to share via the Learning Registry? Do you want to operate a node in the Learning Registry network? Are there additional features that you would like to help implement? Do you want to create mashups with the Learning Registry? Do you want to build value-added services on top of the Learning Registry?") to bring developers together for workshops and retreats. 

The Association of Educational Publishers, with Creative Commons, has another promising haystack-reducer: the Learning Resource Metadata Initiative (LMRI), which has developed a common metadata framework for describing or “tagging” learning resources on the web. This should make it easier to find educational resources on the Web using common search engines like Google and Yahoo by using a consistent tagging standard, controlled vocabulary, and search-engine-friendly metadata.