The LRMI 0.5 spec lets publishers communicate in a page’s HTML things like the competencies taught, the competencies required, the type of educational materials and the typical age range of intended users for anything educational published online. Time required for completion, degree of interactivity and a small number of other ways of describing educational content are included in the spec.
Active participants working to figure out how to construct LRMI and how to integrate it into Schema.org include people from small non-profits like open curriculum community Curriki, corporate education technology giant Pearson, international information standards group Dublin Core and intellectual property law group Creative Commons, among others.
Participants debate on the official mailing list over new terminology, balancing concerns like coherence with Schema.org, ease of input by people who will enter metadata to go with resources being published online and specificity gained or lost by the way that metadata fields are named and framed.
While some semantic technologies are able to assert categorization from the top down, whether content publishers participate or not, it seems likely that the kind of data that will be communicated in LRMI will require informed participation by the producers of the content themselves. Requiring participation in categorization could pose a challenge to hopes the spec will gain meaningful adoption.
The LRMI effort doesn’t seem well-known yet outside its own ranks, either; the official website has almost no inbound links indexed by Google yet and none of the education technology blogs we track here at ReadWriteWeb have mentioned LRMI yet. The project was just announced last month though and in the education market, a month isn’t a very long time.
LRMI isn’t alone though, either. Nathan Angell, a Board Director at the collaborative open education software community Sakai Foundation and a Product Manager at rSmart, calls LRMI “another welcome intervention in growing list of data specifications for education.”
“These days we have access to an unbelievable number of learning resources–both open and proprietary–but it’s still hard to find the right ones, quality resources, suited to your needs, when you need them.
“For example, in the Sakai community, we have built a new platform–the Open Academic Environment–that helps people create and tag learning materials, and most importantly, share them openly by default.
“With the LRMI specification, we can help people tag their materials with exactly the right information that will make them easy for others to find and use…and even better, we can augment the suggested content widgets we already have in place to discover resources in the moment that match the very specific needs of a particular educator or student.”
Angell, who isn’t associated with LRMI in particular, sees data specifications like this as potential game changers. Those suggested content widgets are really shorthand for computation that can begin at a higher level of abstraction if the hard work of content categorization and description has already been done in a standardized way. That means education technology providers, search engines and others don’t have to invest time and energy into understanding educational resources online – they can begin with a pre-existing understanding of that content and then offer higher-level features and services on top of already-organized information.
“LRMI helps set the stage for the hive mind that will help our children’s children learn faster and better than we ever thought possible,” Angel says. “In comparison, school today will look like drawing pictures in the dirt with a stick.”
HealthCare needs to think this way too. Work with the major search engines to introduce a metadata standard for health information.