Blog Post

LRMI for Badgers (and why issuers can't ignore it)

Relevance: Why Alignment matters to badges

One of the primary functions of Badges is to act as indicators of achievement – academic, personal, community, or otherwise. You've accomplished something, documented it, been recognized by your mentors and your peers. You have skills and the badge to prove it!

So what skills were they?

Before you answer, ask yourself whether you're about to use words that your listener will understand. Particularly when your listener will be a computer.

The Open Badges ecosystem will, at its heart, be an intricately interwoven collaborative enterprise linking human organizations and software systems to encourage and document meaningful learning experiences through digital data systems. Systems. Plural. If we accept that John might earn his SQL Programmer Badge in one system, while Susan earns her SQL Coder Badge from another… then potential employer Laurie must be able to find them both and make an apples-to-apples comparison in a third, employer-focused system.

The only way this can be accomplished is if all three of those systems – and in fact, every individual system that chooses to join the Open Badge Ecosystem – can speak the same language when describing qualifications.

This is of the utmost importance to badge issuers, because badges that do not claim relevance in the agreed-upon way will stand mute, looking as if they have nothing to say – and thus fall to the "Uncategorized" bottom of every search. Worse: consider the future of an unaligned Badge in a world driven by powerfully innovative systems like Adams 50/LevelUP's student competency maps – there is no home for a badge with no box.

 

LRMI: A common language for educational alignment claims

LRMI, the Learning Resource Metadata Initiative, is a collaboration of the Association of Educational Publishers and Creative Commons (funded by the Gates and Hewlett Foundations) to produce a standardized data format to embody learning-relevant claims about educational content.

Put simply, LRMI is the project to define a common language for claiming educational relevance and alignment. LRMI is also commonly used as the name of the format itself.

The work behind LRMI has been in progress for some time, and is now reaching a 1.0 level of maturity. LRMI takes the form of a series of tags that content creators (i.e. badge issuers) can embed in their content (badges) that represent a number of different claims about the educational nature and relevance of the content.

For instance, including the following tag on a webpage:

<li itemprop="educationalAlignment" itemscope itemtype="http://schema.org/AlignmentObject">
<meta itemprop="alignmentType" content="teaches">
<a itemprop="targetName" href="http://asn.jesandco.org/resources/S11435AF">Determine whether two events are mutually exclusive and whether two events are independent.</a></li>

Tells any search engine that looks at the page that it is claiming to teach ("alignmentType" is "teaches") something that is educationally aligned ("educationalAlignment") with the standard described at the web address "http://asn.jesandco.org/resources/S11435AF".

That link points the Common Core Mathematics standard "CCSS.Math.Content.HSS-CP.A.2", which reads "2. Understand that two events A and B are independent if the probability of A and B occurring together is the product of their probabilities, and use this characterization to determine if they are independent."

Taken together, this block of code makes the claim that it teaches students about statistical independence, as defined by the Common Core State Standards for Mathematics. And it does so in a format that any LRMI-compliant system can understand.

As an important side note, the current specification for LRMI is designed for inclusion in webpages or other forms of content (e.g. Flash SWF). Badges, technically, are not content, but rather a representation of achievement or completion of that content. Accordingly, work has begun to bridge this distinction and support Badges in the LRMI specification. Once this work is complete, you should expect some more explicit technical direction on how LRMI and OBI interact – or if you want to get involved in making these decisions, by all means speak up!

 

Standards as Shared Reference Points

There is a subtle subtext here that deserves to be addressed.

Standards are often a contentious issue in education for a number of reasons. I won't get into that here, but as you can see in the example above, LRMI uses Standards frameworks as the common reference points for claims of relevance. That is, when you claim that your badge represents a skill, the question "Which skill?" is answered by pointing to a Standard, like "CCSS.Math.Content.HSS-CP.A.2".

If your program chooses to align with the Common Core State Standards, then you will find that every standard is already mapped to an LRMI-compatible identifier. In fact, the Common Core site itself hosts these references, so "educationalAlignment" URLs can be pointed straight to the official source.

It is important to realize, however, that your choice of standards is completely your own. If your work aligns with a different Standards framework (Computer Science, 21st Century Skills, Girl Scouts, …), multiple standards within a framework, or more than one framework, this is absolutely not a problem. Simply list and link them all.

Actually, this multiple-alignment capability turns out to be quite indispensable. In practice, not even the Common Core alignments are a stationary target. For example, as the different states and assessment consortia begin to subdivide the content covered in the CCSS, a project called Granular Identifiers and Metadata for the Common Core State Standards (GIM-CCSS) is tagging the finer-grained skills and concepts. Future Common Core-aligned badges might want to tag themselves with both high-level and fine-grained identifiers, and LRMI supports that.

 

Claims vs. Credibility

Finally, one last distinction that came to light during an Unconference session at the September Badges workshop deserves note: LRMI is completely neutral and hands-off with regard to the actual credibility behind an alignment claim.

If I wrote a paragraph about monkeys and tagged it "Trigonometry", LRMI would not call me out on it – that's not its function or its place. LRMI's job is to make sure that everybody understands that my claim is that the paragraph aligns with learning trigonometry. The fact that the claim is false is a separate point, completely outside LRMI's scope and domain.

Nevertheless, if Badges are to be accepted and adopted by the world, this is clearly a problem. Credibility could be addressed at the OBI level, or as some very knowledgeable posters suggested on the LRMI Google Group, there are already some players in the ecosystem involved in crowdsourcing this task, such as the Learning Registry or the Open Educational Resources Commons. DML projects such as LevelUp have already begun thinking through similar functionality for Badges and badged content.

Tackling credibility full-on may be a problem for another day, but it must be addressed before the system can expect adoption on any large scale.

 

Summary

The success of Open Badges at communicating the value of skills throughout a large ecosystem requires a common language about which skills a badge claims to represent. LRMI is a data format that enables this communication on a technical level, while leaving the definition of the skills to Standards framework makers, and the selection of alignment claims to the content creator or badge issuer.

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1 comment

Thanks for moving our thinking forward on this, Ross. Laying the groundwork for this will benefit everyone, and make the ecosystem stronger.

Another resource on this topic is Peter Rawsthorne's post on Open Badges, LRMI, and OER

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