(22nd in my logic of competence series.)

There has been much discussion recently about Mozilla Open Badges, xAPI (Experience API, alias “Tin Can API“) and LRMI, as new and interesting specifications to help bring standardization particularly into the world of technology and resources involved with people and their learning. They have all reached their “version 1″ this year, along with InLOC.

InLOC can quietly serve as a cornerstone of all three, providing a specification for one of the important things they may all want to refer to. InLOC allows documentation of the frameworks, of learning outcomes, competencies, abilities, whatever you call them, that describe what people need to know and be able to do.

Mozilla has been given, and devoted, plenty of resource to their OpenBadges effort, and as a result is it widely known about, though not so well known is the rapid and impressive development of the actual specification. The key part of the spec is how OpenBadges represents the “assertions” that someone has achieved something. The thing that people achieve (rather that its achievement) could well be represented in an InLOC framework.

Tin Can / Experience API (I’ll use the customary abbreviation “xAPI”) has also been talked about widely, as a successor to SCORM. The xAPI “makes it possible to collect the data about the wide range of experiences a person has (online and offline)”. This clearly includes “experiences” such as completing a task or attaining a learning outcome. But xAPI does not deal with the relationships between these. If one greater learning outcome was composed of several lesser ones, it wouldn’t be natural to represent that fact in xAPI itself. That is where InLOC naturally comes in.

LRMI (“Learning Resource Metadata Initiative”) is, as one would expect, designed to help represent metadata about learning resources, in a way that is integrated with schema.org. What if many of those learning resources are designed to help a learner achieve an intended learning outcome? LRMI can naturally refer to such a learning outcome, but is not designed to represent the structures themselves. Again, InLOC can do that.

What would be chaotic would be if these three specifications, each one potentially very useful in its own way, all specified their own, possibly incompatible ways of representing the structures or frameworks that are often created to bring common ground and order to this whole area of life.

Please don’t let that happen! Instead, I believe we should be using InLOC for what it is good at, leaving each other spec to handle its own area, and no one shamefully “reinventing the wheel”.

Draft proposals

These proposals are only initial proposals at present, looking forward to discussion with other people involved with or interested in the other three specifications. Please don’t hesitate to suggest better ways if you can see them.

OpenBadges

The Assertions page gives the necessary detail of how the OpenBadges spec works.

• The BadgeClass criteria property means the “URL of the criteria for earning the achievement.” If there is an InLOC LOCdefinition or LOCstructure that represents these criteria, as there could well be, then the natural mapping would be for the criteria property simply to hold the URI, either of the (single) LOCdefinition, or of the LOCstructure that comprises all of the definitions together.
• The BadgeClass alignment property gives a list of “objects describing which educational standards this badge aligns to, if any.” In cases where there is no LOCdefinition or LOCstructure representing the whole of the badge criteria, it seems natural to put a set of LOCdefinition URIs into the (multiple) objects of this property — which are AlignmentObjects.
• Each AlignmentObject has the following properties, which map directly onto InLOC.
  • name: this could be the title of a LOCdefinition
  • url: this could be the id of the same LOCdefinition
  • description: this could be the description of the same LOCdefinition

One could also potentially take both approaches at the same time.

I will record more detail, and change it as it evolves, on the InLOC wiki.

xAPI

The developers call this the Tin Can API, but their sponsors, ADL, call it the Experience API or xAPI.

The specification (v1.0.1, 2013-10-01) can be read in this PDF document.

Tin Can is based around the statement. This is defined as “a simple construct consisting of <actor (learner)> <verb> <object>, with <result>, in <context> to track an aspect of a learning experience.” There are a number of ways in which a statement could relate to a learning outcome or competence. How might these correspond to InLOC?

1. If the statement “verb” is something like completed, or mastered, or passed, the “object” could well be something like a learning outcome, or an assessment directly related to a learning outcome. The object has two properties on top of the expected objectType:
   • id: this can be the same as a LOC id in InLOC
   • definition: this in turn has recommended properties of:
     1. name: this is proposed as the LOC title
     2. description: this is proposed as the LOC description
     3. type: this is proposed as the URI for LOCdefinition or LOCstructure
2. The statement could be that some experiences were had (e.g. an apprenticeship), and the result was the learning outcome or competence. It might therefore be useful to give the URI of an InLOC-formatted learning outcome as part of an xAPI result. Unfortunately, none of the specified properties of the Result object have a URI type, so the URI of a LOC definition would have to go in the extensions property of the result.
3. Often in personal or professional development planning, it is useful to record what is planned. An example of how to represent this, with the object as a sub-statement, is given in the spec section 4.1.4.3, page numbered 20. The sub-statement can be something similar to the first option above.
4. A learning outcome may form part of the context of an activity in diverse ways. If it is not one of the above, it may be possible to use the context property of a statement, either as a statement reference in the statement property of the context, or as part of the context‘s extensions.

In essence, the clearest and most straightforward way of linking to an InLOC LOCstructure or LOCdefinition is as a statement object, rather than its result or context. The other options could be seen as giving too many options, which may lead away from useful interoperability.

I will record more detail, and change it as it evolves, on the InLOC wiki.

LRMI

The documentation for the Learning Resource Metadata Initiative is at http://www.lrmi.net/. The specification, and its correspondence with InLOC, is very simple. All the properties are naturally understood as properties of a learning resource. The property relevant to InLOC is educationalAlignment, whose object is an AlignmentObject.

Here, the LRMI AlignmentObject properties are mapped to LOCdefinition properties.

• targetURL: LOCdefinition id
• targetName: LOCdefinition title
• targetDescription: LOCdefinition description

I will record more detail, and change it as it evolves, on the InLOC wiki.

What this all means

xAPI and LRMI

The implications for xAPI and LRMI are just that they could suggest InLOC as a possible format for the publication of frameworks that they may want to refer to. Neither spec has pretensions to cover this area of frameworks, and the existence of InLOC should help to prevent people inventing diverse solutions, when we really want one standard approach to help interoperability.

A question remains about what a suitable binding of InLOC would be for both specs. In many ways it should not matter, as it will be the URIs and some values that will be used for reference from xAPI and LRMI, not any of the InLOC syntax. However, it might be useful to remember that xAPI’s native language is JSON, and LRMI’s is HTML, with added schema.org markup using microdata or RDFa. Neither of these bindings has been finalised for InLOC, so an opportunity exists to ensure that suitable bindings are agreed, while still conforming to the InLOC information model in one or other form.

OpenBadges

The case of Mozilla Open Badges is perhaps the most interesting. Clearly, there is a potential interest for badges to link to representations of learning outcomes or competences as defined by relevant authorities. It is so much more powerful when these representations reside in a common space that can be referred to by anyone (including e.g. xAPI and LRMI users, personal development, portfolio, and recruitment systems). It is easy to see how badges could usefully become “metadata-infused” tokens of the achievement of something that is already defined elsewhere. Redefining those things would simply confuse people.

InLOC solves several problems that OpenBadges should not have to worry about. One is representing equivalence (or not) between different competencies. That is provided for straightforwardly within InLOC, and should be done by the authorities defining the competencies, whether or not they are the same people as those who define and issue the badges.

Second, InLOC gives a clear, comprehensive and predefined vocabulary for how different competencies relate to each other. Mozilla’s Web Literacy Standard defines a tree structure of “literacies”, “competencies” and “skills”. Other frameworks and standards use other terms and concepts. InLOC is generic enough to represent all the relationships in all of these structures. As with equivalencies, the badge issuer should not have to define, for example, what roles require what skills and what knowledge. That should be up to occupational domain experts.

But OpenBadges do require some way to represent the fact that one, greater, badge can stand for a number of lesser badges. This is necessary to avoid being drowned in a flood of badges each one so small that it is unrecognisable or insignificant.

While so many frameworks have not been expressed in a machine processable format like InLOC, there will remain a requirement for an internal mechanism within OpenBadges to specify precisely which set of lesser badges is represented by a single a greater badge. But when the InLOC structures are in place, and all the OpenBadges in question refer to InLOC URIs for their criteria, we can look forward to automatic consistency checking of super-badges. To check a greater badge with a set of lesser component badges, check that the criteria structure or definition for the greater badge has parts (as defined by InLOC relationships) which are each the criteria of one of the set of lesser badges.

As with xAPI, JSON is the native language of OpenBadges, so one task that remains to be completed is to ensure that there is a JSON binding of InLOC that satisfies both the OpenBadges and the Tin Can communities.

That should be it! Is it?