(23rd in my logic of competence series.)

InLOC is well designed to provide the conceptual “glue” or “thread” for holding together structures and planned pathways of achievement, which can be represented by Mozilla OpenBadges.

Since my last post — the last of the previous academic year, also about OpenBadges and InLOC — I have been invited to talk at OBSEG – the Open Badges in Scottish Education Group. This is a great opportunity, because it involves engaging with a community with real aspirations for using Open Badges. One of the things that interests people in OBSEG is setting up combinations of lesser badges, or pathways for several lesser badges to build up to greater badges. I imagine that if badges are set up in this way, the lesser badges are likely to become the stepping stones along the pathway, while it is the greater badge that is likely to be of direct interest to, e.g., employers.

All this is right in the main stream of what InLOC addresses. Remember that, using InLOC, one can set out and publish a structure or framework of learning outcomes, competenc(i)es, etc., (called “LOC definitions”) each one with its own URL (or IRI, to be technically correct), with all the relationships between them set out clearly (as part of the “LOC structure”).

The way in which these Scottish colleagues have been thinking of their badges brings home another key point to put the use of InLOC into perspective. As with so many certificates, awards, qualifications etc., part of the achievement is completion in compliance with the constraints or conditions set out. These are likely not to be learning outcomes or competences in their own right.

The simplest of these non-learning-outcome criteria could be attendance. Attendance, you might say, stands in for some kind of competence; but the kind of basic timekeeping and personal organisation ability that is evidenced by attendance is very common in many activities, so is unlikely to be significant in the context of a Badge awarded for something else. Other such criteria could be grouped together under “ability to follow instructions” or something similar. A different kind of criterion could be the kinds of character “traits” that are not expected to be learned. A person could be expected to be cheerful; respectful; tall; good-looking; or a host of other things not directly under their control, and either difficult or impossible to learn. These non learning outcome aspects of criteria are not what InLOC is principally designed for.

Also, over the summer, Mozilla’s Web Literacy Standard (“WebLitStd”) has been progressing towards version 1.0, to be featured in the upcoming MozFest in London. I have been tracking this with the help of Doug Belshaw, who after great success as an Open Badges evangelist has been focusing on the WebLitStd as its main protagonist. I’m hoping soon (hopefully by MozFest time) to have a version of the WebLitStd in InLOC, and this brings to the fore another very pragmatic question about using InLOC as a representation.

Many posts ago, I was drawing out the distinction between LOC (that is, Learning Outcome or Competence) definitions that are, on the one hand, “binary”, and on the other hand, “rankable”. This is written up in the InLOC documentation. “Binary” ones are the ones for which you can say, without further ado, that someone has achieved this learning outcome, or not yet achieved it. “Rankable” ones are ones where you can put people in order of their ability or competence, but there is no single set of criteria distinguishing two categories that one could call “achieved” and “not yet achieved”.

In the WebLitStd, it is probably fair to say that none of the “competencies” are binary in these terms. One could perhaps characterise them as rankable, though perhaps not fully, in that there may be two people with different configurations of that competency, as a result perhaps of different experiences, each of whom were better in some ways than the other, and each conversely less good in other ways. It may well be similar in some of the Scottish work, or indeed in many other Badge criteria. So what to do for InLOC?

If we recognise a situation where the idea is to issue a badge for an achievement that is clearly not a binary learning outcome, we can outline a few stages of development of their frameworks, which would result in a progressively tighter matching to an InLOC structure or InLOC definitions. I’ll take the WebLitStd as illustrative material here.

First, someone may develop a badge for something that is not yet well-defined anywhere — it could have been conceived without reference to any existing standards. To illustrate this case, an example of a title could be “using Web sites”. There is no one component of the WebLitStd that covers “using the web”, and yet “using” it doesn’t really cover Web literacy as a whole. In this case, the Badge criteria would need to be detailed by the Badge awarder, specifically for that badge. What can still be done within OpenBadges is that there could be alignment information; however it is not always entirely clear what the relationship is meant to be between a badge and a standard it is “aligned” to. The simplest possibility is that the alignment is to some kind of educational level. Beyond this it gets trickier.

A second possibility for a single badge would be to refer to an existing “rankable” definition. For example, consider the WebLitStd skill, “co-creating web resources”, which is part of the “sharing & collaborating” competency of the “Connecting” strand. To think in detail about how this kind of thing could be badged, we need to understand what would count (in the eye of the badge issuer) as “co-creating web resources”. There are very many possible examples that readily come to mind, from talking about what a web page could have on it, to playing a vital part in a team building a sophisticated web service. One may well ask, “what experiences do you have of co-creating web resources?” and, depending on the answer, one could roughly rank people in some kind of order of amount and depth of experience in this area. To create a meaningful badge, a more clearly cut line needs to be drawn. Just talking about what could be on a web page is probably not going to be very significant for anyone, as it is an extremely common experience. So what counts as significant? It depends on the badge issuer, of course, and to make a meaningful badge, the badge issuer will need to define what the criteria are for the badges to be issued.

A third and final stage, ideal for InLOC, would be if a badge is awarded with clearly binary criteria. In this case there is nothing standing in the way of having the criteria property of the Badge holding a URL for a concept directly represented as a binary InLOC LOCdefinition. There are some WebLitStd skills that could fairly easily be seen as binary. Take “distinguishing between open and closed licensing” as an example. You show people some licenses; either they correctly identify the open ones or they don’t. That’s (reasonably) clear cut. Or take “understanding and labeling the Web stack”. Given a clear definition of what the “Web stack” is, this appears to be a fairly clear-cut matter of understanding and memory.

Working back again, we can see that in the third stage, a Badge can have criteria (not just alignments) which refer directly to InLOC information. At the second and first stage, badge criteria need something more than is clearly set out in InLOC information already published elsewhere. So the options appear to be:

1. describing what the criteria are in plain text, with reference to InLOC information only through alignment; and
2. defining an InLOC structure specifically for the badge, detailing the criteria.

The first of these options has its own challenges. It will be vital to coherence to ensure that the alignments are consistent with each other. This will be possible, for example, if the aspects of competence covered are separate (independent; orthogonal even). So, if one alignment is to a level, and the second to a topic area, that might work. But it is much less promising if more specific definitions are referred to.

(I’d like to write an example at this point, but can’t decide on a topic area — I need someone to give me their example and we can discuss it and maybe put it here.)

From the point of view of InLOC, the second option is much more attractive. In principle, any badge criteria could be analysed in sufficient detail to draw out the components which can realistically be thought of as learning outcomes — properties of the learners — that may be knowledge, skill, competence, etc. No matter how unusual or complex these are, they can in principle be expressed in InLOC form, and that will clarify what is really “aligned” with what.

I’ll say again, I would really like to have some well-worked-out examples here. So please, if you’re interested, get in touch and let’s talk through some of interest to you. I hope to be starting that in Glasgow this week.