So, what do we gain by talking about 'probes', and how might it help us understand the 'new-open' / emergent learning, and help us understand how we create / design / curate emergent learning spaces?

A synopsis of a probe (masquerading as a definition) might look something like this:

  • Probes are "experimental tools / ideas / interactive affordances; uncertain, tentative, interventions, that are inserted-and-let-loose within an emergent event", to see what happens (from elsewhere in this wiki, but it's directly in line with Snowden's practice, and writing).

  • Probes, specifically, respect (and assume) the unpredictable nature of a learning event, and the autonomous agency of the participants, and celebrate creative, surprising, unforeseen outcomes.

This is an odd, or certainly a different kind of 'definition', as:

1. The intention is not to pin down, narrow down the key factors into a 'testable' hypothesis, or an 'independent variable', but to try to sketch out some broader, and rather open, rules of engagement for creating, designing, using, rehashing, etc, probes.

2. It follows from this that the outcome of 'releasing' a probe is not a set of rules about predictable relationships, but rather a set of descriptions about unpredictable relationships that might nevertheless indicate an emerging pattern (or two - for a while).

3. It includes a rather odd concept, "respect" (for emergence and for the autonomy of participants' agency), which means that it includes (rather than excludes) specific contexts and specific people and their subjective attitudes - quite the contrary to what we have come to regard as the only, 'normal', 'scientific', and 'objective' attitude to the concerns of research.

4. However, this is not a manifesto for subjective research, but rather a plea for recognising that we need to be able to research complex-adaptive, emergent, events with the appropriate concepts, tools, methodologies, and attitudes, which are different from hypothetical-deductive research, and are equally valid, 'objectively' (which is its own little paradox!).

Probes are at the heart of what I would call 'open learning spaces'. But as Cilliers reminds us, there is no emergence without constraint - the question is, what is the appropriate balance between openness and constraint? - and this question cannot be answered before-hand, you have to 'run' the event (as a probe, or with the addition of further probes) first, and only then can you track it, describe it, and answer this question. 'Complex' events are, by definition, unpredictable (in complexity theory / chaos theory), including events governed by some very simple algorithms (like the graphic 'Game of Life').

And, for a fuller discussion, with some examples, see the recent paper, here