So I was reading something that talked about designed versus emergent experiences. Certainly we have familiarity with designed experiences: courses/training, film, theater, amusement parks. Yet emergent experiences seem like they’d have some unique outcomes and consequently could be more valuable and memorable. So I wondered how an emergent experience might play out to reliably generate a good experience, regardless.
The issue is that designed experiences, e.g. a Disney ride, are predictable. You can repeat them and notice new things, yet the experience is largely the same. And there can be brilliant minds behind them, and great outcomes including learning. But could and should we shoot higher?
What emergent experiences do we know? Emergent means having to interact with something unpredictable and perhaps even reactive. It could be interacting with systems, or it could be interpersonal interaction. So, what we see in clouds, and experiences we have with games, and certainly interpersonal experiences can be emergent. Can they repeatedly have desired outcomes as well as unpredictable ones?
I think the answer is yes if you allow for the role of some ‘interference’. That is, someone playing a role in controlling the outcomes. This is what happens in Dungeons and Dragons games where there is a Dungeon Master, or in Alternate Reality Game where there’s a Puppet Master, or in social learning where an instructor is structuring group assignments.
I’m interested in the latter, and the blend between. I propose that our desired learning experiences should go beyond fixed designs, as our limitations as designers and SMEs will constrain what outcomes we achieve. They may be good, but what can happen when people interact with each other, and rich systems, allows for more self discovery and ownership. An alternative to social interaction would be practice set in a simulation that’s richer and with some randomness that mimics the variations seen in the real world that go beyond our specific designs.
By creating this richness through interpersonal interaction via dialogue and different viewpoints, or through simulations, we create experiences that go beyond our limitations in specific design. It certainly may go beyond our resources: branching scenarios and asynchronous independent learning are understandably more pragmatic, but when we can, and when the learning outcomes we need are richer than we can suitably address in a direct fashion, say when we need flexible adaptation to circumstances, we should consider designing emergent experiences. And I’m inclined to think that social learning is the cheaper way to go than a complex system-generated experience.
I’m just thinking out loud here, a tangent sparked by a juxtaposition, part of my ongoing efforts to make sense of the world and apply that to creating more resilient and successful organizations. Based upon the above, I think emergent experiences can create more adaptable and flexible learning, and I think that’s increasingly needed. I welcome your thoughts, reflections, pointers, disagreements, and more.
For me, at both levels; the one in which one is attaining an experience, and for the society within which any experience takes place, all’experience is emergent, In contrast, non-emergent efforts at intentionally directing experiences for others are made all the time, And all collective-group instructional education falls in this forced interaction. This is true even in the purely experiential-based, direct inquiry context of a master-apprentice learning relationship (though I do think this guild -style learning construct a better than collective-group education e.g. “the schools”), No intentionally directed learning effort has seemed optimal to me, Instead, I have come to believe that ‘only self-directed learning,’ informed by any source, including any instructional artifacts, that challenge, reinforce, or split previously held conceptual constructs for learners, may be a true, natural and systemic means/mechanism for learning to occur/advance. IMHO, only self-directed learning is truly optimal learning.