{"id":4512,"date":"2016-01-23T14:23:55","date_gmt":"2016-01-23T13:23:55","guid":{"rendered":"http:\/\/www.saasoft.com\/blog\/?p=4512"},"modified":"2016-01-23T14:23:55","modified_gmt":"2016-01-23T13:23:55","slug":"emergent-learning","status":"publish","type":"post","link":"https:\/\/hcse.blog\/?p=4512","title":{"rendered":"Emergent Learning"},"content":{"rendered":"

\"CAS_Diagram\"<\/a>The theme this week has been emergent learning<\/em>.<\/p>\n

By that I mean the ‘ah ha’ moment that happens when lots of bits of a conceptual jigsaw go ‘click’ and fall into place.<\/p>\n

When, what initially appears to be smoky confusion\u00a0suddenly\u00a0snaps into\u00a0sharp clarity.\u00a0 Eureka!\u00a0 <\/em>And now new\u00a0learning can emerge.<\/p>\n

\n

This did not happen by accident.\u00a0 It was engineered.<\/p>\n

\n

The picture above is part of a bigger schematic map of a system – in this case a system related to the\u00a0global health\u00a0challenge of\u00a0escalating obesity.<\/p>\n

It is a complicated arrangement of\u00a0boxes and arrows. There are\u00a0 dotted lines that outline parts of the system\u00a0that have\u00a0leaky boundaries like the borders on a\u00a0political map.<\/p>\n

But it is a static picture of the structure … it tells us almost nothing about the function, the system\u00a0behaviour.<\/p>\n

And\u00a0our intuition\u00a0tells us\u00a0that, because it\u00a0is a complicated structure, it will exhibit complex and difficult\u00a0to understand behaviour.\u00a0 So, guided by our inner voice,\u00a0we\u00a0toss\u00a0it into the pile labelled\u00a0Wicked Problems<\/em> and look for something easier to work on.<\/p>\n

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Our\u00a0natural assumption that a complicated structure always<\/em> leads to complex behavior is an invalid simplification, and one\u00a0that we can disprove\u00a0in a matter of moments.<\/p>\n

\n

Exhibit 1. A\u00a0system can be complicated and yet still exhibit simple, stable and predictable behavior.<\/em><\/p>\n

\"Harrison_H1\"<\/a>The picture is of a clock designed and built by John Harrison (1693-1776).<\/a>\u00a0 It is\u00a0called H1 and it is a sea clock.<\/p>\n

Masters of sailing ships required\u00a0very accurate clocks to calculate their longitude,\u00a0the East-West coordinate on the\u00a0Earth’s surface. And in the 18th Century this was a BIG problem. Too many ships were getting lost at sea.<\/p>\n

Harrison’s sea clock is complicated.\u00a0 It has many moving parts,\u00a0but it was the most stable and accurate clock of its time.\u00a0 And his later ones were smaller, more accurate and even more complicated.<\/p>\n

\n

Exhibit 2.\u00a0 A system can be simple yet still exhibit complex, unstable and unpredictable behavior.<\/em><\/p>\n

\"Double-compound-pendulum\"<\/a>The image is of a pendulum made of\u00a0only two rods joined by a hinge.\u00a0 The structure is simple yet the behavior\u00a0is complex, and this can only be appreciated with a dynamic visualisation.<\/p>\n

The behaviour is clearly not random. It has an emergent structure.\u00a0It is called chaotic<\/em>.<\/p>\n

So, with these two real examples we\u00a0have disproved\u00a0our\u00a0assumption that a complicated structure always<\/strong> leads to complex behaviour; and we have\u00a0also disproved its inverse … that complex behavior always<\/strong> comes from a complicated structure.<\/p>\n

The cognitive trap we have exposed here is over-generalisation,\u00a0<\/em>the unconscious habit of slipping in the implied [always].<\/p>\n

\n

This deeper understanding gives us hope.<\/p>\n

John Harrison was a rare, naturally-gifted,\u00a0mechanical genius.\u00a0 And to make it easier, he was working on a purely mechanical system comprised of non-living parts that only obeyed the Laws of Newtonian physics.\u00a0 And even with those advantages it took him decades to learn how to design and to build his sea clocks.\u00a0 He was the first to do so and he was self-educated so his learning was emergent.<\/p>\n

If there were a way to design complicated systems to exhibit stable and predictable behaviour, how could more of us learn how to do that?<\/p>\n

\n

Our\u00a0healthcare system is not made of passive, mechanical cogs and springs.\u00a0 The parts are active, living people whose actions are limited\u00a0by physical Laws\u00a0but whose decisions are\u00a0steered\u00a0by other\u00a0policies … learned ones … and ones that can change.\u00a0 These learned rules of thumb are called heuristics<\/em> and they vary from person-to-person and from minute-to-minute.\u00a0 Heuristics\u00a0can be learned, unlearned, updated, and evolved.<\/p>\n

This\u00a0is called emergent learning<\/em>.<\/p>\n

And to generate it we only need to create the context for it …\u00a0the rest happens … as if by magic … but only if we design a fit-for-purpose context.<\/p>\n

\n

This week I personally observed\u00a0over a dozen healthcare staff simultaneously re-invent a complicated process scheduling technique, at the same time as\u00a0using it to eliminate the\u00a0 queues, waiting and chaos in the system they wanted to improve.<\/p>\n

Their\u00a0queues just evaporated … without requiring any extra capacity or money.\u00a0Eureka!<\/em><\/p>\n

\n

We\u00a0did not\u00a0show them how to do it so they could not have just copied what\u00a0we did.<\/p>\n

We designed and built the context for their learning to emerge … and it did.\u00a0 On its own.<\/p>\n

The One Day Practical Skills Workshop<\/a> delivered\u00a0emergent learning … just as it was\u00a0designed to do.<\/p>\n

A health care system is a complex adaptive system<\/a> (CAS), and system improvement-by-design is what systems engineers (SE) are trained to do.<\/p>\n

And this emerging style of\u00a0complex adaptive systems engineering\u00a0(CASE)\u00a0<\/em>is at the cutting edge of human knowledge, and when applied in the health care domain it is called health care systems engineering<\/a> (HCSE).<\/p>\n

Our experience of the emergent learning that flows from the practical skills workshops verifies that CASE is both possible,\u00a0learnable, teachable, applicable and effective.<\/p>\n","protected":false},"excerpt":{"rendered":"

The theme this week has been emergent learning. By that I mean the ‘ah ha’ moment that happens when lots of bits of a conceptual jigsaw go ‘click’ and fall into place. When, what initially appears to be smoky confusion\u00a0suddenly\u00a0snaps into\u00a0sharp clarity.\u00a0 Eureka!\u00a0 And now new\u00a0learning can emerge. This did not happen by accident.\u00a0 It … <\/p>\n

Continue reading “Emergent Learning”<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6,14,15,22,24,26,40,46],"tags":[],"class_list":["post-4512","post","type-post","status-publish","format-standard","hentry","category-6m-design","category-delivery","category-design","category-healthcare","category-improvementology","category-isp","category-sfqp","category-teach"],"_links":{"self":[{"href":"https:\/\/hcse.blog\/index.php?rest_route=\/wp\/v2\/posts\/4512","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hcse.blog\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hcse.blog\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hcse.blog\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/hcse.blog\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=4512"}],"version-history":[{"count":0,"href":"https:\/\/hcse.blog\/index.php?rest_route=\/wp\/v2\/posts\/4512\/revisions"}],"wp:attachment":[{"href":"https:\/\/hcse.blog\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=4512"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hcse.blog\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=4512"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hcse.blog\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=4512"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}