Learning

Learning

mapping healthcare

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This past year my wife and I have spent a fair bit of time in hospitals and doctors’ offices, helping friends navigate the healthcare system. One thing we have noticed is the siloed nature of medicine here.

When you get limited time with a healthcare professional and they have limited time to get up to date on the patient, a lot of information and context slips through the cracks. Add in the fact that many of these professionals do not regularly communicate with each other, and the patient becomes responsible for closing these gaps. This is impossible with patients suffering from dementia or other cognitive challenges.

In addition, many family members do not know what information is important and are not able to be effective patient advocates. For example, some information — such as the recent death of a spouse — does not get transmitted and the physician’s diagnosis is based only on the visible symptoms as presented at the time.

This example reminded me of a project we did for a healthcare client in 2004. We conducted an elearning and community of practice initiative for a hospital system as part of the transition to a new nursing care model — from the Henderson to the McGill model. The Province of Québec (healthcare is the responsibility of each Province in Canada) was moving from a patient-centric to a learning-centric nursing framework. As part of our project, we developed software for visual mapping to support the standard patient charts and records. The software was used to create visual models of the patient’s family (genogram) and the patient’s community relationships (ecomap).

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reflecting on the future of knowledge

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I started my independent consulting practice in 2003 and one of the first books I purchased was — The Future of Knowledge: Increasing Prosperity through Value Networks by Verna Allee (2002) Butterworth-Heinemann (ISBN: 0750675918). The topic of value network analysis and the leading role that Verna Allee played came up in some recent discussions in one of my online communities of practice. So I decided to re-read the book that planted so many ideas in my mind. Here are some of the highlights, almost 20 years after Verna started writing The Future of Knowledge.

LESS COLLECTION, MORE CONNECTION

One of the primary requirements for supporting knowledge work is to ensure that people have the tools and information they need to complete their everyday tasks. But, another equally important goal is to provide appropriate technologies for collaborative work in a complex global environment. The more complex modes of knowledge cannot be turned over to databases and automation. They are accomplished by people through active and immediate conversation and interchanges. Connective technologies enable us to link up with our peers so that we may weave the threads of our understanding together into new synthesis and insights.

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making time for learning

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For over a decade I have promoted the idea that work is learning & learning is the work. It seems the idea has now gone mainstream, as it’s even noted in Forbes that, “Work and learning will become analogous”. It is much easier to just say that workflow learning is essential rather than putting in the structures and practices that can enable it. There are many structural barriers to learning in the workplace that have been established and embedded over the past century.

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from training to learning

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While social learning may be one of the currently hot new trends in the education and training fields, we have known for a while “why tried-and-true training methods don’t work anymore”, as discussed by Brigitte Jordan (1937-2016) in the mid-1990’s while working at the Institute for Research on Learning. Here are the highlights — From Training to Learning in the New Economy.

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connecting the curious

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Why do students often ask — will this be on the test? It’s because they have figured out the game called education. They are told what to study, what is important, and for how long. Each school year they play the game anew.

Why are some — a significant percentage — employees not motivated to work? They too have figured out the game. Venkatesh Rao, in The Gervais Principle describes this large base of most companies — the losers.

“The Losers are not social losers (as in the opposite of ‘cool’), but people who have struck bad bargains economically – giving up capitalist striving for steady paychecks. I am not making this connection up … The Losers like to feel good about their lives. They are the happiness seekers, rather than will-to-power players, and enter and exit reactively, in response to the meta-Darwinian trends in the economy. But they have no more loyalty to the firm than the Sociopaths. They do have a loyalty to individual people, and a commitment to finding fulfillment through work when they can, and coasting when they cannot.”

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we are dependent on human connection

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What we do not know

Our networks are great places for serendipitous connections. But they are not safe places to have deeper conversations or to expose our points of view, I noted last year in coffee, communities, and condescension. The difference between an open social network (e.g. Twitter) and a private online community (e.g. Mattermost) is that the latter is often based on mutual trust. While community members may disagree, they respect each other. They are not shaming people in public, as happens frequently on Twitter with its loose social ties.

To make sense of our complex world and its often-veiled media sources, we need both open social networks and more closed communities of practice/interest. Sensemaking is an ongoing process and highly dependent on our human connections. Only collectively can we confront the post-truth machines of the network era.

The Dunning-Kruger Effect is the tendency of people who know less about a topic to think that they know more. This cognitive bias comes from people’s “inability to recognize their lack of ability”. The counter to this bias is metacognition — the ability to think about our own thinking processes — and is humanity’s secret weapon that too few of us use. Another counter is to connect to other people with diverging experiences and interests. The more diverse our social networks, the more diverse our thinking can be.

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systems thinking and training

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Continued from — just checking the box

Boeing 737 MAX

I read an article in New Republic entitled Crash Course by Maureen Tkacic, a former Wall Street Journal reporter, which describes how “Boeing’s managerial revolution created the 737 MAX disaster” — resulting in plane crashes in Indonesia and Ethiopia.

In the now infamous debacle of the Boeing 737 MAX, the company produced a plane outfitted with a half-assed bit of software programmed to override all pilot input and nosedive when a little vane on the side of the fuselage told it the nose was pitching up. The vane was also not terribly reliable, possibly due to assembly line lapses reported by a whistle-blower, and when the plane processed the bad data it received, it promptly dove into the sea.

In the article by Tkacic, all the blame is on Boeing.

The upshot was that Boeing had not only outfitted the MAX with a deadly piece of software; it had also taken the additional step of instructing pilots to respond to an erroneous activation of the software by literally attempting the impossible. MCAS alone had taken twelve minutes to down Lion Air 610; in the Ethiopian crash, the MCAS software, overridden by pilots hitting the cutout switches as per Boeing’s instructions, had cut that time line in half. Lemme had seen a lot of stupidity from his old employer over the years, but he found this whole mess “frankly stunning.”

When I shared this article on Twitter, Jim Hays referred me to another article in the New York Times by William Langewiesche, an experienced pilot and aviation journalist who has written technical reports on the flight characteristics of various airplanes. It is entitled — What really brought down the Boeing 737 Max?

Note: I am only comparing these two articles, not making my own uneducated investigation into this aircraft.

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range & inefficiency

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An innovation system should preserve range and inefficiency, concludes the book Range—Why generalists triumph in a specialized world, by David Epstein. Focusing deep yields efficiencies and incremental innovation. But a broad base of learning and experience can produce radical innovation. Many (most?) of our research and education practices are designed for ‘kind’ environments where the rules and parameters are relatively clear. Playing chess is one example. But the world, and most fields of human endeavour are complex, or ‘wicked’. “In wicked domains, the rules of the game are often unclear or incomplete, there may or may not be repetitive patterns and they may not be obvious, and feedback is often delayed, inaccurate, or both.” When faced with new and complex challenges, we cannot rely on learning from experience, as we have none.

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adding value with teams

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In working collaboratively & learning cooperatively I noted that team collaboration requires the transparent sharing of knowledge — using enterprise social networks and other technologies — so that everyone on a team knows what is going on and why. Decisions, and why they were made, are shared. New processes and methods are co-developed to create emergent practices. This method of work has to be supported by management by enabling — innovative and contextual methods, the self-selection of the most appropriate tools and work conditions, and willing cooperation between workers.

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top tools 2019

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Since 2007 Jane Hart has asked working professionals for their top tools for learning — TopTools4Learning — and creates three lists from thousands of responses.

  1. Top 100 Tools for Personal & Professional Learning
  2. Top 100 Tools for Workplace Learning
  3. Top 100 Tools for Education

Work is learning, and learning is the work, so here are my  top 10 tools for work & learning.

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