SocialLearning

Social learning

All things to all people

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It was reported that only 2% of social sharing happens on Google Plus (G+). I too, do not share much on G+. I recently posted on G+ that it did not fit in with my professional use of social media, even though discussions are often fun, interesting, and informative. That G+ post I made now has 52 comments, more than any post on this blog has had.

In that post, Jeff Roach described G+ as “a network that looks like Facebook (media rich) but functions more like twitter (streams etc) but is more friendly to conversations and sharing than both of them.” Joachim Stroh suggested that I create a community on G+ but I countered that I preferred to cooperate in the open, not in another social media walled garden:

I think one of the problems today is that many online social networks are trying to be communities of practice. But to be a community of practice, there has to be something to practice. One social network, mine, is enough for me. How I manage the connections is also up to me. In some cases I will follow a blogger, in others I will connect via Google Plus or Twitter, but from my perspective it is one network, with varying types of connections. Jumping into someone else’s bounded social network/community only makes sense if I have an objective. If not, I’ll keep cooperating out in the open.

Nollind Whachel then weighed-in with several thoughtful comments and Joachim Stroh continued to engage. I stood on the sidelines, and a few others added comments, including one commentator unknown to me who felt I was being unprofessional because I did not understand G+. By the way, all of my G+ posts have been public, so anyone can jump in.

Nollind provided a good way to describe the sense-making process in these online social networks:

Connect = producing content
Empower = making sense of content patterns
Inspire = leap of logic, the patterns form a story, you see the bigger picture

Joachim made an interesting subsequent comment:

So, I’m still looking for the connection to go from unstructured to structured content, without doing a lot of curation. It’s not easy if you are doing this on your own (as you describe), it’s almost impossible to do this collectively (without a CM role).

Nollind added an emergent thought, that I think is important, and is partially what this blog post is all about:

Hmm, just had an interesting thought. It actually may be easier to do the writing and sense making within one community and then do the outlining and structuring in another community.

My interest in all of this comes down to PKM, and so far, G+ is a mere extension of my PKM processes. Perhaps it could be more, but I strongly believe in the centrality of my blog, which I own and control. I am not ready to give that to Google or any other third party. Nollind also made an excellent comparison of my PKM framework with his own methodology,

Seek = Connect = Play
Sense = Empower = Learn
Share = Inspire = Work

At this time, G+ provides a nice place for deep discussions with people who probably would not post as much on my blog and would be throttled by Twitter’s 140 character limit. I know that others use it much more, adding tags to make search and retrieval easier, and engaging with communities. G+ does add to my weak & diverse ties and even enables the sharing of complex knowledge. Perhaps G+ is trying to be all things to all people, and for those of us with existing PKM processes, that’s just too much.

social ties collaboration cooperationImage: Social Ties for Cooperation & Collaboration

An organizational knowledge-sharing framework

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There is a lot of knowledge in an organization, some of it easy to codify (capture), and much (most) of it difficult to do so. Understanding how best to commit resources for knowledge-sharing should be in some kind of a decision-making framework that is easy for anyone to understand. This is a first attempt to do that.

[This post is a follow-up from my building institutional memory post].

Brian Gongol made an interesting observation on three categories of institutional memory. Decision memories are probably the most important, and likely the most open to rationalization in hindsight. The good decisions always seem obvious after the fact.

  • event memories, which are things like the construction of new facilities or the arrival of new employees

  • process memories, which note how things are done in order to save time and ensure their reliable repetition in the future

  • decision memories, which explain how the institution chose one path or policy or course of action over another

We can expand these three categories with Ewen La Borgne’s observation on the types of artifacts left by work projects. Outputs are quite explicit, while expertise is mostly implicit knowledge. Networks can be mapped, and are therefore explicit, but interpreting them requires implicit knowledge.

  • Information and outputs produced

  • Expertise (knowledge and know-how)

  • A network of connections

Put all of these together in order of difficulty in codifying memories/artifacts and the following graphic is my working interpretation. Explicit knowledge is easier to codify and more suitable for enterprise-wide initiatives, while implicit knowledge requires personal interpretation and engagement to make sense of it. Note that these six categories only serve as examples and are not a complete spectrum of knowledge representations.

codifying knowledge

So what types of knowledge management (KM) frameworks could help us support the codification of these knowledge artifacts? One way to look at it would be from a perspective discussed by Patti Anklam a few years back. Patti explained the differences between Big KM, Little KM and Personal KM and this distinction could be useful. Big KM is good for knowledge that can be easily codified, and Little KM can provide a structure for teams & groups to try out new things (in a Probe-Sense-Respond way). PKM puts individuals in control of their sense-making, but the organization can benefit from this by making it easier for workers to share knowledge.

structuring knowledge

Finally, there are certain types of tools and and platforms that would be more suitable for sharing of each type of knowledge artifact. I describe only a few in this image, but it gives an idea of how one could structure a full spectrum of knowledge-sharing in order to support institutional memory.

knowledge sharing

From here, one can now ask what types of platforms would help to codify and share the knowledge that is important to any organization. For larger organizations, all three types of KM are most likely necessary. Too often, Big KM is seen as sufficient, but in complex work environments, Little KM and Personal KM are also needed and should work in conjunction with Big KM. These are three important pieces, that should remain loosely joined in order for each to do what it does best.

The Storytelling Animal

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storytelling-animalIn The Storytelling Animal, Jonathan Gottschall tells us how stories make us human. The book looks at gender differences in weaving our own stories, the cultural significance of stories, and some of the science and pseudo-science on story, narration and memory. It boils down to a simple formula, says Gottschall.

Story = Character + Predicament + Attempted Extrication

This made me consider how this could be important for institutional memory. Would this be a good formula to try to capture past events from those who have experienced them? It could be, but it might be highly dependent on how much time has passed and how important accuracy is, as we are not very good at remembering, especially critical, or ‘flashbulb’, events. “Memory isn’t an outright fiction; it is merely a fictionalization“, says Gottschall.

“The signature flashbulb event of our age is 9/11, which led to a bonanza of false-memory research. The research shows two things: that people are extremely sure of their 9/11 memories and that upward of 70% of us misremember key aspects of the attacks … In one study, 73 percent of research subjects misremembered watching, horrified, as the first plane plowed into the North Tower on the morning of September 11.

The research shows that our memories get worse over time, but our stories, as we remember them, become much clearer. We have a propensity for self-delusion, something every jury member should always keep in mind. But fiction (story) is much more powerful than non-fiction. Gottschall discusses the power of Wagner’s mythology on Hitler, as well as how the book, Uncle Tom’s Cabin, influenced the 19th century anti-slavery movement.

“When we read nonfiction, we read with our shields up. We are critical and skeptical. But when we are absorbed in a story, we drop our intellectual guard. We are moved emotionally, and this seems to leave us defenseless.”

Consider the above statement and think about training. Would it not be more effective if content was developed as stories? How about knowledge management? I think stories would be most effective for new hire training. Perhaps we should focus less on instructional design or knowledge repositories. Instead, organizations could engage good story tellers. We hear a lot about the importance of curation in the digital workplace today. The best curators are also story tellers.

I enjoyed this book and learned a fair bit from it, but it is not a book that deals much with how stories can be used for KM or other organizational purposes.

Institutional Memory

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Roger Schank has several interesting articles posted on his site in the Corporate Memory section, which I decided to dive into recently.

In The Future of Knowledge Management, he says that the main problem with KM systems is that they do not copy how real people think and that unlike a person, a “KM system simply gets slower as a result of more information”. He proposes creating software scripts to organize information, but these must be capable of self-modification. I have not seen any systems that really do this well, yet. Schank concludes:

There is a lot of knowledge in an enterprise that can be used to organize new knowledge that is coming in. People understand new knowledge in terms of what they already know. A smart KM system must know a lot of about an industry and a particular enterprise before it starts up. This is hard but by no means impossible. And it is the future of software – namely software that really knows a great deal about your business.

Until these types of systems are available though, I would encourage individuals to practice personal knowledge management and use enterprise social networks to share within the organization. It may not be as elegant, but I know it can be implemented today, with existing technologies and skills that can be developed by anyone.

Algorithmic search filters that can push things out, based on certain criteria are what Schank calls “Information that Finds You”. Add geo-location and you can get immediate feedback on things around you. These exist, but take time to setup and maintain. In organizations, providing coaching and support on how to optimize our software & hardware tools (our outboard brains) is often lacking. Not only is there a need for a learning concierge but also a basic digital concierge, so that we can use our tools optimally. For instance, even doing an advanced online search query is beyond the grasp of most people on the Net.

Schank also writes about the need for a Reminding Machine, which is based on the premise that knowledge is best communicated just in time.

A reminding machine has thousands of stories from experts in various areas of life telling about important aspects of their lives that have lessons about life in them, the kind of stories you might tell to colleagues or to students … In order to build this machine it is necessary to collect people’s stories and index them according to the goals and plans that a story instantiates.

In his keynote at DARPA in 2010, Schank discusses story telling and KM in great detail. Here are some highlights

  • Stories: should be full of details but short
  • Lecture: people cannot think about what they are thinking and listen to the speaker at the same time
  • Stories, to be effective, must not be too abstract for the person listening. Listeners must be able to absorb the stories.
  • Comprehension means “mapping your stories onto my stories”. It’s difficult to communicate with someone who has different stories.
  • In good stories, we do not give answers.

There are 12 Fundamental Cognitive Processes, according to Schank:

  1. Prediction
  2. Modelling
  3. Experimentation
  4. Evaluation
  5. Diagnosis*
  6. Planning*
  7. Causation
  8. Judgement
  9. Influence
  10. Teamwork
  11. Negotiation
  12. Describing*

* These processes are what Schank calls “The Big Three”.

Several examples of the 12 processes are presented as stories in the second video of the keynote.

For anyone interested in institutional memory, story telling, or knowledge management, all four videos are well worth watching. Roger Schank concludes that the most difficult part in all of this is actually collecting the stories. The best people to collect stories from are those who are able to admit that they mismanaged, botched, or bungled something. This can be a real challenge in organizations that do not discuss failure.

Network Era Fluency

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Today, it’s all about networks, something you were most likely not taught about in school. This means that most of our education is useless in understanding the world as it currently exists. Yes, useless.

If you were raised during the past several decades you probably understand tribes and institutions. You likely heard a lot about market forces, especially in 2008. But that is a triform society. What happens as we become a quadriform society (Tribes +Institutions +Markets +Networks)?

There are some interesting things that happen when hyperlinks subvert hierarchy, as the writers of the Cluetrain Manifesto said in 1999 (that long ago). For example, United Breaks Guitars, a video that gave a whack on the side of the head to United Airlines, adversely affected United’s stock price. Wikileaks published some documents and enormous state resources were put against one person, now holed up in an embassy, at significance expense to those who pay the guards. Arab Spring became a force overnight, confusing intelligence agencies (the same ones who never saw the collapse of the Soviet bloc in advance). The Occupy movement came and some say has gone, but it’s likely a field test for more movements to come.

In education, the current subversion is called a MOOC, which has already been subverted by corporate interests, but will likely rise again in another name or form. In the labour movement we are seeing things like alt-labour as well as a growing shareable economy. CSA’s are becoming the norm. Networked, distributed businesses, like AirBNB, are disrupting existing models, with the inevitable push-back as they become successful.

Big data is also networked data. Data is the new oil, according to Gerd Leonhard. While my personal data may not be that important in the great scheme of things, networked data drive advertising, brands, and security systems. To negotiate the network era we need to understand networks – social networks, business networks, government networks, and information networks. We need network fluency.

Tony Reeves wrote a recent post about the 21st century skill set, showing that global fluency could be developed through certain skills like critical thinking, in addition to some key literacies, like information literacy. I have taken these ideas but describe them slightly differently, as shown in the image below.

network era fluencyNetwork era fluency could be described as individuals and communities understanding and being part of global networks that influence various aspects of our lives. For individuals, the core skill is critical thinking, or questioning all assumptions, including one’s own. People can learn though their various communities and develop social literacy. Information literacy is improved by connecting to a diversity of networks. But control of networks by any single source destroys the ability for people and communities to develop real network era fluency, which is not good for society in the long run and may kill innovation and our collective ability to adapt.

Mass network era fluency can ensure that networks remain social, diverse, and reflect many communities. This kind of fluency, by the majority of people, is necessary to deal with the many complex issues facing humanity. We cannot deal with complex issues and  networked forces unless we can knowledgeably talk about them. This requires fluency.

Related: The Network is the Solution

Preparing for the network era workplace

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My presentation at the Learning Technologies Summer Forum in London two weeks ago concluded with the advice to help people be more explicit in their work. Leading up to that conclusion, I showed how the nature of work is changing. We are moving into a creative economy, as Gary Hamel says. Customized work, with high task variety, is becoming the norm. Routine work is being replaced by software and robots. Formal instruction cannot keep up with workplace needs, so there is an increasing requirement to support informal learning and the sharing of implicit knowledge. Finally, much of what we produce at work today is intangible.

Here is the video recording: enterprise social technologies, learning & performance

 

Learning is too important to be left to the professionals

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profWorkplace learning professionals are in for a shock. Business is waking up to the fact that learning is now mission critical. Will executives continue to allow learning policy to reside in a separate department or some sub-department of HR for much longer? Do you think they will let “learning professionals” maintain sole control? I doubt it; especially if the military, which is either training for war or engaged in one, is an example.

For example, the military lets training specialists and schools run individual training, but even more time and effort is put into collective training that emphasizes social and informal learning. The latter is run by operators (e.g. line of business owners) not learning specialists. I think business is going there as well, if the struggle over control of enterprise social media is an indicator – and the learning function seldom is allowed to run it. Using the 70:20:10 lens, it’s likely that these professionals may only look after the formal 10% of organizational learning. You could say that is being marginalized.

Enterprise social media and external social networks are where more business transactions will occur. They are also where a lot of learning will happen, but not separated from business. The networked business world is subverting the learning and development hierarchy. Scalable learning does not come from a separate departmental function.

The cost and difficulty of coordinating activities across entities, on a global scale, is far lower now. The pace of change is accelerating and the degree of uncertainty increasing. Perhaps a new rationale will be required to drive institutional success in the future. Perhaps we need to move from a rationale of scalable efficiency to one of scalable learning — designing institutions and architectures of relationships across institutions that help all participants to learn faster as more participants join. —John Hagel – HBR

Mainstream media are catching on that in the network era, work is learning and learning is the work. This article from BloombergBusinessWeek is an example of the growing understanding that social learning is a business imperative:

Staff who carry out day-to-day duties—and whose productivity you’re looking to improve—should ultimately be the source for defining what knowledge they need and what knowledge they know is valuable to others.

With learning in the business spotlight, questions will be asked about the efficacy of current methods and practitioners of those methods. We are seeing a growing demand for self-directed and networked professional development. Recently, Craig Wiggins told the ASTD (training & development) community to just stop pretending – “Let’s stop pretending that, at one point or another, we haven’t for a moment wondered if we deserve to be marginalized. (Opinions on learning are never short supply.)” Learning will not be marginalized, but the learning trades, like scribes of old, will be.

The network is the solution

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Our future needs to be focused on learning, not instruction. The key to a flourishing civilization in the network era is sense-making. We have to move from what David Warlick describes as individualized instruction to personalized learning. In the latter, “Literacy becomes a wide range of evolving information skills developed around the activities of learning – the ability to acquire knowledge and skills through the resourceful and responsible utilization of information.” Self-instruction, the basis of personal knowledge mastery, is a necessity in effective peer-to-peer networks, as networks are how we will govern ourselves more and more. David Ronfeldt articulates this with his TIMN [Tribes-Institutions-Markets-Networks] framework.

TIMN has long maintained that, beyond today’s common claims that government or market is the solution, we are entering a new era in which it will be said that the network is the solution (e.g., here and here). Aging contentions that turning to “the government” or “the market” is the way to address particular public-policy issues will eventually give way to innovative ideas that “the network” is the optimal solution.

We all need to understand how to become contributing members of networks, for work and for life. This should be the primary focus of all education.

“Reed’s Law” posits that value in networks increases exponentially as interactions move from a broadcasting model that offers “best content” (in which value is described by n, the number of consumers) to a network of peer-to-peer transactions (where the network’s value is based on “most members” and mathematically described by n2).  But by far the most valuable networks are based on those that facilitate group affiliations, Reed concluded. – David Bollier

Without sense-making skills, the citizenry cannot understand complex issues, such as individual privacy versus national security. These issues require networked, human intelligence, not broadcast sound bites nor ‘learning objects’.

Sensemaking should drive policy. Policy drives decisions. Decisions, of course, need to be informed. If the People don’t know what makes their world go ‘round, the folks on the Hill sure won’t. Globalized governments can’t. – What the Snowden Case Teaches Us

As David Bollier concludes, “Legitimate authority is ultimately vested in a community’s ongoing, evolving social life, and not in ritualistic forms of citizenship.” Should not education move beyond ritualistic forms of subjects, classes, and certifications and toward ongoing, evolving social learning? How else will we be able to deal with the complexities of this networked, connected sphere that we inhabit?

Jon Husband writes that we are all in this together:

The interconnected Information Age is beginning to show us that we’re all linked together – and that the whole system matters.

This principle applies to organizations, to networks of customers, suppliers, employees and communities, to our societies and to the planet.

New language for this principle is popping up everywhere – knowledge networks, intranets, communities of practice, systems thinking, swarming, social software, social networks, tipping points.

Awareness is the key.  Maintain an “open focus”.

Being aware of yourself, others and the effects of your actions and ways of being in relation to others is a fundamental requirement in these conditions.

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Note: This post was written in order to put a number of ideas together into an initial narrative, mostly for myself. To me, it makes sense, as I have read and tried to unpack the many linked articles. For the casual reader, this may not be so clear. – Harold

Social learning is for human work

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This past week I came across the theme of the changing nature of work several times.

As computers transcend many human capabilities and work is dehumanized, we must focus on the skills and abilities where humans excel beyond any imaginable machine capability. At the heart of those human capabilities are creativity and innovation. – Ross Dawson

“Focus on the human factor,” says Gerd Leonhard, “If our work – and our output – is robotic we will soon be surpassed by intelligent software agents and machines.”

This is exactly the message I am trying to convey in the image below. Standardized work (blue) is already being outsourced to the lowest cost of labour and will eventually be automated. This includes knowledge work. Customized work (yellow) is human. Its dominance will mark the end of the industrial era. Talent will replace labour as intangible assets will provide value while machines and software will handle any work that can be standardized.

jobs and workThe learning imperative for the new workplace is not to know more stuff, because software can do that for us, but to become more human. Social learning will help us collaborate and cooperate in doing customized work, requiring thinking and building skills in order to innovate and craft unique products and services.

Fortunately, most human behavior is learned observationally through modeling: from observing others one forms an idea of how new behaviors are performed, and on later occasions this coded information serves as a guide for action.” –Albert Bandura, Social Learning Theory, 1977

Social learning helps groups of people share their knowledge in non-hierarchical ways and is not limited to the confines of instruction. Training courses take too long to develop and will be obsolete before they are launched. Most organizations today have a 95% informal learning gap they are not addressing. Social learning, using PKM methods and social networks, can address much of this.

Social learning networks enable better and faster knowledge feedback loops, essential for innovation and creativity. In an environment of constant innovation and faster market feedback, social learning is how we will share implicit knowledge and get work done. Social learning is for human work.

social learning is how work gets done

Becoming explicit

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print to digitalOur old technology — paper — gave us an idea of knowledge that said that knowledge comes from experts who are filtered, printed, and then it’s settled, because that’s how books work. Our new technology shows us we are complicit in knowing. In order to let knowledge get as big as our new medium allows, we have to recognize that knowledge comes from all of us (including experts), it is to be linked, shared, discussed, argued about, made fun of, and is never finished and done. It is thoroughly ours – something we build together, not a product manufactured by unknown experts and delivered to us as if it were more than merely human. – David Weinberger

Helping people become explicit in their work, as David Weinberger suggests in the above article, was my concluding advice to delegates at the Learning Technologies Summer Forum in London yesterday [curated tweets by Martin Couzins]. As learning and work get integrated, the co-creation of organizational knowledge develops from the sharing of our implicit knowledge. This is a messy, never-finished process that requires continuous engagement, usually through conversation. I think it is becoming rather obvious that knowledge cannot be directly transferred, but better understanding can emerge from open sharing. In the digital age, supporting knowledge sharing can be a key role for learning and development in the organization.

The nature of work is shifting. The dominant framework is moving from corporations to networks. As I explained in my presentation, knowledge networks are optimized when they are based on openness, which enables transparency, and in turn fosters diversity, thus reinforcing the basic principle of openness. Over time, trust emerges. Openness can be supported through social networks, as they are non-hierarchical by design, allowing anyone to connect to everyone. Supporting social networks becomes a business imperative, and a potential role for learning & development staff. They can also help people develop personal knowledge mastery skills, a foundational competence for the connected workplace. As the graphic below shows, becoming explicit can have a direct impact on innovation.

becoming explicitBooks gave us the illusion that knowledge was stable. It never was. Now it’s time to think of organizational learning as a process of shared attempts to become explicit. As Gerd Leonhard remarked in the opening keynote yesterday, a critical skill in the near-future workplace will be sense-making. I could not agree more.