I before A

Learning

Those of you who know me well will concur when I say I don’t take myself too seriously, but when I’ve laid out my predictions for L&D over the last two years, I don’t think they’ve been too ridiculous.

I’ll keep this brief, largely because I don’t deem what follows as thoroughly researched and credible.

What I’ve understood so far is this….

Machines need data.  They (partly?) infer through data.  But whilst a swathe of organisations may bury their heads when the Semantic Web goes mainstream, they could probably prepare themselves for the inevitable and do more now to improve and share their data internally.  I believe this is still called ‘Business Intelligence’.

But imagine sharing data beyond the firewall.

I’m not talking about releasing the PDF ‘Annual Report’ (now with new improved data viz) on your website, but about providing raw data that enables the opportunity to partner and create better services, better products, better experiences.  Yes it’s risky and to your detriment perhaps, but you already release this rawness (un)willingly in your day-to-day with Google, Facebook and all the other others.

In 2010, Tim Berners-Lee proposed a system for rating datasets based on a similar five-star rating system used for hotels.  This system is a core principle for linking data, the bedrock of Web 3.0.

You can learn more about this rating system via this very short video.

Now I could say that xAPI is the on-trend answer to all this for L&D, but I’m not qualified.  However, in the meantime, the ugly humbly CSV file could be the contribution that you Early Adopters, and even Laggards, make to the ‘Web of Data’.

So let’s call my L&D 2018 prediction, nay vision, ‘Information Architecture’.  And even though that’s the wrong term, I feel like I belong again…all clever and smug.

PS Here’s what I said in 2016 and 2017.

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Día de los Santos (#MHAW17)

humanity, Learning, Love

To you, the person that bullied me, my wife, my parents, my friends.  You who couldn’t look me in the face, leaving hurriedly and voluntarily after the hearing. You who defied CISCO-certified engineers a year later, delivering unfinished toxicity into my INBOX.

To you, the boss who let it happen and who pummeled me into thinking I was wrong – wrong to raise the grievance, wrong to highlight the incompetences, but who guised it with a smile and firm shake of the hand when I moved on.

I wish we could all meet again and talk about it, see what’s changed.

To you,
Alison. My work colleague and favourite lunch partner.  My friend, taken from this world, a husband and two beautiful young children within five months of your diagnosis.

I wish I had found the right words.

To you, Dad. Eighteen months since I went downstairs to the kitchen for that momentary cup of tea and stared at it, sensing that something had just changed. You chose your moment. You were always in control, and in some respects, you still are.

To you, Mum. I’ve finally realised that the only ‘planning ahead’ we need to do is the here and now.

To you, Believers. I occasionally close the door on you. I’m sorry. I hope it’s never too late.

To you, Disbelievers. Well, fuck you.

And to you.  You’ve never really had or given yourself a participation strategy have you? You’ve never had or given yourself permission? You may have experienced the polarised judgement that comes with people knowing….and not knowing, but who assume. It’s a terrible affliction isn’t it, but so is not opening up sometimes.

You are quite brilliant in some things.  Remember that and build on it.

Seek purpose, but don’t hurry it along.

Be generous whichever way you feel is right.

You are your legacy.  Those that matter write the eulogy.

Here is the data…

Learning


Dear Sir or Madam
Here is the data….. by way of
 my letter and application.  What I’ve achieved, where I’ve failed, where I’m heading.

Dear Panel
Here is the data…..w
hich was publicly available. Which came out two days before we met.
Which I presented, and which you later denied. The data which was supposed to be part of the conversation.

Scores
Dear Panel ( and algorithms)
Here is the data…..you chose to gamify.  Which came to me with a disclaimer*. Which you thrust down (and up) my data pipe.  The data we really should have spoken about.

MJ

Here is the data.  What questions are you asking of it?

*’It is not guaranteed….that the contents of the report are the unmodified outputs of this system.’

Dumb ‘n’ Bass

Learning, Recruitment

Sorry, Robin.

That seems a good place to start this unload.

As the latest recruit to the covers band and my new partner in time, you arrived to such scrutiny; ashamedly from all of us.

A seasoned, knowledgeable, technically gifted and personable bassist, we doubted your integrity, your commitment, your longevity, your honour. Why would you, a pro who has played all over the world with some great musicians, want to play with us Sunday footballers? But that’s the view we took about ourselves before you joined, intentionally overlooking all your attributes to protect and mitigate risk.

Fuck risk. We, and you, are better for accepting it.

Right. You set, Robin? Count us in.

Is….?

Learning
  1. ….70:20:10 the new Pareto’s Law for L&D?
    • 10% Effort
    • 20% Resources
    • 70% Results

     

  2. ….there such a thing as L&D borrowing capital (budgets) from shareholders (other depts) and promising them a dividend?  Or is this what they call ‘Shared Services’?
  3. ….L&D ‘at risk’ and/or ‘a risk’?  And who is best positioned to make that assessment?

More questions (and no answers) to come.

Environments

Learning

Please help me out here.  I don’t think the light is quite ON.

  • Learning in isolation is an environment.
  • Applying in isolation is an environment.
  • Learning as an individual within a group is an environment.
  • Applying as an individual within a group is an environment.
  • Learning as a group is an environment.
  • Applying as a group is an environment.

Each is unique.

 

Resist

Learning

#resistlist

I’ll be adding as and when.

  1. Thumping it in the back of the net when a simple tap-in will do.  Same outcome.
  2. Pretending to understand. Ask. Ask again.
  3. The fear of not doing ‘it’.  Just because everyone else is doing ‘it’, it doesn’t mean you’re not current.  Anyway, what is current?
  4. The thought that the problem is you. You might just be in the wrong company.

2016 A.D. – the year of ‘Smart Learning’?

analytics, CPD, Learning, smart city

One of the trends that appears to have gained traction in recent months is Learning Analytics (LA). It has heavily featured in conferences right across the world, most recently at DevLearn.

Now I know LA strikes fear and loathing in some of you, but like it or not, it does appear to be here to stay.

Wikipedia defines analytics as ‘the discovery and communication of meaningful patterns in data.’

Data.

Technology has made data ubiquitous and, if Edward Snowden is right, more open than we had perhaps estimated. Data and the rights to privacy can be argued back and forth, but I do believe in the sharing of data for the social good.

One example of this is with Smart Cities.

For those not familiar, Smart Cities harness smart technology and data to tackle issues ranging from the economic to environmental. I live quite close to one – Milton Keynes.

Here’s an example of how they are using tech and data.

Energy systems for smarter cities

What the video shows you is consumer becoming a producer of data and then actively surrendering that data for the greater good. But they go beyond that. They go on to co-create by changing their behaviour. They call it Consumer to Prosumer, a top-down/bottom-up approach.

So, if people are comfortable doing this within cities or communities, why shouldn’t organisations be any different?

I get the trust, culture, WIIFM, Big Brother thing, but in the same way that we might relinquish control of our data for the social good, why wouldn’t we back in the workplace? Would opening data create conversation, create innovation and ideas, enable behaviour changes for the better? Would it enable co-creation within your organization? Isn’t this what xAPI and AI are there to assist with?

This leads me to Professor Everett Rogers and his theories documented in his wonderful work, ‘Diffusions of Innovation’.   Aspects around ‘Properties of Innovation’ and ‘Adopter Types’ may provide some clues as to the ‘whys’ and ‘why nots’ of Big Data.

Here’s my retrospective VLOG that explores this.

I just wonder if Smart Cities will become a benchmark for more openness in data-sharing within other areas of our lives. Could it influence what and how we learn in our schools, our communities, our workplace?

Will 2016 be the year of ‘Smart Learning’?