Tuesday, 20 June 2017

Stephen Downes on a model of personal learning #learningtechday

STephen looks great while he takes the stage, and delivers an authentic, humorous talk with lots of ideas to reflect upon, while all the time simply sharing his experiences and thoughts. I must admit… I have a lot of speaking flow to learn.

Streaming life from https://www.youtube.com/watch?v=PnI5NBo13y4 see the full talk there.

A model is somethign that seems to always be a defined object, but research and life shows that the application of a model predetermines what comes out of a model. You practically determine what comes out at the other end… how well does this approach increase learning … the conclusion is built into the model. You always find what you are looking for and a model does just that.

If a model comes into play, i twill only be at the end of the journey. Stephen refers to old age, the moment where you have the idea that ‘I get it, finally!’.

What is missing in the standards based approaches and the models-based approaches is what we used tot hink of as BAD (Bricolage, Affordances and Distribution). Technology should be build for affordances… not predicting what people will do with that technology (Inge: think Iron Bridge approach).
A day in the life of Stephen…. Tech selections and purposes
Sharing what I do, looking for similarities and then having a laugh at what we do.
The tech we are introduced to, is the tech that we will absorb to use, that is the ‘real point of reference’.
(everycloudtech.com is used to filter out spam, but still a lot is still).
The starting page is an overview of all he does.
Using RSS feeds to get information from others (feedly).
Stephen does not care about too much information, but to make sure he is getting enough of a snapshot of the world. IN a sense the feeds are random, as they multiply as the information is written.
OPML is then shared by entering it into feedly.
From there, he selects (from getpocket.com) the content he wants to have a closer look at. A searchable list.
Social media: twitter, linkedin (Microsoft acquired it, so now they might go to expensive learning quite quick – 30 dollars a month), plus.google.com (baseball)
Newer, distributed social networks Stephen currently uses: joindiaspora.com , app.net and what works still mastodon.social/@downes  (inge: check out mastodon!)

codecademy.com/learn (learned basic python on it)
Stackoverflow.com is great, you type a question into google on programming and you choose the stackoverflow page.

Learning through webinars: CIDER and elearninggguild.com

The harvest of these informations is saved on gRSShopper http://grsshopper.downes.ca
Open coded, creating library (now database of others), 280.000 posts in the last 20 years… WOW! These focused posts drive you to be consize and brief.

Reflection of the talk
What has come out of all of that: the concept of the personal learning environment
No one actuallyhas been able to build it … yet.
The PLE connects to all the stuff you need or at least think is important.
The big question is: how do you pull this off?
This is completely distributed, not within one single online entity
Internet is capricious at this point in time, as things started frequently get deleted as well (in terms of software built by corporates)
Decisions to be made: what information should it record, who owns the data, how private, what should it do, what would a person do with it, where exactly is a PLE located?
So all of us should have a PLE.
So where do we connect with to do stuff with people.
There are millions of ways to connect with each other, but the network is currently broken as a lot of software cannot communicate with each other.
Properties of the network: how do people find each other? Services? How do they communicate? Is it secure? What do they share? How does a single PLE work with services? Do we need centralized registries?
We need to work decentralized for these PLE, as this will prevent total shutdown.

Why a personal learning environment?
What is the value proposition for a PLE?
Note: value is not what you can do, it is how you benefit
This is usually stated in financial terms (earn more, cost less)
Can also be stated in terms of quality: faster, bigger, better
And can be non-financial goods: satisfaction, happiness, memories… that is what is going to matter more than the financial benefits… but also different for all the people.

Education is not a search problem
It is not about finding, curating the best resources. Quality really matters only if you really did not want that learning resource anyway. If you are really engaged, you will make due with marks on a rock, … if it solves your problem…

Education is to a large extend a making problem - making
Lightroom.adobe.com (pictures), affordable because it is now in the cloud
Audacityteam.org/download (for recording as well from radio or audio sources 😊
Docs.google.com sharing documents, commenting…
Rebus community or open textbook library…
Movies: for this live stream on YouTube Stephen used  xsplit.com  combining slides with video.

www.downes.ca/edradio.htm (from selected podcasts)
slideshare.net/downes for slides, sometimes combined with audio (also from this talk).

New learning paradigms
See carrie Paechter, metaphors of space in educational theory and practice
The original MOOC was a map, where the collective learners explore and map
Personalisation are currently: rules-based events, user models, adaptive learning… Stephen sees two approaches to this. Personalised learning is serendipitous, you do it for yourself, it is creating your own learning experience. The outcomes are not certification, but present inner network, your own persona, which manifests your interactions, experiences… extended cognition, including the network.

Friday, 9 June 2017

#oeb_midsummit Cognitive neuroscience and learning by @BekkeringHarold

http://www.ru.nl/publish/pages/792606/harold_bekkering.jpgHarold Bekkering reminds me of some of my Dutch family, funny feeling. Once he took the stage, it really was like listening to cousin Folkert.
Everything is connected in the brain, and the brain is a predictive machine.
A neuron at work is incoming data is output in just one unit. So in neuroscience we see that multiple inputs triggers a process into one output.
Hebbian learning: everything is connected (Hebb’ theory).
A human can adapt to one specific tone of voice and timbre. Our brain adjusts.
The brain is a prediction machine. Read Karl Friston and Andy Clark.
Distributed knowledge in the brain. Exteroceptive, autonomic (interoceptive), motoric (proprioceptive) given the conceptual multimodel representations. The brain tries to make the best things for you. It is a multimodal representations, which makes it of interest.
The whole brain is summed up in error correction.
E.g. you walk to a door (prediction is going through the door), but if a door is closed you adjust your action based upon the perception after the prediction.
Amal and Giraud, TICS 2012, beta and gamma power. The brain is only active when you make errors. Only after making an error your model is updated [interesting].
We learn more from negative feedback. Oh no! 😃
Creating a safe environment to learn from errors.
Social learning: humans are by nature social, homo imitans.
Dunbar (1998) The social Cortex, it is big because we have huge networks. The Dunbar’s number.
Social learning is needed due to the brain needing to be matured over time (baby to adult).
Good tip for learning: saying: hi (insert name) and then say the action. The brain does not ignore the calling of a name to become active.
Mirror neurons: have revolutionised neuroscience. Motorcortex was investigated, and in the lab, monkeys mimicked humans picking up peanuts. There are cells that only get active if we see someone else moving. Your brain cannot help to observe and react.
Learning analytics: extracting data, predicting data, … data driven education.
It is not useful to only learn in one learning style is the real point of interest, if you want to really learn the best thing to do is to use all styles for learning.  
Lessons for online learning
Hebbian learning: be careful with what you offer
Predictive learning: structure and provoking errors (job aids similar)
Social learning

#OEB_midsummit teaching critical thinking by Ben Nelson @MinervaSchools

https://d33z52hfhvk3mr.cloudfront.net/s3_proxy/minervaschools-production-cms-uploads/images/ben-nelson-large-flipped.width-1200.jpg Ben Nelson takes the stage. What is critical thinking? Critical thinking in itself does not exist. There are many things that together make up critical thinking. Evaluating a claim is something else than critical thinking, which requires arguments and proof.
Famous study with air traffic controllers, a manual job and taking in enormous amounts of data at split seconds. Critical thinking was similar because of far transfer. Far transfer is the holy grail of wisdom, of learning.
Point of wisdom is when you encounter a novel topic, you are able to weave your previous together to come up with a logical response. But we are seldom able to do this.
Contexts are influencing learning and recall of learning, which is why people do not often far transfer.
At Minerva far transfer is practiced in complex systems, applicable to many different fields. There is a large set of rules that underpin what creative and critical thinking is. At Minerva we took each of these rules and broken it down into approx. 100 parts and we teach them in multiple contexts. This way the students learn to use far transfer more often.
Eg. Foundational concept: Bayesian formulas for choices. Learning the concept, and distribution, the hard part is to develop the instinct of when to apply what to which data set. The bulk of the time is to train responses to triggers that point towards one or the other concepts.
Once you understand these concepts you can continue to use them over time.
Technology is used for tracking data to see whether the students interact based on the data and results in critical thinking. To do this there are also highly immersive seminars with fully active learning: at least 75% of the time need to be active in these seminars. They can debate, then others moderate the debate, interact or fill in the next part of a thought… all of these techniques enable students to be fully engaged [Inge: wondering whether this is not simply Pavlov combined with engagement]. Also using Deep Processing (repeating for deep remembrance).
A bit like the Flow, as the learner learns more by being engaged, motivated, willing to learn and focus on something specific.