Learning in Communities - Networked Collaborative Learning
The third topic is on Learning in Communities – Networked Collaborative Learning.
In our course material, Kay Oddone discusses
personal learning networks (PLN), online learning communities and personal online
learning networks.
According to Kay Oddone, there are quite
a few definitions of PLN; but she also says that, in reality, it really is a
personal experience.
The term PLN started to appear in the
late 1990:s, in 1998 Daniel R. Tobin published a web article Building your
own personal learning network. Tobin´s definition of a learning network was
“a group of people who can guide your learning, point you to learning opportunities,
answer your questions and give you the benefit of their own knowledge and
experience”. According to Kay Oddone, the definition is still valid, although how
we learn and what we learn through our networks have changed, partly due to new
technologies. The power of online PLN:s come from the interaction that occurs. PLN:s
are based on social learning, but the learning is driven by the individual. Following
others is not enough to develop professionally.
One reason for the importance of
networks, according to Oddone, is that with today´s information overload, it is
more important to know “how to find information and knowledge when we need it than
it is for us to carry this knowledge in our head all the time”. To filter large
amounts of information is a much more important skill than simple memorization.
She is also referring to online learning
communities, which are different from online personal learning networks since the groups
are smaller and tighter and in general people know each other. “There is a high
level of trust and reciprocity within the relationships”. The members have a
shared goal and there is a sense of security, and relationships are stronger
than in a PNL. A drawback might be an inward focus.
My most important personal learning
network are my friends. We have somewhat similar educational background, work
in different areas but there are still connections between our job roles and I
place a great trust in them, their knowledge and their points of view.
I am also part of communities in my job,
which provide me with more in-depth knowledge related to my role, but it is not
always evident how to evaluate the information/knowledge and how I can use the
shared information, since the relationships aren´t so close that I get “the full
picture”. Solutions are shared but the prerequisites that made a presented
solution successful are not always discussed.
When it comes to PNL:s, I have to admit,
I am a slacker. I follow people, but I don´t interact. It is more a way for me
to scan for trends and new information than an exchange and sharing.
What I do find difficult with the
overload of information is to evaluate. What is true and what is
relevant? How well researched are models, frameworks, ideas that seem to be
popular and the “talk of the town”? And if they are well researched, during
which circumstances do they work well?
A few months ago, I listened to a very
interesting program on the public radio (so I assume the information to be true), where they addressed a problem with
research results - research experiments with interesting results get
published and receives attention in media, but quite often when experiments
are repeated, results are not the same; the results are not replicable. One
example is one of the most viewed TED Talks ever (summer 2021) on power body
language. The presentation is based on results from an experiment that had been
conducted only once. Later, when the experiment was repeated, the results were
not the same. So is the research valid? And how to evaluate the information?
How do we unlearn all the invalid information
we come across when we search for valid information? If we have read a text, we
have read it, we can´t unread it! Information spreads globally
and becomes part of the “collective consciousness”. We have read something
somewhere and six months later we believe it to be true, we can´t remember
exactly where we read it, but information becomes part of our belief system
without us knowing how it happened. This raises questions: How can we check
underlying data? How can we screen information efficiently? Where do we search for information? Who can we
trust in this world of online visibility and constant information upload? Who
and what brands are reliable?
The challenge for the individual is not
only filtering large amounts of information and knowing where to find knowledge
and whom to connect with, but to evaluate information and decide on
trustworthiness of online information and our relationships. And last but not
least, to forget information that is not relevant or true!
PLN:s Theory and Practice, part 1 and 2, Kay Oddone
Very interesting reflections and I immediately think of the famous song by Mikael Wiehe and Björn Avzelius, "Vem i hela världen kan man lita på?" We see so often that research that confirms our world view gets media attention and research that challenges popular opinion is often ignored (eg Prensky's digital natives concept still gets attention despite being disproved many times, we still build open plan offices despite lots of research showing how ineffective they are). Truth is in the eye of the beholder perhaps? Maybe this is central to our students' learning process - the realisation that there are many truths and developing strategies for dealing with uncertainty.
SvaraRaderaThanks a lot for this interesting input! Indeed, when I saw the webinar by K. Oddone I also immediately thought about the huge issues we have nowadays with fake news and unreliable information sources. It is not only forgetting unreliable results, it is also fighting the confirmation bias, that is one of the worst problems on our learning paths. I believe that the access we have today to this huge amount of information can be definitely overwhelming; however, it also offers the opportunity to see a lot of different nuances of a certain topic. Of course, we need to have the instruments to analyse and digest all the information.
SvaraRaderaHi,
RaderaThanks for your input! I agree!