In last week's Learning Circuits, I explored how I use Twitter as a professional development tool, and explained how doing so has helped me build a personal learning network. Personal Learning Networks (PLN) are, in many ways, both the past and the future of how people will learn.
Training and formal education are important, but people have always learned more from sharing with each other informally. Technology has finally reached a point where it is no longer a barrier to this sharing, and can actually amplify it. The concept of a PLN is the natural evolution of this, enabling us to connect, share, and learn with others that historically were out of our reach. It enables us to reach across the globe as easily as we historically have peeked over the cubicle wall.
But with the new technologies are new challenges. I often tell people about the value of PLNs, and share tips on how to get started. I notice a number of them taking the first steps towards building a PLN, but shortly thereafter abandoning the task. In almost all of the cases, the reasoning follows a common theme: being overwhelmed.
It's not so much that the technical mechanics of a tool like Twitter are challenging; it's the world that Twitter opens up that can be overwhelming. The common metaphor for new Twitter users is that it's like 'trying to take a drink from a fire hose'. There is so much information that trying to take it all in is impossible.
This isn't just a problem related to Twitter. In today's digital world where anyone can be a content creator, the amount of information that is available can be staggering. Various studies estimate that the amount of digital data that is stored doubles every 18 to 24 months.
Which begs the question: In a world of ever-increasing data, how do people find what they are looking for? How can all of the 'noise' be blocked out? Returning to the Twitter example, how can I find people to connect with in an endless sea of unrelated tweets?
It all comes down to a single word, a word that is a critical skill in the digital world: Filtering.
Looking through random data to find the information you need is time consuming and inefficient. Individuals need to develop filtering skills to block out the noise of everything so that they only see the information they are looking for.
Many applications have tools that can help with this. Let's revisit personal learning networks and Twitter as an example.
Thankfully, Twitter self-filters. When you log into Twitter, your main feed will only show the tweets of those people you choose to follow. However, that really isn't enough. As the list of people you follow increases, and the reasons for following individuals varies, your main feed may quickly become disjointed.
That's where lists come in.
If you access your profile from the Twitter home page, you'll see an option for lists. Creating lists is an excellent way to filter the tweet stream.
In the example below, I created a list called TwitterTips. Once the list is created, I can easily add individuals to the list via their profile. That way, if I am interested in reading tweets from people talking about Twitter tips, I can go to the list I created and the feed will filter down to just the accounts I added to that list.
Another filtering option is to search for hashtags. A hashtag is created when an individual adds a number sign before a word or series of characters. Twitter does not yet have a system where you can tag or categorize message. When a user adds a hashtag, they are essentially adding some sort of category to a tweet.
ASTD is a great example. If I search Twitter for the 'ASTD', I will see tweets related to employee learning. However, I will also see tweets from people using 'ASTD' as an abbreviation for the word 'assorted' (a common practice on EBay). By placing the number sign in front (#ASTD), I am essentially searching on the category of ASTD. Many learning and performance professionals (including me) will add the #ASTD hashtag to tweets about our field because they know that people in the field are following the hashtag.
Lists and hashtags used together are a great way to build your personal learning network. Following hashtags like #ASTD (or #lrnchat, another popular hashtag in the field) will get you exposed to other individuals you may want to follow and add to lists. This will filter the Twitter feed down to the information you find most valuable, and help you build a strong PLN.
My first two Learning Circuits posts have focused primarily on building a personal learning network via Twitter. However, the underlying concepts of this discussion apply to the work we do as learning professionals as well.
People learn most from sharing informally with each other. Social media tools like Twitter enable us to take the informal learning that traditionally took place only face-to-face and amplify it to a global scale. We are constantly learning from one another informally, and the pace is only increasing via social media.
In a world where most learning is taking place informally, shared via social media tools that reside outside of LMS platforms, and are not tracked what role does the learning and performance professional play?
My next post focuses on that question, and introduces what I believe is the next core competency for learning and performance professionals: Curation.
Thanks for reading - see you next week.
David Kelly is the director of training at Carver Federal Savings Bank and Member of the ASTD National Advisors for Chapters. He is also the author of the blog Misadventures in Learning, where he discusses the future of the learning field and curates the backchannel of learning conferences
