Last month at TechKnowledge, I did a panel discussion on Learning Experiences and Activity Streams with Reuben Tozman and Aaron Silvers. While the three of us tread in these waters every day, it struck me that most people would have only an inkling of an idea of what “learning experiences and activity streams” actually are.
Technology is now enabling us to interact and communicate with each other in very different ways. Not only that, but everything we do online can be tracked.
Think about learning experiences as things that people DO to learn how to do or get better at something. I’m not talking about didactic content presentation, nor am I talking about review and recall exercises (although, in the lowest implementation of learning experiences, they are often thought of as such). Learning experiences, at their best, are authentic practice and application of knowledge and skills in context.
Activity streams are a flow of information about what people are doing or engaging with. Twitter is a kind of activity stream, although its an “opt in” stream where people select what they want to post. Other activity streams, like the news feed feature on Facebook, automatically populate with what someone is doing. If you scan your news feed in Facebook, you’ll see status updates, what people are reading, what music people are listening to…and then you can engage with them real time.
What if you could take the information collected in people’s activity streams and recommend learning experiences to them based on their interests or what they are doing? Better, what if activity streams collected performance data from online learning experiences and then recommended additional learning experiences based on their strengths and weaknesses? This is the basic concept behind personalized curriculum; our learning experiences can now be recommended and filtered based on our past performance and demonstrated competencies or skill gaps.
Games already do this in the form of “leveling up.” In order to move on to higher levels, you need to prove competency in the lower levels. In games, however, the leveling up path is linear and consistent across all players. The opportunity for activity streams and learning experiences is that no two people’s learning paths will look the same. Instead of a leveling up path, learning will resemble more of a web, with each learning experience connecting different skills and knowledge sets.
Still, we need to measure competency, and that’s where game mechanics can support this evolution to personalized learning. Collecting learning experiences, much like collecting achievements or badges, is the first step. The second step is showing skill progression, the gradual “leveling up.” The third step is showing mastery in context, or in gaming terms, the “boss level.”
As we find ourselves more closely connected with each other and with information, we need to rethink our relationship with learning. In an age where anyone can know anything in a matter of minutes just by typing in keywords into a search engine, what’s valuable is learning how to apply that information in meaningful ways. Activity streams can provide information on what people need to know or do better and learning experiences can create the opportunities for people to build competencies. Wrapped in a game, achievements can be measured and rewarded.
Maybe instead of degrees and certifications, we should think in terms of “achievements unlocked.”
About the Author
Koreen Olbrish, Ayogo VP of Learning Design, creates games that demonstrate the untapped potential of immersive learning design.