The year sure went by quickly, did e-learning evolve at the same pace?
At the beginning of every year I take a moment to make three predictions in the e-learning industry. There are times where I am right, and others when I miss the mark. Either way, it’s fun to watch the evolution of e-learning!
As 2018 has just ended it is time for me to have a look at my most recent predictions and give a self-assessment on how accurate I was now that 12 months are in the books. Below you will find my predictions and my estimated outcome of each.
Prediction #1: Growth in Micro-Learning Delivery & Reporting
Result: Nailed it 🙂
I first mentioned micro-learning back in 2016 and today it is very much en vogue. The rise of micro-learning cannot be ignored. It’s everywhere.
The micro-learning niche in e-learning is so profitable that we are now seeing services and platforms that are specifically built for micro-content delivery. What gamification did for e-learning five years ago is what micro-learning will be in the years to come.
If you have an LMS and you aren’t thinking about micro-content then you will be behind the curve very soon. Start getting your micro-learning plan together, and fast!
Prediction #2: The “SaaS’ing” of Courses
Result: Sort of Right
This prediction was in relation to how course creators would sell their offerings. Individuals and organizations would pay monthly fees to access a course, or library of courses. In return, the course creators keep the content up-to-date, handle technical support inquires, and manage the tech stack (LMS).
I have seen this model used, but it’s rarely pulled-off successfully and usually only by larger entities. For instance LinkedIn Learning uses the business model almost exclusively. At LearnDash we see many of our customers creating membership oriented course platforms, but the value proposition isn’t as I outlined above. The courses are supplemented with webinars, community events, and other “extras”. This isn’t bad, it’s just a different business model than my prediction.
Prediction #3: Machine Learning for E-Learning
Result: Wrong 🙁
I was hopeful to see this year the beginning of machine learning being applied to learner behavior in e-learning. Sadly, it has not manifested in the way that I imagined it would. The idea is still conceptual, just as it was in January 2018. No real progress has been made.
Applying artificial intelligence into any segment is going to be an endeavor. The lack of growth just means we aren’t quite there yet in terms of our understanding on how to apply this to learning environments as well as market need. I actually don’t think it will be ready for quite some time, certainly not within the next three years or so, but hopefully within five.
What will come about in 2019?
So that is a brief recap of my predictions from last year. I think that all three will continue to evolve in their own way, even the prediction that I got wrong. Which begs the question: what is in store for this coming year?
Sometime this month I plan to make another round of predictions, and I think they will mostly be focused on tech and instructional design theory (as these two often play off one another).