I’ve been writing about learning personalization for more than two decades. Influenced by the perspectives of Sir Ken Robinson and others, it seemed only a matter of time until learning content, activities and experiences would be personalized to some degree for each of our learners.
Learning personalization makes total sense. We should “optimize” the time (and wage expense) of learning content. We should shape the content around what employees need to know, avoid what they know already, and adapt to their requirements, backgrounds and ideal learning formats. The aggregate impact on motivation, engagement, efficiency and cost could be amazing for both learners and the organization!
Learning personalization is a great idea; yet, it has been amazingly difficult to implement. There are a number of enemies and obstacles to personalization in the workplace.
First, there’s compliance: The rules, expectations, and style of compliance and regulatory action demands a common learning delivery for all. They want to know for certain that all employees have been taught the same stipulated content.
Traditions and rituals are another obstacle. An example of this is that every day, millions of passengers are taught how to use a seat belt on an airplane. They already know that skill from their automobile experiences, but tradition (and regulations) drive the airlines to keep teaching this known skill.
Additionally, most of our learning management systems are not able to personalize content for each learner. They are good at “counting and tracking” content that is delivered but not at adapting it to each participant’s reality.
Finally, our current design models are based on finding a common denominator or efficient mixture that will address most learners’ needs.
Ironically, learning personalization happens naturally in one-to-one, on-the-job training. The mentor or teacher naturally looks at, recognizes and adapts to what the learner already knows and their work context, and they can focus on new or difficult elements in the work process.
Scaling learning personalization is way more difficult and therefore not in the current reality of our learning designs, systems or ecosystems. Sigh and oops! So, what might change soon and make personalization a reality in the workplace?
Learners outside of work are already personalizing. Watch how you (and others) learn about a topic when you are away from the workplace. You search for information, skip content that is off-topic, and gravitate to the “just right” content you want right now. Employees will want the same power to personalize learning at work.
AI and smart technology are already personalizing, as well. Online shopping and social engines are using data to personalize their marketing, information sharing and preference selection. In the years ahead, AI will meet and enhance LMSs and talent systems.
Learning analytics will drive personalization. The conversations about data analytics and learning will expand to include the ability to leverage data about each employee that could shape their learning content. We can also aggregate data from the enterprise to assess the impact of different aspects of personalization.
Real-time visual and behavioral responses have great potential. Imagine a learner is taking one of your courses. Could facial recognition, learner gestures, speed of response, and even mouse movements be captured and used to adapt, in real time, the next segment of their course?
Finally, learner controls will increase. A good share of personalization will come from learners themselves as they are given the ability to select formats, content sequence and even the level of feedback they need to master new topics.
I think we need to ask two provocative questions to ourselves in the learning field: First, are we truly ready for the age of learning personalization? And second, what shifts in design, systems, data analytics and compliance are needed to make learning personalization a reality?
We also need to have a deep conversation with our providers of LMSs, talent systems and content systems about their ability to enable learning personalization, or we should look for new ventures that will add that capacity to our ecosystems.
We need to build out our learning analytics talent and skills to leverage the data collections and real-time “data exhaust” that enable learning personalization. Let’s also look at how some K-12 schools are experimenting with “curriculums of one,” which provide each learner with a detailed and personalized course of study every week or even every day, based on data and success patterns. And let’s get personal in design tests with our learners.
They will eventually push us from the learning publishing model to a hyper-personalization reality. They want to be curious and efficient learners versus passive students with hardened curriculums that ignore their knowledge or needs.
Learning personalization is right at our fingertips. Let’s take it personally, now.