The Path to Learning Personalization

January 30, 2014

Personalization is one of those big, broad terms that can mean different things to different people. I'm a big fan of how Richard Culatta from the US Department of Education defines it. He says personalization is the sum of three factors: adjusting the pace (individualization), adjusting the approach (differentiation), and connecting those to the learner's interests and experiences.

That's a tall order – and for most learning and development organizations, it's not going to happen all at once; rather, it's going to be a journey. Today, we're seeing high-impact learning organizations take their first steps toward personalization by embracing modern content development processes and adopting new technologies for content delivery and tracking. These smart companies are steadily deploying multiple layers of personalization, each building upon the previous ones to reach the holy grail of personalization: a one-size-fits-one experience that rapidly drives the desired learning outcome.

Let's take a look at this journey from the learner's perspective:

I see content that matches my individual user profile – job role, location, clients, etc. – and I choose how I will navigate and interact with it. Xyleme - The path to learning personalization In this scenario, user profile data is matched to content metadata to filter out content that is not relevant to me. Like the other social networks I use, I will like, follow, favorite, and create personal playlists and channels.

I see the highest ranked, most viewed content first. I can also provide direct input about the content. Here, personalization is taken a step further by determining the best content based on ratings, reviews, and usage. In addition, user comments are leveraged to continuously improve the content.

I see only the content relevant to my situation or task at hand and retrieve it from any device at my disposal. This is where personalization intersects with performance support to deliver moment-of-need content.

The type of content I am served is based on my activity history.  At this layer, enough tracking data about me has been accumulated to understand my desired learning approaches and to deliver content in my preferred format.

The path to personalization arrives at its desired destination when we reach a one-size-fits-one learning approach based on a personalized, recommended path to success. This is where the promise of big data comes to fruition. Sophisticated algorithms assess my knowledge and/or skill gaps (e.g., unsatisfactory KPIs, an inability to complete tasks, pretest scores, etc.) and then use all of the information gathered through earlier stages to drive personalized recommendations.

So, what we can see from plotting our journey is that many organizations are already on their way toward personalization – perhaps without even realizing it. As we get further along, what we need to ask ourselves is: What do we do with all of this personal learning data? And, how does it help us in our quest to deliver bigger and better business outcomes? Stay tuned...

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