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App Fusion: Learner Analysis 2.0

by Terrence Wing

March 3, 2011

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by Terrence Wing

March 3, 2011

“Why do we do what we do (on the Internet)?” The answer to that is far more important than your sex, your education, your age, or many of the other typical demographic boxes that sculpt how we design training and instruction. That’s not to say those are invalid, but what we “like” seems to be a much stronger demographic.

Some may argue that, since the inception of ADDIE, training design has remained relatively consistent and grounded. There have been some modifications of the acronym, or even, in some cases, a rebranding with a different name entirely.

As training designers we have ADDIE, Rapid Prototyping, the Dick and Carey Model, and a number of other tools to help us develop training courses and instruction. Each model has its critics, and there is no shortage of critics. However, one step that is available in every model has gone relatively unnoticed. This step takes place early in most of the processes and we could argue that it can determine the eventual ROI. This step is the Learner Analysis.

The process of boxing our future learners into a demographic profile remains common practice. Learner Analysis 2.0 is the process of aggregating semantics about our learners (particularly their likes) through their digital feedback. It’s sort of like getting a pulse from the crowd based on observations. The difference is the observations are compiled through the learner’s digital experiences. Learner Analysis 2.0 has as its premise the assertion that every click of the mouse reveals something about the learner.

The mechanics of Learner Analysis 2.0

Let’s take your Internet behaviors as an example. As you surf (with or without purpose), you reveal the “digital you.” It’s hard to argue with the idea that, “We are all creatures of habit.” Even the most spontaneous among us is still grounded in some form of routine. Our use of the Internet is no different.

  • We visit specific sites routinely.

  • We click on certain media routinely (photos, videos, text, etc).

  • We even visit the Web based on a routine.

  • We prefer one browser over another.

  • We use specific social media sites over others (Facebook, LinkedIn, Twitter, etc.).

  • We sign off at specific times.

  • We spend more time on certain sites.

  • We leave comments in one area and no evidence of our existence in another.

The significance of this information lies in the question, “Why do we do what we do (on the Internet)?” The answer to that is far more important than your sex, your education, your age, or many of the other typical demographic boxes that sculpt how we design training and instruction. That’s not to say those are invalid, but what we “like” seems to be a much stronger demographic.

Marketing, media, and motivation

I was inspired to write about Learner Analysis 2.0 as I started to see how forward-thinking marketing entities were recognizing that you could see people’s buying motivations through social media-like behaviors. One TED TV episode by Johanna Blakely of the Norman Lear Center at USC in southern California stimulated my interest in this theory.

Blakely titled her TED Presentation, “Social Media and the End of Gender.” Although she approaches the topic from the perspective of marketing, I see many analogies to training and instructional systems design (ISD). She argues that (based on Lear Center research) the “Old School Demographics” (age, sex, gender, etc.) for describing a potential buyer are far less useful than an understanding of what the buyer “likes” based on the digital feedback they leave behind via Social Media. She explains that Social Media allows us to transcend our demographic boxes, revealing our true motivations and impulses. People aggregate far more often around common “likes” than they do around age, gender, education, etc.

Community-mediated content

This also brings to mind sites whose content is democratized by its users. Popular sites like Digg and Reddit aggregate content based on community feedback. If a community “likes” a post, that post is elevated. How much of corporate learning content is democratized? In my experience, very little is learner-generated or promoted. Learning and Content Management Systems usually take a top down approach and typically accommodate Blakely’s “Old School Demographics.” What if learners guided content design and delivery through their digital behaviors? As a learner yourself, would this matter to you? For this learner, I would have to reply with a resounding “YES!” Life today is customized (or at least becoming more customized than in the past). Why can’t learning be customized and democratized?

Executing an idea seems to be more of a challenge then generating one. The concept of Learner Analysis 2.0 is no different. This is especially true in organizations that still run away scared from Social Media. I pray for them every day. The tools to accomplish this are not conceptual. They are actual and available. Net neutrality continues to fertilize the soil for even more social-media tools to spawn and flourish. The next steps would be for us, as training and instructional designers, to start collecting this data (this VOICE) from our learners. The next time you stumble on a “LIKE” button, think about Learner Analysis 2.0.


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Hi Terrance.
Interesting article and points made here.
My question is, where is this information stored for us to access it from? How can I see what social net trends people are using? is there a privacy issue associated with gathering this information?. I feel there is a much bigger side to this article than specifically the point you made.
Good work :-)
Hi Benny,

Unfortunately, this perspective is emerging so there aren't any studies I could find relative to learning. Most of the data on this is related to marketing and advertising. For now we simply have to extrapolate the learning relationship from this data. Mashable has published a few articles and I would definitely suggest going to Johanna Blakely's site at the Norman Lear Center for her research on the topic. Hope that helps. - Terrence Wing
Hi Benny,

I re-read your question and I don't think I answered it in my response. So, here goes again. The way to capture this data is to embed it in your courses and have your LMS capture it. Most LMS are very capable of gathering user data. I hope I answered the question better this time. -Terrence Wing
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