Somemay argue that, since the inception of ADDIE, training design hasremained relatively consistent and grounded. There have been somemodifications of the acronym, or even, in some cases, a rebrandingwith a different name entirely.
As training designers we have ADDIE,Rapid Prototyping, the Dick and Carey Model, and a number of othertools to help us develop training courses and instruction. Eachmodel has its critics, and there is no shortage of critics. However,one step that is available in every model has gone relativelyunnoticed. This step takes place early in most of the processes andwe could argue that it can determine the eventual ROI. This step isthe Learner Analysis.
Theprocess of boxing our future learners into a demographic profileremains common practice. Learner Analysis 2.0 is the process ofaggregating semantics about our learners (particularly their likes)through their digital feedback. It’s sort of like getting a pulsefrom the crowd based on observations. The difference is theobservations are compiled through the learner’s digitalexperiences. Learner Analysis 2.0 has as its premise the assertionthat 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 (withor without purpose), you reveal the “digital you.” It’s hard toargue with the idea that, “We are all creatures of habit.” Eventhe most spontaneous among us is still grounded in some form ofroutine. 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 dowe do what we do (on the Internet)?” The answer to that is farmore important than your sex, your education, your age, or many ofthe other typical demographic boxes that sculpt how we designtraining and instruction. That’s not to say those are invalid, butwhat 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 tosee how forward-thinking marketing entities were recognizing that youcould see people’s buying motivations through social media-likebehaviors. One TED TV episode by JohannaBlakely of the Norman LearCenter at USC in southern California stimulated my interest inthis theory.
Blakely titled her TED Presentation, “SocialMedia and the End of Gender.” Although she approaches the topicfrom the perspective of marketing, I see many analogies to trainingand instructional systems design (ISD). She argues that (based onLear Center research) the “Old School Demographics” (age, sex,gender, etc.) for describing a potential buyer are far less usefulthan an understanding of what the buyer “likes” based on thedigital feedback they leave behind via Social Media. She explainsthat Social Media allows us to transcend our demographic boxes,revealing our true motivations and impulses. People aggregate farmore 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 itsusers. Popular sites like Digg and Reddit aggregate content based oncommunity feedback. If a community “likes” a post, that post iselevated. How much of corporate learning content is democratized? Inmy experience, very little is learner-generated or promoted. Learningand Content Management Systems usually take a top down approach andtypically accommodate Blakely’s “Old School Demographics.” Whatif learners guided content design and delivery through their digitalbehaviors? As a learner yourself, would this matter to you? For thislearner, I would have to reply with a resounding “YES!” Lifetoday is customized (or at least becoming more customized than in thepast). Why can’t learning be customized and democratized?
Executing an idea seems to be more of a challenge then generatingone. The concept of Learner Analysis 2.0 is no different. Thisis especially true in organizations that still run away scared fromSocial Media. I pray for them every day. The tools to accomplish thisare not conceptual. They are actual and available. Net neutralitycontinues to fertilize the soil for even more social-media tools tospawn and flourish. The next steps would be for us, as training andinstructional 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.
