The Total Learner Experience

Hyperlearning Creates Smarter Content

I was trolling through an article in Wired magazine when I read about a computer science student at Carnegie Mellon who is working on creating computer experiences that people can engage in synchronously with a specific goal or objective in mind.

This got me to thinking about what we do as learning developers. We are focused on creating computer-driven experiences designed to make people smarter. Our content (at least in the Web 1.0 arena) is often linear and travels one-way: computer to learner.

But what if we focused less on making sure our content was "the best it could be" before we disseminated it in a one-way route, and relied more on learners to ensure its validity, evolve it as it needs to be, and make the content smarter (as well as other learners)?

We even measure results in an old-style model: After the learner consumes the content, did performance improve? This seems slightly unbalanced, since in reality, we are rarely disciplined enough to seek and observe whether or not an improvement in performance was actually realized (and in most global working environments it is hard to determine).

By harnessing the power of hyperlearning (in this iteration: synchronously linking two or more learners) to the same content at the same time, we can enable a process wherein these linked learners will work together to make the content smarter.

In the Wired article, the student designed a matching game where two players saw the same images at the same time on different computer terminals, and added metadata describing the photos. The players theoretically built a database of search terms for the images, which after evaluation were shown to be much more accurate descriptors of the data than what a computer could produce itself (how many times have you conducted a Google image search and retrieved images that just didn't seem relevant to your original query?).

If our linked learners can be synchronously paired to our learning content, and are provided a mechanism to evaluate, reflect upon, review, and/or add to the content in real time, we would be able to detect trends that may very well help to make that content smarter.  By looping the evolved content back through the system and making it available to others, we in turn not only make the content smarter, we are able to share it to others with related interests.

That in essence is the power of social learning on a connected platform. We just need to divorce ourselves of thinking only about one-way dissemination of content. By linking learners synchronously, we will build richer learning experiences. Naturally, we provide the linked players a reward mechanism: vital to making the experience fun (otherwise, people won't do it). And of course, my bias is to design game experiences to facilitate this -- our learners would be much more interested in doing some of the "work" for us by making better content, if we let them have fun while doing it!

To begin, we have to throw off the shackles of rigid, SCORM-compliant learning management systems... but my disdain for SCORM is the subject for a longer rant...

Try one of the labeling games here. Or this really cool web treasure hunt game.

Or here for a whole mashup of linked brainpower games. 

Digital Immigrants vs. Digital Natives

In today's world there are now two kinds of learners: "digital immigrants" and "digital natives."

Digital immigrants came of age before technology revolutionized learning, and they often struggle to adapt to new rituals and protocol.

Digital natives instinctively adapt to technology and expect it to be available to assist them in the ways they find most appropriate for their specific needs.

Texting is one example of the divide that exists between digital immigrants and digital natives.  

The United States lags behind most of the industrialized world when it comes to texting. There were about 176 million texts sent between cell phones in the United States last year. Next year that number will increase to 1.5 billion. By comparison, there are an estimated 30 billion messages exchanged every month in Europe.

The Chinese, who embraced this technology years before it arrived here, send over 300 billion text messages a year. Half the 13- to 15-year-olds in Australia own cellphones. In Japan, texting is so prevalent that Japanese teenagers are called the "tribe of the thumb."

As learning professionals, we must assess how technology transforms the way digital natives communicate, and analyze whether or not we should integrate new communication channels into our learning interventions. If so, we must also design to enable digital immigrants to grasp the new delivery method.

Why is texting a potential useful tool for learning? Consider this:

• Texting is perfect for viral messaging to specific audiences, especially those that may not have high-bandwidth internet connections.
• Texting works great for short messaging, including reminders of important events such as the availability of new learning objects, upcoming classes, and key nuggets of information.
• Texting can also be used to query web services, such as Twitter. One useful application is to obtain an instant weather or traffic report. For learning, simple queries could offer true on-the-job performance support, i.e., send a direct query to a content object for a reply to a CLI command, a price quote during a sales inquiry, or a status on the availability of an offering.

More than likely texting may have a short life-span, especially as portable devices focus on ease of e-mailing. For example, Apple stressed e-mailing in its iPhone instead of multimedia messaging.

The broader lesson for us to grasp is the ability to leverage communication channels effectively to ensure we can offer information in a suitable format for digital natives, while also supporting the transitioning digital immigrants.

Microsoft is Dead

Don't know how well this essay has propagated, but this guy has it spot on in his arguments as to why Microsoft is dead. Long live open source, eh?

Intuitive Assumptions Lead to Faster, Better Analysis

Needs Assessment

• Needs assessment is a systematic effort to determine the difference between a model situation and the actual situation and to determine the type of performance problem or opportunity the differences indicate.

Needs Analysis

• Needs analysis is the process of completing a root cause analysis of high priority needs and selecting solutions based on their advantages and disadvantages.
  

Connect Analysis With Intuition

• I recommend a 6-step iterative process to determine the most responsible performance intervention based on the results of needs assessment and analysis:

1: Omit non-value-added activities	Ask this question: What is better -- cooperation or competition? Can we build cooperative competition? Can we create serious fun?
2: Avoid unnecessary interventions	When there is not a lack of skills and knowledge, the gap may be a motivation problem. Approximately 60% of training interventions address motivation -- which may be a waste of valuable training time. Training may not be able to sufficiently address a motivation problem. Don't create training just for the sake of creating training.
3: Limit analysis	Usually we can get 80% of the information we need in the first few minutes of analysis. We quickly find out who needs to learn what. The client can assist us in making intuitive assumptions about needs, tasks, and learner characteristics.
4: Survey the audience	Talking to as many people in the target audience can provide insight that may not come through otherwise. One group shouldn't dictate the problem without consulting the affected parties. One problem with traditional change management: many times the directives come from the top-down. Bottom up changes may be more sustainable!
5: Design metrics for monitoring negative consequences	Think about this: is your cell phone a problem or a solution? More than likely, it's both. Sometimes there are no problems or solutions -- in many cases the actual state and the ideal state both have advantages? Performers may look at the actual state as ideal because they are familiar with it. One question they may ask: who designed the ideal state?
6: Agree on metrics related to business strategies	Keep the process as simple as possible, and relate the solution to the business strategy defined. If you can't map the prospective solution to a business need, question the need for the solution.