In preparing for a talk I’m going to give, I was thinking about how to represent the trends from web 1.0 through 2.0 to 3.0. As I’ve mentioned before, in my mind 3.0 is the semantic web. I think of web 2.0 as really two things, the social read-write user-generated content web, and the web-services mashup web. In elearning, we tend to focus on the former, but the latter is equally important.
However, if we think about web 2.0 as user-generated content, we can think about 1.0 as producer-generated content. The original web was what people savvy enough (whether tech or biz) could get up on the web. The new web is where it’s easy for anyone to get content up, through blogs, photo-, video-, and slide-sharing sites, and more.
Extending that, what’s web 3.0 going to be? If we take the semantic web concept, the reason we add these tags is for systems to start being able to use search and rules to find and custom-deliver content. An extension, however, is to have the system generate the necessary content (cf Wolfram|Alpha). In a sense, by knowing some things about you and your interests, needs, and activities, a system could proactively choose what and when to deliver information.
And that, to me, is really system-generated content, and a real opportunity. It’s not ahead of what we can do (though I recognize it’s ahead of where most are ready to be; why do you think it’s called Quinnovation? :), but it’s certainly something to keep on your radar. And when you’re ready, so am I!

By having smaller introductions that break up the intervention, you decrease the negative effects. The point is to take small steps that make improvements instead of a monolithic change.
The goal is to maximize improvements while minimizing disruption, and doing so in ways that capitalize on previous efforts and existing infrastructure. To do this really requires understanding how the different components relate: how content models support mobile, how performance support articulates with formal learning and social media, and more. And, of course, understanding the nuances of the underpinning elements and how they are optimized.
I’ve had a slight blindspot for photos and video because I peg the ‘conceptual’ meter. I recognize the value, though I don’t play with the files enough (tho’ I took a digital audio/video editing course more than a decade ago, and recently edited home videos for my wife’s birthday). Photos and videos are really good for contextualizing, and that’s particularly valuable for examples (and practice).