Page:A Review of the Open Educational Resources Movement.pdf/69

 sim clip can be rendered visual and tinkered with in and out of context. Building a multi-scale complete simulation of the human body is enough of a challenge, let alone finding an architecture that is flexible enough to allow thousands of people to contribute in ways that compose and recurse.

Such a simulation would be of use to learners of all ages and again could yield an infinite number of grounded conversations—not just random blogs talking to each other, but rather create a context in which you run a simulation to prove your point. Now the contested ground becomes the quality and validity of the simulation and the interpretation of its results. The twenty-first century is a century of biology, yet we are creating the visualization tools, the simulations, and workflow environments to get a feeling for this domain. The simple magic of the cell as machine and how that machine works is awesome. For some of us, the movie “The Fantastic Voyage” had images and drama in it that still years later are cemented in our mind. Think about creating machinima movies based on experiments or simulations composed from the sim clip library. This raises the question of whether NSF and NIH will expect most anything they fund to eventually be folded into a simulation of the subject. All the above suggests that we are shifting from static content to increasingly active content that is hopefully more and more systemically integrated.

Content was king, and open content we hope will be even more royal, but perhaps today the ruler is content and context. In the digital era we can start considering many different contexts in which learning will transpire. The learning-on-demand scenario has already transformed the need to spend all one’s time memorizing facts. Google becomes a living index and repository for enormous content. We now live in a world of abundance where editing and curating become more crucial than ever.

It is under-appreciated how Google has empowered the geek generation to be fearless in picking up new languages, etc. Why? Because language compilers, integrated debugging environments, and operating systems generate error codes when they get stuck. An error code is meaningless to a human but it does wonders as input to Google. Just type it in (plus the system you are using) and instantly Google gives you pages and pages of fellow geeks who have encountered that same error code along with what it means and what to do about it. This has allowed, for example, a 60-year-old colleague to run a one-person software shop to confidentially master Java and Enterprise JavaBean (EJB). He was not going to go back to school; he accepted a task to build a system in EJB using Google as a primary (open) resource.