Here's what we distributed at the beginning of project #2. We haven't developed any additional guidelines for the writeup, but as with project #1, photos, drawings, work sketches, and other materials are welcome, as a well written (correctly spelled, punctuated, generally literate) report. The quality of the report is important to us; reports that are just 'thrown together' will fare poorly; those that exhibit care and effort will receive more consideration.
Project II is to design, construct, and test an exhibit for a museum, gallery, or public space (e.g., the ITLL lobby). The exhibit should offer knowledge, enhance understanding, provoke curiosity, or otherwise catalyze learning about a principle or phenomenon about the natural or human world. The exhibit, which must incorporate a significant degree of computation, may be designed for children, adults, or both; for the general public with little experience with science, or for a more sophisticated audience.
What kind of science? Any science you like. Mathematics, physics, chemistry, biology, psychology, sociology, and computational science are all fair game. Naturally, it will help if you have a good understanding of the science you are trying to explain.
What kind of exhibit? We see various forms the exhibit could take. For example, imagine a pair of shoes like the sneakers that Glenn described in his talk on wearables, that measure and display the force and acceleration of your footsteps. Or imagine an exhibit in the form of a game in which various participants work together at some kind of collaborative (or competitive) task. Or imagine an environment (like the Exploratorium imaging wall). Naturally there's nothing wrong with the usual stand-alone walk-up museum exhibit.
What kind of computation? We don't require that you use the crickets for this project, although we hope that some of you do. We do want the computation to be embedded in or integrated with something physical. That is, a purely Web based learning environment does not fit the bill, no matter how sweet it is. In our discussions, we have thought of at least two ways that computation can be integrated into the exhibits. One, computation (e.g., crickets) can be used to sense, measure, or effect a physical or social phenomenon. For example, a computer can sense temperature, count people, or trigger sound, heat, or light. Two, the science phenomenon can be computational itself. That is, the exhibit can be about something computational, or can offer a simulation of some complex real world phenomenon. For example, the exhibit could use crickets to explain the functioning of simple neural networks. If you think of another way to integrate computation into your exhibit, check it out with us.
What learning? We do care very much that the exhibit have a point and that the point comes across to the audience. We'll ask, 'what can we learn from this exhibit?' We expect that interpretive text will be needed to communicate with the exhibit audience. The design of this text may be crucial in making the exhibit function not only as a curiosity, but as an opportunity for learning.
What about art? Yes, we also care that the exhibit you design and build is a work of art. That is, we care about the level of craft in construction, the aesthetic experience that the exhibit offers, its ability to attract people. This does not mean it has to be beautiful (although that's not a bad idea). It can be terrible, fearsome, intensely ugly, or hilarious. But it should be fantastic, outstanding, or amazing.
What about craft and construction? One of the main criteria for successful exhibits is that they are robust. Real museum exhibits must last months. We'll require that the exhibit you build be sufficiently robust that we can leave it in a public space for a day. (If we can figure out how, we may do this!).
What else we'll want (in addition to a working project and a demonstration including an oral presentation that includes all of the team members):
-a project report, along the same lines as the last one. We'll probably add additional categories to the outline that address the science content itself and how you expect the learning to take place; we'll let you know the exact format at a later date.
- a work log (again). The most successful logs from Project 1 included descriptions of design challenges, dead ends, major changes in plans etc. This is not to say that you have to go in search of dead ends, but we doubt that your project will go completely smoothly.
-a statement from each person individually about "What I learned in doing this project." Part of the reason people work in teams is because no one person has all the necessary knowledge to complete a complex task. In the process, everyone (hopefully) learns something new. We hope - and ex pect - that each of you will learn something, and we want to hear what it was. We also hope that by thinking about this requirement from the beginning, you will set out with the explicit intention to learn something, rather than just doing what you already know how to do.