It makes a useful analogy to science labs in classrooms around the world. That may seem a bit far fetched. As you read this analogy, don't assume it's crazy. Read to the end before passing judgment. You may be surprised at how apt the analogy is.
When NASA designed the Mars Rover program, it had a number of goals and restraints. Assume that it could consider just about any approach and then had to adapt to the goals and restraints, a brainstorming session. What were the range of options available?
At one extreme would be no trip to Mars. At the other extreme would be a manned trip to Mars. In between is the idea of a remote robotic explorer.
At one point during your brainstorming session, a software developer jumps up and proclaims that you can have a software program that includes all known information about Mars. This program can then simulate the data that a trip to Mars, manned or unmanned, might produce. The program not only could produce data but even could put together simulated images of the Martian surface. Just look at the benefis.
- low cost (compared to a Martian trip)
- complete safety (no astronauts at risk)
- short time (writing software instead of building equipment and sending it to Mars)
- very high cost (compared to a robotic mission)
- extreme danger (never been done before, may not be able to return, etc.)
- very long time horizon (years of preparation, very lengthy trip)
The scientists carefully explain that computer science is not science in the usual sense. It's actually an engineering discipline that produces tools used by scientists and by society.
In the end, of course, the robotic mission wins out as the least expensive real science option for exploring Mars. The scientists have a number of options regarding how to handle the data from the mission. It could be streamed live continually (sort of), or it could be stored on the rovers and sent later. The received data could be stored in a database and available for retrieval at any time in the future, sort of prerecorded for use by many different people at many different times.
While bringing NASA into this discussion does exaggerate the situation, it also shines a very bright light on how best to teach science, especially the use of science labs. In today's discussions of science labs in science courses, you'll find two extremes: those who insist on 100% hands-on labs and those who, with equal vehemence, insist on using simulations instead.
Fortunately, some are finding middle ground. At MIT, they're working on the iLabs project, which allows real-time remote robotic experimentation. Unfortunately, these labs are mostly engineering labs, and the likelihood of covering a reasonable range of science labs with this technology is very remote at this time.
The fact that all Mars Rover data are stored and usable by many scientists in many locations opens up a different approach: prerecorded real experiments. Images, videos, data, and other information can be stored for retrieval by students. The science certainly is as real as hands-on and remote robotics approaches.
The pedagogy depends on the software and the instructors. People who write the software and create the experiment videos cannot also create the instructors. They can only provide software that's easy to use and instructions for correct usage. Better science teachers know how to incorporate science lab experiences into their classes.
Data collection forms a very important aspect of the science lab experience. Data should not be precollected or automatically collected. Just as in a science lab, students should take their own individual data point by point. Each point represents not just the experiment but also student care and judgment, an important factor in understanding the nature of empirical data.
Each video should tell a story and provide means for collecting experimental data. If the video itself doesn't tell enough of the story, then the lab units should be supplemented with text, diagrams, animations, and videos that complete the story: tell the students enough so that they truly understand the details of the experiment.
Finally, sufficient supporting materials should be provided so that both students and teachers are able to succeed. This approach and list form the basis for Smart Science® education, a system of more than 150 lab units for use in science courses from grades 6 through college.
© 2010 by Paracomp, Inc., U.S.A. www.smartscience.net
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