This is a companion discussion topic for the original entry at http://studio.code.org/s/sciencePD-iZone/stage/4/puzzle/4
Science is very much related to computer science. The use of technology is science. The scientific method correlates beautiful with computer technology by using critical thinking and testing variables.
Science is relative to many different things . It is amazing to see how computer science can be used in order to deepen understanding for students , it is a modality that will enhance learning for all learners. Makes it more interesting for this generation to grasp understanding through technology. Since kids are beginning to shy away from the traditional way of reading and writing .
II liked the example given in the video on droughts and water shortage. Students can understand the importance of conserving water in a limited capacity. A computerized simulation will allow them to see the big picture and allow them to see individuals can make a difference within a system of conservation
Computational science expands the opportunities for data gathering vs traditional science course experiments that were the norm when I was in school. Students can use the CS methodology to estimate crop yields or to see the frequency of a genetic mutation. This kind of real world experiment would never have been possible for a middle school student without the use of computational modeling.
Computation science will allow my students to take their ideas and test to see if there is a reality. Many scenarios come to mind …such as alternative uses of energy. How will adding modifiers to a home reduce the carbon foot print. While we work wits models that give us numbers…this would allow us to see the impact on reduction of use of fossil fuels in a more detailed picture.
Things that I learned in science class in school can be illustrated more accurately by using computational science. Many things that we learn in science class are much more complex in real life & hard to accurately model. Computational science allows us to more accurately model and experiment with science phenomena. For example, when learning about ecology you don’t have the time or resources to observe an ecosystem long enough to see any long term effects. If you model an ecosystem using computational science then you can change variables (predator/prey, etc) and watch the results quickly thereafter.
That would be neat to have an accurate simulation of the large scale impact of alternate energy sources. If one does exist, it would be interesting to see what kind of feedback they receive from big oil. Ha!
I like the merge between mathematics and science in computational science. There are many natural disasters such as flooding and forest fires that are difficult to expect its effects on urban and residential places. It would be great to obtain a map of flooding zones and use computational science to make a plan for evacuation. You can plan for the worst scenario by changing variables and observe the result. This kind of data gathering and simulation can be done successfully using computational science.
Real life questions posed in science investigatons would connect science to the world for my middle schoolers. It moves beyond your basic experiments. For example, many of my kids have asthma. If they could use computational science to answer why higher cases of asthma exists in the Bronx than any other borough that would be way different that the investigations I did in school.
What is similar between the Science that I learned in school and computational science is that both are all about identifying/defining problems and finding ways to solve them. What’s different are the tools and approaches used. In the Science that I grew up with, the tools used were lab equipment (like microscopes, beam balances, rulers, spring scales, thermometers, etc.), while in computational science, the tools used are computer software and machines/gadgets or “robots.” In terms of the approaches used, conventional Science uses the scientific method (problem identification, hypothesizing, experimentation, data gathering and analysis), while in computational science, the approach involves roughly the following steps: selecting a problem in the real world; making a simulation; making a computational model using math algorithms; translating these into a computer code; and then testing the model to find the solution to the problem.
Thinking back to my formal, K-12 science education experience this idea of computational science seems foreign. When I was in school the focus was memorization of facts relating to science - we didn’t delve into modeling the impact of changes in complex adaptive systems, for example - we were just supposed to take at face value the lessons our science teachers imparted. I’m happy for the change though - computational science can demonstrate for our students real life ripple effects, such as how changing one item, such as raising the average temperature on Earth one or two degrees can have wide ranging impact. This kind of project, due to its vastness and time span, could not be done in a traditional science lab.
Everything I learned in school was very hands-on, and we were very much limited by the materials and the practicality of acquiring certain technologies. Computational science removes these boundaries and allows us to perform experiments that would be otherwise impossible in a classroom. Some things that are possible with computers are the study of change over long periods of time that would be impractical to observe live.
The science I learned is school was pure memorization. The labs we had involved very little technology except microscopes.
there are many correlations to science and computer science today. It can be used to help enhance our learning and broaden our understanding of concepts that are hard to conceptualizer on a small scale.
Sometimes, our schools are underfunded. Conducting a computational science project could overcome the funding challenges we as teachers face in the classroom. I would say I would experiment on showing how body systems work inside our bodies, weather nature disasters (tornadoes, earthquakes, etc). A good project would be for students pretend being scientist and work together in order to predict and help out evacuate communities. Recently on PBS, they screened a film called the Big Fire and I thought how my students could learn a great deal from it and come up with ideas to study weather and assist save lives.
The method I was taught science involved memorization and some labs. Computational science would allow my students to come up with a “What if” scenario and see the possible outcomes. One example that comes to mind would be the affect of pollutants introduced into a watershed.
For many science disciplines, computers provide the ultimate set of tools - they are cheap, smart, quick, and safe for conducting investigations/experiments. I didn’t do any computers in my high school (1970s), but mainframe computers were clumsily used in college engineering courses and we had an early PC that used an early version of Excel.
An example would be testing real-size steel girders for stress tests under full building loads.This would be quite expensive and perhaps dangerous to build and test in a lab, however stress-test modeling is probably quite simple and would certainly get quicker and cheaper results.
In HS we did not use computers (1970s).In college we used mainframes clumsily for a few engineering courses. I even used an early PC with a similar spreadsheet to Excel called Visicalc.
My simulation (now) would be a virus that mutated as it was transmitted from birds to humans. It is now a deadly bird flu epidemic quickly spreading. The agents are: birds, non-mutated and mutated viruses and humans. The environment would be air and shared spaces for viral transmission.The interactions are virus/host reproduction, mutation, people-to-people passing of virus, deaths to viruses and humans and birds.
I agree with you Carol. The two disciplines are very much related. Using technology definitely enhances the science curriculum and allows all learners to be engaged. It definitely encourages critical thinking.
Science is similar since they are both subjects that follow parts if not all of the scientific method to solve a problem. An experiment might be to have the students create a pedator and prey model using computer technology which can not be done in a science lab.