How cool to be able to change the variables as your students work through the models?
In my science classroom we spend a lot of time emphasizing the key components of experimental design like identifying variables, forming testable questions, developing a hypothesis, and testing that hypothesis. These key concepts are shared by the process of experimental design and forming computational models. The main differences I see between the two are the ease of making adjustments to the original design and running multiple tests. With limitations on time and materials, multiple tests arenât always feasible in the classroom.
I agree! One of the reasons students enjoy science so much is the âhands onâ component. I think the computational models are great for those concepts where it would be difficult for students to participate in something hands on. I certainly see value in both experiment types.
As resources increase, so will my ability to run additional experiments in my classes. I think the variables regarding experimental design with computational models make it so much more fun and interesting for the students compared to just conducting an experiment in class. They both have their place in the classroom and outside the classroom but, if we are being real, in my opinion, the student needs to know how to conduct experimental design with a computational model for his or her future related endeavors.
Similarities in Science and computational science both use models. In science models looks like real one, while computational models looks like real ones and can be program to function like real. The model can be used to observe the behavior that a scientist wants to study. Computational model can be used in different ways in computer. One can manipulate different variables and come up with a lot of data.
In the lab and with computational models students observe, gather data, analyze and interpret data to come up with conclusions. In computational science simulation is run in computers so the model can be used in different ways to generate large amount of data. More data reduce the percentage of error in an experiment.
My students use the science inquiry which is taught at the beginning of the year. With the science inquiry, I have five classes for between 50 to 60 minutes each day, Therefore, time can be a factor in completing a lab and limited amount of materials. Using the computational models, the science can still be used and they would have design it in their groups. The students would have the opportunity to repeat it.
For me the current space is an issue. I donât have a lab room and when students do labs and experiments it is very hard for them and me especially seeing 3-4 classes per day. Also, the cost of materials is another factor for not being able to conduct many experiments in class. Therefore, having students conduct experiments with computational models will allow students to run it multiple times and easily change variable to observe and record changes and results which will also help students make hypothesis easier. For instance, when students are learning about the seasons, they can change the tilt or the distance of the earth from the sun to observe and communicate changes that occur.
The creativity the computer models allows is exciting. As students observe the experiment they can explore their âwhat if ideasâ immediately.
Good point, one of the big misconceptions in nature of science for my kids is that if they observe it once, they assume it occurs that way every time.
The problem I see is keeping the balance of time to create a valuableâmeaningful curriculum to challenge students.
I have learned that computational models allow easy experiment repetition to ensure result validity. It is also simple to adjust a parameter and see the outcome. I like the idea of students performing a hands-on experiment first (when possible) so they have some concrete ideas for developing the computational model.
Yes . . . this is a big plus!
When I set up an experiment in class, I always have a component that will have students think and try to figure out what the outcome would be. An example would be in testing the insulation value of household items. Many think sand is a great insulator, but in fact it is not. We test everything from cereal to cat food. Cotton and grass clippings work the best.
I do a bacteria collection lab with my kids using agar and petri dishes. We keep them warm and the kids observe and record their swabs every day for 4 days. Some kids (not very many) swabbed the lid of the dish, and not the prepped agar. With computer simulation, these kinds of errors would carry less impact and the students wouldnât be a day behind everyone else. Also, kids could âswabâ multiple locations with a computer simulation, whereas financial constraints limit two locations per team for sampling.
That sounds like a great lab! I am surprised about the grass clippings! Is computer modelling going to open up the range of possibilities, or do you think kids will end up with the same findings as your classroom lab?
In lab experiments and using the computer both engage the students in experiments. However a computational experiment can be repeated many times with the same results, or you can change selected factors in the repeated experiment.
This is so true, It will save me time and money. Running to pick up materials and setting up 4 labs a week is often time consuming.
This is a wonderful way for students to understand that most times scientist take years, and years before answering their questions. They also often find answers to unasked questions along the way.
The benefit to this method is the freedom to run the simulations more than once. The slight modifications you might discover are needed during the running of a model can be easily changed and run again. This can allow for a greater amount of data collected and can lead to better student learning.
What an excellent point you make about the unanswered questions. This can be a way for more student questions to be answered in a shorter amount of time.