I teach 6th grade -to reinforce the steps of the scientific method, I incorporate several hands-on STEM activities which engage the students in problem solving. I would have to really think about how to
incorporate computational modeling with my 11 year old students. And there’s the limited time factor.
They both have controlled experiments that need to be repeated more than once. They are different because coding is more flexible and can reduce human error.
Time is always an issue with labs. Sometimes, I have them share data with each other in place of conducting multiple trials on their own. Using computer models may allow them to repeat the experiment 3 times (or more!) in one period. They may also be able to save it and work on it the next day, which is impossible for many labs since the next class usually needs to use the same materials.
When conducting an experiment in class it is difficult to replicate the same experiment with different variables because of the cost of new supplies, however with computational models they can be easily repeated and the cost is the same. It would also save on time because it would reduce the time for set-up.
In comparison of the experiments that my students conduct in class, computational models can allow my students to change many different variables, rather than just selecting one variable to focus on. The students can perform the experiments over and over again. My students in both types experimental models would get experience with hypothesis testing, using control variables, measuring independent and dependent variables.
In both Chemistry and Computer Science one uses variables in experiments. All good experiments have controlled variable, independent variables, and dependent variables.
I like to send kids of with purposefully general assignments in labs, for example:
“Using the materials provided, find the magnitude of acceleration due to gravity, g, in this classroom.”
Using computer models, I could broaden the assignments to test physically impossible questions, such as:
“Using the model provided, describe the relationship between mass, distance and the acceleration due to gravity of an object in a gravitational field.”
Computational models in the science class has the following advantages over real lab situation
- It is less expensive
- Variables could easily be manipulated
- Data collection could be easily done.
- It saves time
- It allows students to tap into their knowledge by virtually observing the results.
However results from both real experiments and computational models could be used for hypothesis.
When conducting experiments in the classroom, I believe that it is hard for students to always be consistent when keeping variables stable. While using computational models this would be easier for students to change just one variable at a time to see the affect of that change. Once the computational model is written it would also be quicker for students to do the experiment several times and to track their data, while doing an experiment might mean getting all the materials out and having to reset the materials every time which might take several days to get the number of trials needed and the results.
Doing numerous experiments in class can get costly. Using computational models allows for students to take an experiment and change it as they develop their own questions. It allows for students to complete something that may take too long in a more efficient manner.
they are very similar as you are trying to answer a question. The computer model makes it easy to do the unthinkable experiment.
This would be a great way to do science fair experiments. I would not have to change how I teach the scientific inquiry to my students, but this would give them a large choice for projects. Also student could work in together easy on a project.
I think the experimental design process is still fairly similar. It is just easier to control for variables and create repetition with a computational model.
When conduction experiments in the classroom we need to keep in mind factors such as availability and cost of supplies, time constraints, and safety issues. Models can eliminate all of these constraints.
One difference is that we can use abstractions on the computer, where in real experiments we cannot.
Experimental design can become expensive and you can only do the experiment one time, if there is an error the entire experiment can become a disaster. If you use a computational model, you are able to run many trials and repeat for a different outcome or change the variables. Computational makes way for a much simpler process if done correctly.
Moon phases, students create models and predict the future phases of the moon over time. I feel that if they could create these models on line and watch the progression of the moon and it’s phases it would help them greatly.
In class we always focus on controlling the variables so we only test one. I see that this would be similar. I like the aspect of randomness that can be added to the simulations.
I believe that both lab and computational models are the same overall. However computational models can change variables that might be very difficult to change it n the real world.
Models are fast, cheap, and they usually work.