Computer Science in Science PD: Using Computer Models in Science - Discussion


In the lab, experiments (especially those which test complex systems) are often expensive, time-consuming to set up, and hard to repeat with precision. The advantage of a computer model is that they are cheap to produce, easy to set up, and easy to repeat without involving the possibility of human error. In computer models, even randomness can be controlled precisely by defining certain parameters for the model to work within.


With computational models, the students will be able to run more trials within their experiments. Also, they will be able to run their experiments with different sets of variables. This way, they will be able to explore how different factors affect the results.


A similarity is that you can run the computer model using similar variables if you wanted. The difference is that when using the computer model you can change variables multiple times as you obtain more information during the experiment to see how those changes could affect the results of the experiment, but you could revert these changes using the model which would be difficult to do in real world labs.


The computational models allow you to collect data the same way that lab experiments do. I think they are different in that the computational models nearly eliminate human error and allow you to run the same models over again without accidentally changing the wrong variable.


I agree. It’s important for students to be able to complete their projects / experiments while studying the topics. Being able to create simulations means they can still experiment with flight even if the weather does not cooperate.


YES! The most frustrating thing is to repeatedly remind them to only change ONE variable. They have a hard time with this concept. The modularization will help them to see which are the variables, thus being able to isolate only one to change at a time. Hopefully they can then make the transition to hands-on experiments.


I focus on using the Design Process which allows multiple changes at the same time. This is sometimes easier for students if they notice that adjusting several things will help their experiments. However, with some experiments, they try to change too much all at once. Computer Modeling will allow them to make smaller adjustments and understand the effect prior to making another adjustment.


It seems with computational models you can run multiple trials and get more reliable data.


This is always a hard thing for students to grasp so that is a good idea.


Conducting experiments in class in different from using computational models because the experiments in class generally take longer and there is more room for human error. In addition computational models provide larger amounts of data that can often contain more accuracy.


The thought process is similar but with the computational models it is easily repeated as many tilmes as you want.


I think everyone has already said everything I was going to write :slight_smile:


Time is a huge issue with conducting experiments in class when working with a 47 minute period. Setup and clean up take up large amounts of time and it is difficult to continue experiments through multiple days. I feel that computational models are more easily saved and then continued the next day.


I also have to agree that one of my toughest challenges is finding time to go the the store, buy supplies, and do the necessary setup before the students enter the room. It still has to be done, but computational models will allow the students to experience a whole new side of experimentation to supplement the curriculum


One area of similarity between how my student conduct experiments and the experimental design enabled with computational models is that both methods are used to answer some question, create hypotheses and after an experiment, come to some conclusion. One difference is that the computational models allows for easy replication of the experiment (with/without modification to the procedure). This is rarely possible in the classroom lab setting due to limits of time and supply costs.


I agree. I use to work as a lab technician at a university and I share with my students that my job involved repeating an experiment over and over again for a whole year. My boss wouldn’t write it up until she was 100% positive about the outcome. Replication in the classroom is usually not possible in the traditional classroom lab setting. I have limited funds and class sizes of 35+ (200 students total). Computer simulations would take care of this issue.


I really like that computational models can be modified, changed and rerun quickly and easily. This will allow me as a teach to give more open-ended parameters to my students. With physical experimentation I need to give more direction to my students, because we have limited supplies and time. With computational modeling my students can run an experiment, ask new questions, change the model and run more experiments.


I think the CS model is very similar to experimental design I use in my classroom. Both have variables. CS may have fewer constants that need to be considered. Conducting actual experiments in class are time-bound and limited in terms of resources. CS modeling does not have the same limiting factors.


hmmm…wonder how Starlogo Nova could be used to simulate the launching of rockets. If you figure that out, please share.


Our labs are only done once due to lack of time and funds.