Computational mode requires students to use true inquiry. No procedures to follow and the scientific method will be much more authentic. You can do the same with traditional hands on but when the students get what I like to call “outliers” they can repeat the trials with ease using computation and probably well within the 45 minute instructional block.
Computational models allow students to change variables and do experiments over and over again without the added cost of doing experiments using the physical materials. it gives students to try out things you know won’t work, but they get to experience it and see what happens instead of just listening to the teacher tell them another answer to another problem.
I agree with you. There must be a way to provide both enriching experiences.
Time, space, resources, and many other outside variables affect the “science lab/experiment” in my STEAM block classes. I see the value in providing both the traditional experience and the experimental design with a computational model. Students will absorb both and will continue to utilize skills gained from both practices.
Similar in that they both are trying to model the same phenomena, but very different in how deep you can take the usefulness of the model.
Comp Models allow the student to manipulate the agents within the model\experiment, which then allows them to see the 1st hand affect of each Agent and its parameters. Students will witness the change, not just model the before and after.
One factor is to eliminate human error as much as possible. For example measuring the exact amount of ml of liquid that may be needed for an experiment. It appears in computer assimilation the measurement would be exact because you are inserting the amount that is needed no one is pouring a liquid into a cup. Another factor is time and space, in a traditional hands-on lab, clean up and distribution can take away from the actual time of running an actual experiment, and nay need to be completed over several days, Where as with (CS) there is no clean up, it appears that you can run a couple of trials in a given period.
I agree with you. It will allow the students to explore.
In the types of experiments we typically do in class we don’t have enough technology to do computer models. So we have always used the students as agents to model a phenomenon. While this is great, it only allows for one run-through so students often miss the importance of multiple trials or fail to see the impact of the “randomness” built into the activity. I think it would be great to start with this type of model and then have the students translate it into a computer model.
Computer models also eliminate human error in the form of cheating, misinterpreting rules and directions, inaccurate measurement, etc.
Computer Models allow for experiments to be repeated a multitude of times with varying variables with little to no cost (aside from time).
Due to limited resources, it is very difficult to conduct complex experiments in middle school science. Students learn the basics of questioning, hypothesis development, step for experiments, etc. It is often difficult for them to anticipate all of the variables that can impact an experiment, so often their data is invalid due to lack of regulation of a variable. It is most often not possible for the experiments to be repeated due to the need to move on to more curriculum. Using computational models would eliminate this problem, allowing the students to make as many mistakes as necessary for them to see the whole picture and then to complete their experiment. It would also allow us to tackle bigger issues than which hamburger has the most preservatives.
I’m excited that students will be able to “do science” in the time allowed in a middle school schedule. Instead of trying to get through before a bell rings on an experiment, the student will be able to return to the process at another time and the results will be better. Students can also look at long term effects within a model that would be impossible to do in a regular classroom setting.
Computational science allows the student to concentrate on a fixed outcome. This model would help give focus on the desired outcome of an experiment.
Using computational science gives students the flexibility to manipulate their experiment so that they have a very good understanding of how to keep experiments controlled and look at one specific variable. Students could test concepts that could easily reach outside the classroom.
In class, students use the steps in the scientific method to establish the parameters of the experiment and guide them through the process. With the constraint of time, repeating the lab is not possible with regards to data. Using computer models, students can repeat the experiment as many time as possible (and I hope work on the program at a later date) and manipulate variables to see how outcomes change. This would give them great insight to how/what variables can do to within an experiment and the importance of controlling everything you can so that data is solid.
My students conduct various hands-on experiments throughout the school year using the scientific method. Availability of space, materials, and class time can be limiting factors when it comes to planning high-quality experiments, and multiple trials are rarely an option. However, hands-on experiments are crucial to scientific inquiry, and the flexibility offered by the use of computer models/simulations has the potential to be a wonderful way to supplement classroom learning and experimentation.
I also agree, another limiting factor at my large school is that we may have several sections of a course running at the same time, meaning that teachers have to coordinate use of materials and transferring the materials to different classrooms. There has been times when I could not teach the lab on the day I planned because another teacher was already using the materials. With the computer modeling, materials sharing would not be as much of an issue.
Computer modeling in some learning scenarios could be a more beneficial learning activity for students than a traditional experimental design process. I believe there are some concepts in science that lend themselves better to computer modeling than experimental design and vica versa.
Typically, in our maker lab, we invite students to create something and then test out its ability to perform. A student may make an airplane and try to fly it. If it succeeds, they are done, but if it could fly better, they may go back and redesign the plane based on another idea. Computer modeling would allow students to see what successful design might look like before they build, or use computer modeling to improve their physical designs. It seems that computer modeling would be a great improvement to speed up the process of successful design or to save on materials.
The Computational Experimental Design model is very similar to the one that I am familiar with. The only difference is asking what is the range of values you will use for each variable.
The computational model allows for students to not only repeat their experiments, which should always be encouraged, very easily, but they can also then change things about their experiment and see how the outcome differs. This will encourage them to think more openly about science and will help them form better hypothesis in their experiments and be more certain of their conclusions.