Frequently Asked Questions

  1. How are these simulations made?
  2. How do the models work?
  3. What do I do if my school blocks this website?
  4. How can I support this work?
  5. Are there other ways I can support this work besides Patreon?
  6. How can I get a specific quantity at different time intervals in a simulation?
  7. What is the difference between a comparative simulation run and a live simulation run?
  8. Are there worksheets to go along with the simulations?
  9. Are there answer keys?
  10. How are these simulations used to practice science? (How are they used to teach the Scientific Practices?)
  11. How can I practice statistics to support or reject hypotheses using these simulations?
  12. How can I use these simulations to practice the different forms of inference to practice scientific reasoning?
  13. Who is Jon Darkow?
  14. Got a question?


How are these simulations made?

These models are made using the system dynamics software, Stella from iseesystems inc. To create your own free system dynamics models you can use Insight Maker or Vensim.

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How do the models work?

These simulations are system dynamics models. The models are for teaching complex biological systems. Many of the units and relationships do not reflect current scientific consensus. That is not the primary reason why I build the models. I build the models to show non-linearity, feedback loops, leverage points, and other relationships of the natural world to teach students how science builds knowledge from complex systems.

After I build a model, I build an interface. The interface is what you see in the simulation. When sliders and buttons are changed, it changes the initial conditions of the model. When students run the simulation, they are running the model according to the initial conditions specified by the interface.

The simulations are running in HTML5. (I have deleted all simulations that were running in Flash. If you cannot see the simulations, then most likely your school filter is blocking the simulation.

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What do I do if my school blocks this website?

Make sure all of the following URLS are NOT being blocked by the school filter.

http://www.jondarkow.com , or https://sites.google.com/site/biologydarkow/, and

https://sims.iseesystems.com/

The third link is where I publish my sims to. The first two links are to make all the sims more accessible.

All of the simulations run HTML5 so they should be accessible on all devices, including Chromebooks, iPads, and laptops. If the simulations are not visible, more likely than not, a filter is blocking access to the simulations.

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How can I support this work?

The best way to support this work is to pledge a few dollars a month through Patreon.com. The simulations are ad-free, online, and free. The costs of the technology and time is supported by generous donors. The simulations are used daily by students from all over the world. By becoming a Patreon patron you are helping students from all over the world get access to these simulations to practice and play with the concepts of biological science.

If you would like to just make a one-time donation, you can become a Patreon patron, donate for one-month, and then cancel you patronage.

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Are there other ways I can support this work besides Patreon?

Talking about and sharing the simulations through your website, blog, twitter, or facebook are other ways you can support this work. Let me know, if you do! Here’s my twitter handle @jondarkow.

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How can I get a specific quantity at different time intervals in a simulation?

After a simulation is run, left click and drag to see the quantities of the different outputs on the graph at different time intervals.

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What is the difference between a comparative simulation run and a live simulation run?

If you are interested in comparing the quantities of simulation runs, then use the green “Run” button. For example, the graph below shows 5 simulations runs by varying the “Distance to Light (cm)” slider. This is incredibly useful for running experiments because you can click on the graph to get subsequent quantities of different simulation runs simultaneously. For experiments that produce stochastic results, like the random variations of genetic drift, my students will run the same parameter 5-10 times in a row, without varying a parameter, then collect the 5-10 data points simultaneously.

In contrast, clicking the blue “Live” button, allows users to see live updates to graphs when adjusting sliders. This is an awesome method to infer cause and effect relationships. By clicking on the blue “Live” button, when students adjust a slider (an independent variable), the graph outputs (the dependent variables) automatically update. While useful for observing relationships, and determining the rules that may govern relationships between two variables, the “Live” simulations should be avoided for collecting data for experiments. Examine the graph below to see how the “Live” simulation runs work.

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Are there worksheets to go along with the simulations?

Yes. I have included activity sheets on each simulation page when available. Additionally, I have an entire Google Folder of all simulation activity sheets. These worksheets and simulations are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Feel free to remix and share, just give credit where credit is due.

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Are there answer keys?

The simulations produce a variety of results. The purpose is to have students explore and discover relationships through interactive simulation. Students can test assumptions in a rich variety of methods. I do not have specific answer keys.

However, if you become a Patreon patron I would be happy to answer any questions you may have.

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How are these simulations used to practice science? (How are they used to teach the Scientific Practices?)

I specifically build my simulations for my students to practice science. This is my wheelhouse!

At the National Association of Biology Teachers (NABT) Professional Development conference in St. Louis (2018) I gave a workshop on using simulations to teach the scientific practices. Here are the materials I gave to attendees for the workshop:

Here are some of the presentations I have made on using simulations to teach scientific practices:

“Using Simulations and Computational Models to Teach Scientific Practices”, Workshop at the NATIONAL

ASSOCIATION OF BIOLOGY TEACHERS CONFERENCE, St. Louis, Missouri, November, 2017.

“Using Simulations to Teach Scientific Practices,” Session at the OHIO EDUCATIONAL TECHNOLOGY

CONFERENCE, Columbus, Ohio, February, 2017.

“Using Simulations to Teach Science,” Workshop at the OHIO EDUCATIONAL TECHNOLOGY

             CONFERENCE, Columbus, Ohio, February, 2016.

“Simulations and Computational Thinking to Teach Scientific Practices,” NORTHWEST OHIO SYMPOSIUM ON

SCIENCE, MATHEMATICS, AND TECHNOLOGY TEACHING, Bowling Green, Ohio, November,  

2015.

“Complexity Made Simple: Fostering Creative, Quantitative, and Critical Thinking,” NORTHWEST OHIO

SYMPOSIUM ON SCIENCE, MATHEMATICS, AND TECHNOLOGY TEACHING, Bowling Green, ‘

Ohio, November, 2013 and November, 2012.

“Systems Thinking and STELLA,” NORTH CENTRAL OHIO EDUCATIONAL SERVICE CENTER, Tiffin, Ohio,

              March, 2013.

“Quantitative Experiments and Modeling in the Science Classroom,” NORTHWEST OHIO SYMPOSIUM ON

             SCIENCE, MATHEMATICS, AND TECHNOLOGY TEACHING, Perrysburg, Ohio, November, 2009.

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How can I practice statistics to support or reject hypotheses using these simulations?

Statistics is how we can better describe a varied set of data (mean, standard deviation, and standard error), and how we can can infer relationships between variables for a set of data (Chi-square, T-tests, linear regression.)

Using statistics for some of the simulations would NOT BE APPROPRIATE because each simulation run will yield the exact same results.

 Look for the following warning. Simulations that generate variation are the simulations that you can use statistics to support or reject hypotheses. For example, the graph below shows 10 different simulation runs with the exact same initial conditions. The simulation produces random results. MOST of my simulations will generate variable results. If the simulation produces random results, then statistical tests can be done.

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How can I use these simulations to practice the different forms of inference to practice scientific reasoning?

Philosophers classify reasoning into three different forms of inference:

Reasoning is the method of presenting a series of premises, and drawing a conclusion from the premises. Only valid deductive arguments produce conclusions with certainty. A valid deduction necessarily produces a certain conclusion.

In contrast, inductive and abductive reasoning DO NOT generate certainty in their conclusions. Rather, induction and abduction produce probable conclusions.

One of the best distinctions of deduction, induction, and abduction focuses on what is the goal of the argument.

In deductive reasoning, the goal is to justify the effect based on a rule and a cause.

In inductive reasoning, the goal is to justify the rule based on a cause and an effect.

In abductive reasoning, the goal is to justify the cause based on a rule and an effect.

The following table distinguishes these forms of inference.

Form of Inference

Premise 1

Premise 2

Conclusion

Good arguments with true premises yield

Deduction

Rule (or hypothesis)

Cause

Effect

Certainty

Induction

Cause

Effect

Rule (hypothesis)

Probability

Abduction

Rule (or hypothesis)

Effect

Cause

Probability

In the photosynthesis simulation students can manipulate a variety of sliders and buttons. These independent variables are CAUSES. The graphs show the outputs of simulation runs, which are the dependent variables. These dependent variables would be the EFFECTS.

I used scientific theories to compute results for different dependent variables based on different initial conditions (independent variables). The computational rules I used are my assumptions for how I think the system should behave based on scientific theories of photosynthesis. My assumptions in the computational model are the ultimate RULES in this virtual system. For example, when the distance from light increases, the amount of oxygen produced decreases. This is a RULE of my model, which I based on a scientific theory of photosynthesis.

In my simulations you can use these forms of inference to guide questions about the simulations. Let me walk you through examples of each.

Deductive Reasoning

Premise 1, RULE:        Under standard initial conditions, when the distance from light increases, the

production of oxygen in the plant decreases.

Premise 2, CAUSE:        The distance from light increased.

Conclusion, EFFECT        Therefore, the production of oxygen decreased.

                        

With deductive reasoning the conclusion, “the production of oxygen decreased”,

necessarily (certainly) follows from the premises. In all possible cases (as long as run under standard initial conditions), when the distance from light increases, the amount of oxygen decreases.

Inductive Reasoning

Premise 1, CAUSE:        The distance from light increases.

Premise 2, EFFECT:        Oxygen production decreases.

Conclusion, EFFECT        Therefore, under standard initial conditions, when the distance from light increases,

the production of oxygen in the plant decreases.

                        

With inductive reasoning the conclusion, is the RULE. This is what science does,

generates rules based on experiments. The RULE is only possibly true, NOT certainly true. In the simulation, the RULE,  under standard initial conditions, when the distance from light increases, follows when the distance from light increases from 0 to 100 cm. However, at 100 cm the production of oxygen is zero. When the distance from light is between 100-150cm oxygen production is also zero. Therefore, the RULE does NOT follow when the distance from light is greater than 100 cm.

Abductive Reasoning

Premise 1, RULE:        Under standard initial conditions, when the distance from light increases, the

production of oxygen in the plant decreases.

Premise 2, EFFECT:        Oxygen production decreases.

Conclusion, CAUSE        Therefore, the distance from light increased.

                        

With abductive reasoning the conclusion, is the CAUSE. This is what science does,

when applying a rule under some scientific theory. The CAUSE is only possibly true, NOT certainly true. In the simulation more than one CAUSE can regulate the EFFECT “Oxygen production decreases”. While increasing  the distance from light can CAUSE oxygen production to decrease, other CAUSES can lead to the same EFFECT. Changes in the “Temperature”, “Light Wavelength”, and “Atrazine” also can be the CAUSE.

When using the simulations, I mix question types to have students practice different types of scientific reasoning.

        

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Who is Jon Darkow?

Jon Darkow teaches AP Biology, Environmental Science, Anatomy and Physiology, and Biology at Seneca East High School in Attica, Ohio. His students make him laugh often as they struggle with a diversity of biological systems. Jon creates computer simulations of biological concepts to help teach concepts, patterns, and practices in biology (www.jondarkow.com).

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Got a Question?

Submit questions and comments to this Google Form. I will try to answer any questions I can.

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Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.