Jon Darkow's Profile
Number of items: 124
Date joined: Apr 05 2016
Website: www.jondarkow.com
Jon Darkow has taught a variety of biology courses at the high school and college level for the past ...Read more Jon Darkow has taught a variety of biology courses at the high school and college level for the past 15 years at Seneca East High School and through Bowling Green State University. Currently, Jon teaches Biology, AP Biology, and Anatomy and Physiology. Additionally, he teaches Instructional Technologies to educators in Seneca County. Jon has a diverse academic training with a B.A. in Sociology from Ohio State University in 2000. He has a post-bachelors in Life Science Education and an M.Ed. in Curriculum and Instruction from Ashland University where he received The Most Outstanding Professional Educator Award in 2007. Jon Darkow was the 2016 recipient of the Outstanding Biology Teacher Award from the National Association of Biology Teachers. Jon is most interested in teaching scientific reasoning and systems thinking using system dynamics modeling.
Jon Darkow's Work
#1
Cellular Respiration Accounting Model
The purpose of the model is to understand how glucose is metabolized, and how the energy stored in i
... Read more
The purpose of the model is to understand how glucose is metabolized, and how the energy stored in its chemical bonds is transfered.
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⋮ 714585 runs
cellular respiration
aerobic respiration
ATP
biology
#2
Evolution of Antibiotic Resistance Simulation
Evolution of Antibiotic Resistance Simulation. This model tracks the accumulation of 40 colonies of
... Read more
Evolution of Antibiotic Resistance Simulation. This model tracks the accumulation of 40 colonies of bacteria. The main purpose of the model is to show that new adaptations are not caused by an environmental factor, like antibiotics. Rather, new adaptations are the selection of available variations. In this model you can increase variations by increasing the UV dose. The UV dose increases the mutation rate with a Monte Carlo function.
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⋮ 176498 runs
Biology
Science
Ecology
Education
#3
Position, Velocity, and Acceleration Simulation
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⋮ 3136 runs
Science
#4
Lactase Enzyme Simulation with Data Analysis
sim
⋮ 12155116 runs
#5
Cell Cycle - Simpler 2020
sim
⋮ 61631 runs
Biology
Science
Education
#6
Pattern with recessive single band
sim
⋮ 95152 runs
genetics
#7
HPV and Adaptive Immune Response
sim
⋮ 11863 runs
HPV
Antibodies
feedback loops
vaccine
#8
Slider Bets and Metacognition
sim
⋮ 89 runs
Education
#9
The dynamics of photosynthesis - variable sample size
The dynamics of photosynthesis - variable sample size
sim
⋮ 93728 runs
photosynthesis
sample size
biology
#10
Stock, Inflow, and Outflow with Atrazine
Simple stock and flow diagram. Flows linear.
sim
⋮ 86 runs
stock
flow
atrazine
#11
Neurophysiology and Information Processing 2022
sim
⋮ 19331 runs
Biology
information processing
neuron
neurotransmission
neurophysiology
#12
Extinction
sim
#13
Evolving Bits N=40
sim
⋮ 2663 runs
evolution
bits
receptor
substrate
#14
Genotyping with Electrophoresis
sim
⋮ 43943 runs
biology
inheritance
DNA
restriction enzyme
#15
Enzyme Diversity: Enzymes, Products, and Substrates
sim
⋮ 1095235 runs
enzymes
substrates
products
DNA
trypsin
#16
Thyroid Hormone - Negative Feedback
sim
⋮ 79054 runs
negative feedback
thyroid hormone
metabolism
biology
#17
SIR COVID-19 Coronavirus Simulation
sim
⋮ 18856 runs
Environment
Biology
Science
Education
SIR
#18
Chaos Theory: Strange Attractor
Manipulate the main variables of the Lorenz equation.
sim
⋮ 2322 runs
chaos theory
Lorenz
attractor
manifold
#19
Evolution with Heterozygous Advantage
Evolution of Populations: Genetic Drift, Natural Selection, and Mutations
sim
⋮ 7686 runs
evolution
natural selection
genetic drift
#20
ATP Hydrolysis
sim
⋮ 6951 runs
Science
ATP
Free Energy
Entropy
#21
Photosynthesis Simulation with Variance
sim
⋮ 209027 runs
#22
Photosynthesis Simulation - Simplified
sim
⋮ 75 runs
Environment
Biology
Science
Ecology
Education
#23
Illusions and Assumptions
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⋮ 918 runs
Biology
Science
#24
Evolving Bits
Diversity and selection for the basis of evolution. This simple model tries to illustrate these conc
... Read more
Diversity and selection for the basis of evolution. This simple model tries to illustrate these concepts.
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⋮ 1666 runs
Diversity
Selection
Evolution
Receptor
Antigen
#25
Predator Prey Model - Mobile
sim
⋮ 97 runs
Biology
#26
Carbon in the Atmosphere - Graphic Input constant
sim
⋮ 28 runs
#27
Evolution and Natural Selection
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⋮ 353039 runs
#28
White-Eyed Genetics
White-eyed is an allele that results in a fly white eyes. Wild-type variants have red eyes.
The
... Read more
White-eyed is an allele that results in a fly white eyes. Wild-type variants have red eyes.
The goal of this simulation is to determine the pattern of inheritance for the white-eyed phenotype. Is yellow body dominant or recessive? Sex-linked or autosomal? Complete, incomplete, or codominant?
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⋮ 186172 runs
Genetics
#29
Ball Bet Code Generators for Answer Keys
sim
⋮ 808 runs
Education
#30
Mechanical Energy and Kinematics
sim
⋮ 397 runs
Science
Physics
Energy
Acceleration
Velocity
#31
Evolution: Grants Finches
Models the effects on population sizes of ground finches with different beak sizes in response to di
... Read more
Models the effects on population sizes of ground finches with different beak sizes in response to different amounts of annual precipitation.
sim
⋮ 12258 runs
evolution
biology
natural selection
#32
Ball Bet for Metacognition - Random
sim
⋮ 96 runs
Education
#33
HPV with Influenza A Humoral Immunity
Immune response of HPV
sim
⋮ 27445 runs
HPV
antibodies
biology
Immunity
#34
Diffusion of a Spherical Cell
Why are cells small? This model allows users to see how the size of a sphere affects the rate of dif
... Read more
Why are cells small? This model allows users to see how the size of a sphere affects the rate of diffusion.
sim
⋮ 145407 runs
diffusion
surface area
volume
radius
#35
Cellular Respiration Inquiry
Model of the dynamics of the metabolism of one mole of glucose. Randomness is built into the computa
... Read more
Model of the dynamics of the metabolism of one mole of glucose. Randomness is built into the computations.
sim
⋮ 111980 runs
metabolism
respriation
ATP
biology
#36
Population dynamics of white footed mouse
sim
⋮ 1334868 runs
#37
Catastrophic Regime Change in Aquatic Ecosystems
sim
⋮ 111575 runs
Ecology
#38
Phenology of the Karner Blue Butterfly
Karner Blue butterfly is an endangered species. Habitat loss and climate change are contributing fac
... Read more
Karner Blue butterfly is an endangered species. Habitat loss and climate change are contributing factors to the reduction in the butterflies' population sizes. Climate change can alter the timing of lifecycles. When climate change disproportionally affects the timing of life cycles of species in an ecosystem asynchrony within a food web occurs.
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⋮ 11674 runs
asynchrony
timing
phenology
climate change
butterfly
#39
Grant Finches Mobile
sim
⋮ 15 runs
#40
Student Model (X. Hicks and J. Margraf) - HIV
sim
⋮ 84 runs
#41
Ball Bet 3.0.2
sim
⋮ 1 run
#42
Oxytocin-P
sim
⋮ 36 runs
Biology
#43
Growth Factors, Cyclins, and Cancer
Explores the feedback loops that regulate the cell cycle. Model focuses on manipulating stimuli (gro
... Read more
Explores the feedback loops that regulate the cell cycle. Model focuses on manipulating stimuli (growth factors), to stimulate the cell cycle feedback loops.
sim
⋮ 307185 runs
growth factors
cyclins
cell cycle
cancer
#44
Exponential Growth
sim
⋮ 13032 runs
Biology
Ecology
#45
Circadian Clock in the Mouse
Transcriptional Translational Feedback Loop in the Mouse
sim
⋮ 31042 runs
Mouse
Circadian
Clock
#46
Beta Cell Membrane Transport - Insulin Regulation
sim
⋮ 269 runs
Insulin
Glucose
Beta Cell
#47
Neurophysiology and Neurotoxicity
The main dependent variable measured in the model is the membrane potential (millivolts) of a motor
... Read more
The main dependent variable measured in the model is the membrane potential (millivolts) of a motor neuron and the muscle fiber it innervates. You will be able to add excitatory and inhibitory neurotransmitters, and compare how neurotransmitters modulate the electrical impulses of the motor neuron and the muscle fiber.
Additionally, you will be able to compare the effects of four neurotoxins: Tetrodotoxin, botulinum toxin, sarin nerve gas, and VX. While extremely lethal, these toxins are very instructive in understanding neurons because of the specific way the toxins act. Each toxin modifies or inhibits a specific molecule in neurons that help process and transmit information.
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⋮ 46458 runs
Neurophysiology
toxins
sarin
VX
TTX
#48
Limiting Nutrients in Aquatic Ecosystems
Experiment with a variety of nutrients that are limited by different degrees in four different ecosy
... Read more
Experiment with a variety of nutrients that are limited by different degrees in four different ecosystems.
sim
⋮ 124572 runs
limiting nutrients
ecosystem
biology
logistic growth
#49
Phosphorus in Lake: Changes to Flows in a Dynamic System
This model allows users to experiment with a very simple dynamic system: one stock (Phosphorus in a
... Read more
This model allows users to experiment with a very simple dynamic system: one stock (Phosphorus in a lake), an inflow (added P/day), and an outflow (removed P/day).
The flows can either be constant throughout the simulation run, or dynamic (changing throughout the simulation run.)
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⋮ 3052 runs
flows
dynamic
phosphorus
#50
Logistic Growth Model and the Butterfly Effect
Model allows users to test the starting population size (N), the carrying capacity of the populatio
... Read more
Model allows users to test the starting population size (N), the carrying capacity of the population (K), and the intrinsic rate of growth (r max).
Iterations are discrete, not continuous.
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⋮ 5833 runs
logistic growth
carrying capacity
#51
Understanding Linear Motion
Understand linear motion with automated feedback.
sim
⋮ 1107 runs
Science
Education
physics
motion
velocity
#52
Tesing Unknown Enzymes
sim
⋮ 277736 runs
enzymes
#53
Bathtub Dynamics
This simulation has three models.
Model1 shows constant inflow and outflow into a bathtub.
Model
... Read more
This simulation has three models.
Model1 shows constant inflow and outflow into a bathtub.
Model 2 shows constant inflow and nonlinear outflow based on the quantity of water in the bathtub.
Model 3 shows constant inflow and nonlinear outflow based on the quantity of water in the bathtub. However, Model 3 uses Torricelli's law to calculate the flow rate based on physical principles.
This law was formulated by Evangelista Torricelli, an Italian physicist, in the 17th century. It's an important principle in fluid dynamics and is closely related to Bernoulli's principle. Torricelli's law states that the speed (velocity) of efflux of a fluid through a hole under the force of gravity is proportional to the square root of the vertical distance (height) between the fluid surface and the center of the hole. The formula is given by efflux velocity = 2*g*ℎ, where:
g is the acceleration due to gravity (approximately 9.81 m/s² on Earth).
ℎ is the height of the fluid column above the hole.
The idea is that the fluid's potential energy due to its height is converted into kinetic energy as it falls. The higher the fluid, the greater its potential energy and thus the greater the speed at which it exits the hole. This principle is used in various applications, such as determining the flow rate of liquids from tanks, in hydrodynamics studies, and even in everyday situations like draining a bathtub. The law assumes an ideal fluid (incompressible and non-viscous) and neglects factors like air resistance and the viscosity of the fluid. It also assumes that the size of the hole is small compared to the depth of the fluid.
The flow rate (the volume of fluid flowing per unit time) can be calculated by multiplying the cross-sectional area of the hole (A) by the velocity of the fluid (v), leading to the formula
Q=A*v, where Q is the flow rate.
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⋮ 739 runs
Environment
Science
Education
Bathtub
hydrodynamics
#54
Water Potential and Osmosis
Factors that affect the flow across a semi-permeable membrane.
sim
⋮ 396576 runs
#55
Evolution of LAP Allele in Mussels
sim
⋮ 85167 runs
Evolution
Natural Selection
Cline
#56
Beta Cell Simulation - Split story
sim
⋮ 79275 runs
#57
Cell Cycle Simulation
sim
⋮ 2558 runs
Biology
#58
Fruit Fly with variable sample size
sim
⋮ 43 runs
#59
Soybean and Aphid Dynamics
sim
⋮ 90 runs
Environment
Biology
Science
Economics
Ecology
#60
Tryptophan Operon: A repressible system
sim
⋮ 88886 runs
#61
Steady State in Freshwater Ecosystems
sim
⋮ 34615 runs
#62
Body Temperature Regulation with Scatter Plot
sim
⋮ 111 runs
Biology
Science
Education
Health
#63
Guppy Evolution
sim
⋮ 180941 runs
evolution
biology
genes
#64
Recombination and Gene Linkage
sim
⋮ 142805 runs
#65
System Dynamics of Carbon Budget
Simulation of the system dynamics of the global carbon dioxide budget based on the work on systems d
... Read more
Simulation of the system dynamics of the global carbon dioxide budget based on the work on systems dynamics based on John Sternman (MIT) and Krytyna Stave (University of Nebraska)
sim
⋮ 16486 runs
system dynamics
carbon
climate
#66
Gravitational Attraction of Three Bodies
sim
⋮ 314 runs
Science
Education
Forces
Gravitation
Physics
#67
Oxytocin and Child Birth
sim
⋮ 245046 runs
#68
Uniform Circular Motion
sim
⋮ 796 runs
Science
Education
Circular
Motion
Physics
#69
Extinction Vortex
sim
⋮ 59632 runs
#70
Lotka-Volterra Predator-Prey Model
Explore my favorite aspect of system dynamics and a historic example. The homeostasis generated by t
... Read more
Explore my favorite aspect of system dynamics and a historic example. The homeostasis generated by the interconnections of a negative feedback loop governs much of life.
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⋮ 276372 runs
negative feedback loop
Lotka-Volterra
homeostasis
predator-prey
#71
GLUT and Insulin
sim
⋮ 20 runs
#72
Lactase with Variable Sample Sizes
Arrayed Lactase Model
sim
⋮ 837038 runs
Lactase
array
sample size
biology
#73
Carbon Cycle Simulation
Simulation tracks the movement of carbon to and from the atmosphere in Gt C (and Gt CO2). Users can
... Read more
Simulation tracks the movement of carbon to and from the atmosphere in Gt C (and Gt CO2). Users can manipulate with graphical inputs the changes in fossil fuel emissions, land-use, and ocean sinks.
sim
⋮ 9607 runs
Environment
Biology
Science
Ecology
Education
#74
Lactose Operon: An Inducible System
In this simulation users explore the negative feedback system of the Lactose Operon found in bacteri
... Read more
In this simulation users explore the negative feedback system of the Lactose Operon found in bacteria. Lactose induces the system by inhibiting and inhibitor.
sim
⋮ 145629 runs
Inhibition
negative feedback
biology
lactose
operon
#75
Photosynthesis Model
sim
⋮ 2534754 runs
#76
Photosynthesis with Variable Sample Sizes
Sample sizes of Photosynthesis stocks in an array
#77
Apterous Genetics
Apterous is an allele that results in a fly without wings. Wild-type variants have normally function
... Read more
Apterous is an allele that results in a fly without wings. Wild-type variants have normally functioning wings.
The goal of this simulation is to determine the pattern of inheritance for the apterous phenotype. Is apterous dominant or recessive? Sex-linked or autosomal? Complete, incomplete, or codominant?
sim
⋮ 307527 runs
Genetics
#78
Cardiovascular Model
sim
⋮ 27211 runs
#79
Simple Genetics
sim
⋮ 128928 runs
#80
Tick Tock: The Biological Clock and Circadian Rhythm
Explore gene expression of the transcriptional-translational feedback loop (TTFL) of the mouse circa
... Read more
Explore gene expression of the transcriptional-translational feedback loop (TTFL) of the mouse circadian rhythm.
sim
⋮ 1128 runs
circadian
clock
feedback loop
#81
Fruit Fly Choice
Simulation to model random behavior in a fruit fly choice chamber
sim
⋮ 1017 runs
randomness
random
#82
Soybean and Aphid Population Dynamics
sim
⋮ 1934 runs
Biology
Science
#83
Information Processing and Neurophysiology Model
The main dependent variable measured in the model is the membrane potential (millivolts) of two diff
... Read more
The main dependent variable measured in the model is the membrane potential (millivolts) of two different neurons in a series. You will be able to add excitatory and inhibitory neurotransmitters, and compare how these modulate electrical impulses of the two neurons.
Additionally, you will be able to compare the effects of three neurotoxins: Tetrodotoxin, botulinum toxin, and sarin nerve gas. While extremely lethal, these toxins are very instructive in understanding neurons because of the specific way the toxins act. Each toxin modifies or inhibits a specific molecule in neurons that help process and transmit information.
sim
⋮ 306819 runs
infromation processing
neurophysiology
biology
#84
Lac Operon with Monod Bump
sim
⋮ 203791 runs
Lac Operon
Gene Regulation
mRNA
#85
Transformation Experiment with Controls
Simulation allows users to test the bacterial transformation principle discovered by Frederick Griff
... Read more
Simulation allows users to test the bacterial transformation principle discovered by Frederick Griffith.
sim
⋮ 29393 runs
Biology
Science
Education
transformation
DNA
#86
Transformation Simulation
Simulation allows students to test the transformation principle. Two major goals of the experiment a
... Read more
Simulation allows students to test the transformation principle. Two major goals of the experiment are:
1. Allow users to see that supernatant from heat-killed bacteria can transform the genes of another bacterium.
2. What transforms the inheritance of the bacteria is DNA, not RNA or proteins.
sim
⋮ 134858 runs
transformation
DNA
biology
#87
Enzyme Diversity
sim
⋮ 477563 runs
enzyme
biology
substrate
pepsin
indicators
#88
Pendulum Model
sim
⋮ 17 runs
Science
Education
Physics
Simple Harmonic Motion
Pendulum
#89
#90
SIR Model for COVID-19
This model was copied from Jon Darkow:
This model was copied from Jon Darkow:
#91
Mechanical Energy Model
#92
SIR Model for Coronavirus (COVID-19)
#93
#94
#95
#96
Exponential Growth in Population - AF
Chapter 2: Modeling the Environment
#97
#98
#99
#100
Modeling Constant Acceleration
#101
#102
Two Variations - Population Growth
#103
#104
#105
#106
#107
#108
#109
#110
SIR Model for Coronavirus (COVID-19) - with social distancing
This model was copied from Jon Darkow:
#111
#112
#113
#114
#115
#116
#117
#118
#119
Projectile Motion Physics
#120
Comparing COVID-19 with xxx
This model was copied from Jon Darkow:
#121
Endocrine System Dynamics
This model shows how FSH regulates the reproductive cycle in females, and how diseases may emerge fr
... Read more
This model shows how FSH regulates the reproductive cycle in females, and how diseases may emerge from underproduction and excess production of the hormone.
This model was developed for a high school Anatomy and Physiology class.
#122
Differential Reproduction, Natural Selection Model
This is the fourth model in a sequence of models to show the logic of natural selection, formalized
... Read more
This is the fourth model in a sequence of models to show the logic of natural selection, formalized by Earnst Mayr.
Mayr E. The growth of biological thought. Cambridge: Harvard University Press; 1982.
#123
Uploading a Bundle from Zip
Instead of creating bundles, categories, and assemblies one by one, you can upload a single zip file that contains all of your bundle's content. To create your zipped bundle, make a folder with your bundle's name and add subfolders with your categories' names. The folder tree should have the same structure that you want the categories to have in your bundle. Place your assembly .stmx files in the appropriate category folders, then zip your bundle folder and upload it using the Upload Bundle from Zip link above.
Assemblies, Bundles, and Categories
Assemblies are self contained models that demonstrate common ways to connect together building blocks and that can be used as parts of other models. This is analogous to using prefabricated wall and roof pieces to construct a house.
Bundles are groups of assemblies with a common use or theme. For example, a Health Care bundle might contain a variety of assemblies that aid in creating health care models. When you download assemblies from the isee Exchange™, you download an entire bundle, rather than individual assemblies.
Categories are subgroups of assemblies within a bundle. For example, a Health Care bundle might contain a Funding category for assemblies related to the management of hospital funds. All assemblies must be assigned to a category—they cannot be assigned to the root of a bundle.
Assemblies, bundles, and categories can be created and uploaded to the isee Exchange™ via the options on the Manage My Assemblies page. To learn more, visit our help pages, or take our assemblies tutorial.
Sim App (Sim)
An interface that allows users to interact with a model.
Sim apps allow users to interact with a model using buttons, sliders, knobs, tables, graphs, and storytelling. These interactions help users understand how parts of a system interact.
Interfaces are created by model authors in the Stella desktop software and can be uploaded to the isee Exchange™.
Model
A diagram that represents how elements in a system influence one another.
Models are mathematical representations of how elements in a system are connected and interact (e.g., ecosystems, organizations, supply chains). When running models on the isee Exchange™, results can be viewed in output devices like graphs and tables.
Models appear in the isee Exchange™ directory when authors upload them from the Stella® desktop software or create them with Stella Online™.
Causal Loop Diagram (CLD)
A map that represents the feedback structure of a system.
CLDs are high-level maps that represents the feedback structure of a system and easily communicate the essence of a model. They appear in the isee Exchange™ when authors upload them from the Stella desktop software or create them with Stella Online™.