Evolution Unit

“Nothing in biology makes sense except in the light of evolution” is the title of an of-quoted essay by noted evolutionary biologist Theodosius Dobzhansky. It underscores the explanatory power of evolution, transforming biology from a descriptive science to one that can provide generative mechanisms that account for what we observe. Yet despite its importance, it is widely misunderstood and rejected by the population at large, and it has been shown to be challenging for students. Educators and psychologists have described a host of student misconceptions about evolution, including difficulties with essentialism of species, confusion about natural selection mechanisms, as well as issues with the relation between micro- and macro- evolution, the status of evolution as a theory, intentionality and teleology in evolutionary trajectories and explanations, and the passage of “deep time”. Clearly this is an area where there is great need for improved instruction and materials.

To address this issue, we have designed a state-of-the-art curriculum that closely aligns with the Next Generation Science Standards. This unit consists of a suite of activities designed to facilitate inquiry into core evolutionary mechanisms such as natural selection, genetic drift and speciation using computational models. Each of the activities is designed around a computational model that simulates the evolutionary phenomena of interest. These models serve as environments for designing and conducting experiments to collect and analyze data to construct scientific explanations for the evolutionary phenomena of interest. Each activity begins with a pre-class discussion to introduce students to the central question of the activity and to elicit students’ prior ideas about the topic. After students have interacted with the model, either alone or in small groups, the teacher facilitates a consensus-building discussion in class to synthesize what students learned about the mechanisms and outcomes of the evolutionary phenomena.

These activities have been pilot-tested in high-school biology classrooms, and revised based on the implementations.

Description of the Activities in Each Lesson

Lesson 1  Why Do These Organisms Look The Way They Do?

Performance Expectation:  

  • Ask questions and brainstorm ideas about why domestic dogs, wolves, Maned wolf, coyote, and African wild dog have many similar traits, but different characteristic variations.


Students predict which photographs of 9 canids are of dogs or wolves and which are not. Students share their prior conceptions about why these organisms look the way they do with each other and then students share these ideas with the class.   Students create questions they want to figure out the answer to over the course of the unit and each student shares and posts one question to the case study question board.

Lesson 2a  How Can I Influence Traits Through Selective Breeding?

Performance Expectation

  • Conduct an investigation to influence the characteristics of virtual birds and their gene pool by selective breeding them in a cooperative participatory computer simulation.


Students identify variations of traits that people might selectively breed for in cats and dogs.  They then work in a team of 4 students to selectively breed virtual birds in a computer simulation where they cooperate with each other and compete against other teams of students to see which team can most quickly develop a fancy breed of bird.

evol_1Bird Breeders NetLogo Model

After analyzing the results of the simulation, the teacher facilitates a consensus building discussion through which the class identifies the mechanisms of selection in the model, including selection of which individuals will reproduce and which individuals will be removed from a population.  They also identify how allele selection (via. Meiosis) for passing on genetic information to offspring is a random selection processes.  And they describe how these mechanisms of selection influence the outcomes of the selective breeding.

In their out-of class reading, they apply these experiences and understandings to describe how people have selectively bred corn, dogs, foxes, and cats for different trait combinations and how selective breeding in corn has changed the traits variation in these species over time.

Lesson 2a  How Did People Develop Breeds of Dogs?

Performance Expectation

  • Obtain and communicate information from text and verbal presentations about the physical and behavior traits, health issues, and breeding history for dog breeds and possible trait variations that would have been selected for in wild wolves to help early human settlements.


Students choose a case study of a dog breed to learn more about the breeding history of this type of dog and its physical and behavioral traits.  They work in teams to develop a list of trait variations in wild wolves that people might have noticed and found useful in early human settlements.  And they describe how selective breeding might have removed some traits that would help dogs compete against wild wolves in natural ecosystems.

In the out of class reading, students learn more about domestication of animals and the results of an experiment to attempt to domesticate foxes.  They develop a hypothesis about why house cats might have been first domesticated from wild cats through selective breeding.

Lesson 3  Why Do Some Variations Become More Common and Others Disappear? (part 1)

Performance Expectations

  • NGSS HS-LS4-3.  Analyze data from a computer investigation applying concepts of statistics and probability to support explanations that organisms with an advantageous heritable trait tend to increase in proportion to organisms lacking this trait. [Emphasis is on analyzing shifts in numerical distribution of traits in a histogram and using these shifts as evidence to support explanations.]


The teacher demonstrates the model rules for the computer model.  Students use the computer model to assume the role of predator in a population of prey (bacteria).  They hunt bacteria using two different predation strategies, each of which generates a different selective pressure and a different outcome from natural selection.  They compare how the competitive advantage for different variations of speed in the prey changes based on these two types of interactions that occur with the predator.

evol_2Bacteria Hunt NetLogo Model

At the end of class, the teacher develops a class consensus through discussion on the big ideas regarding the conditions necessary for natural selection and how these conditions leads to changes in the proportion of individuals that have advantageous characteristics will increase.

In their out-of-class reading, students describe how a population of prey and predators would change over time due to natural selection, why bacteria have become more pesticide resistant over time, and what will eventually probably happen to populations of plants that pesticides are currently effective at killing off most of the individuals.

Lesson 4   Why Do Some Variations Become More Common and Others Disappear? (part 2)

Performance Expectation

  • NGSS HS-LS4-3.  Design and conduct an experiment to provide evidence to explain why organisms with different kinds of heritable traits tend to increase in proportion to organisms lacking this trait in different environment with no predators.. [Emphasis is on analyzing shifts in numerical distribution of traits in a histogram and using these shifts as evidence to support explanations.]


Students then design an experiment to explore how different distribution of food/water in an ecosystem and different metabolisms for different behaviors (due to a physical trait – flagella number) affect the outcomes of natural selection in population of virtual bacteria.

evol_3Bacteria Food Hunt NetLogo Model

Students present their initial results to the class and the class discusses possible explanations for why these different conditions yield different shifts in the distribution of trait variations from natural selection.  Groups return to their experimentation and develop their explanations further, and report these out at the end of their experimentation.

At the end of class, through discussion the teacher develops class consensus on the big ideas regarding the conditions necessary for natural selection and revises the scientific principles from the last lesson.

Lesson 5a:  Why Do Some Variations Become More Common and Others Disappear? (part 3)

Performance Expectation

  • Design and conduct an experiment to determine the effect of meiosis on fluctuations in the distribution of traits in a population and alleles in a gene pool. [Emphasis is on analyzing traits and alleles in the population through visualization of virtual karyotypes and related bivariate graphs]


Students experiment with fish reproduction in a virtual fish tank, noting changes in allele frequency due to results of meiosis and fertilization events.

Students design experiments to investigate factors that affect loss of alleles from a population.  They discover that the types of alleles that are lost from genetic drift are not predictable.  They find that smaller populations and small gene pools lose alleles more quickly due to genetic drift than larger populations and larger gene pools.

evol_4Fish Tank Genetic Drift NetLogo Model

At the end of the lesson, the teacher helps build consensus  how genetic drift can lead to some trait variations becoming more common and others disappearing from a population.

In their homework students apply the mechanism of genetic drift to show how two descendant populations of organisms could appear very different from one another and they read about population bottlenecks and founder effects in article about cheetahs.

Lesson 5b: Why Do Different Sub-species of Wolves Have Different Trait Variations?

Performance Expectations

  • HS-LS4-4  Build a model to show patterns in variations of a trait based on geographic location for different to support an explanation for whether natural selection or genetic drift most likely led to adaptation of the populations to its environment (in wolf sub-species).
  • Argue from evidence and critique other arguments for why some similarities and differences in trait variations between sub-species of wolves are more likely to be the result of natural selection rather than random selection events (genetic drift) or vice-versa.


In this activity, students make predictions about how different initial conditions affecting amount of resources available in the ecosystem will affect the stability of the bug population size.   From their model runs, students record observations about fluctuations in population size and stable states (equilibrium levels) for each population to test their predictions.

Through discussion, the teacher helps build consensus  about some of ways that populations sizes change in ecosystems – exhibiting minor fluctuations, cyclical fluctuations, while remaining relatively stable under certain environmental conditions.  They discuss how sustained environmental changes lead to new stable states for the ecosystem.

In their homework students brainstorm other types of environmental changes and read about the sources of evidence scientists use to figure out how the environment changed in the distant past.  They read about some of the type of climate changes and biological changes that have occurred on earth over the past 3.5 billion years.

Lesson 6: How Do Adaptations Emerge In Populations?

Performance Expectation

  • Conduct an investigation to provide evidence for an explanation of how natural selection and mutation work together to generate new adaptations in a population over time using a class-wide participatory simulation


Students compete as a team in a bug hunt competition generating a simulated form of natural selection with an outcome being that a population of bugs becomes progressively better camouflaged over time.  They see how mutation is modeled as random changes, but slight changes to genetic information.

They investigate the outcome that results when a population of gray bugs is placed against an image of a field of red flowers as they compete to find bugs to eat.  As each bug is eaten, a new offspring is asexually produced from one individual in the remaining population, with slight mutations in the genes that determine the pigments it produces (and resulting phenotype – color).   After studying the adaptations that results, they then change the environment (a new background image of a glacier) and repeat the natural selection simulation.  In this competition new colors emerge as adaptations for camouflaging, better suited to blending into the colors of glacier.

evol_5Bug Hunters Camouflage Model

Through discussion, the teacher helps build consensus about how populations adapt to an environment through mutation and natural selection, and how new trait variations emerge through these mechanisms that help the population become progressively better adapted to the environment over time.

In their homework students look at examples of camouflaging in animals and compare the Lamarckian perspective vs. the Modern Synthesis perspective to address misconceptions about the mechanisms that drive adaptation.

Lesson 7: How Do Adaptations Emerge In Populations? 

Performance Expectation

  • Design and conduct an experiment using a team-based participatory simulation to investigate how natural selection and mutation work together to generate populations that become progressively better adapted for survival and/or reproduction over time in different environments.


Students design an experiment in natural selection, using digital images they captured of the natural world (from the homework the previous night) as “background data” to include in the experiment.  In the experiment they the model they used in the previous lesson, but they now choose which images (environment(s)) to use as a background.  They choose whether the players on their team will be all mates, all predators, or a combination of both for a population of bugs.  And they choose the initial variation in the colors of the bugs they will start with in each population.

It’s likely that different groups will design different experiments.  Group will present their results to the rest of the class.  These results will motivate the revision/development of some of the scientific principles listed above.

In the homework, students will read about examples of sexual selection (for mates).  And they will compare examples of traits for attention seeking behavior/traits that is displayed only for a limited time (e.g. during a mating season, or only when other mates are detected nearby) or in only one of the two sexes.

Lesson 8: Where Do New Species Come From?

Performance Expectation

  • Analyze data from a computer investigation applying concepts of statistics and probability to explain why adaptations for reproductive isolation can help reinforce specialized adaptations for survival for different niches within different gene pools in a population.  [Emphasis is on analyzing shifts in numerical distribution of traits in a histogram and using these shifts as evidence to support explanations.]


The class revisits their definition of a species and discusses whether genetic drift alone could account for why new species emerge.

They then use a computer model of plants in an ecosystem to explore how speciation always could also emerge from a single population over time under certain conditions.

evol_6Plant Speciation Model

Through discussion, the teacher helps build consensus about why speciation might occur when mutation initiates the pathway to speciation, but natural selection and adaptation are the driving mechanisms that continue to reinforce the emergence of this outcome.

In the homework they study examples of how speciation has been created in laboratory conditions with human intervention and contrast the mechanisms at work in real world ecosystems when new species emerge.  And they read Darwin’s finches on the Galapagos Islands as a real-world example of adaptive radiation.

Lesson 9: How Are Different Species Related to One Another?

Performance Expectations

  • Analyze data and make inferences about evolutionary relationships of four wolf-like species based on data about physical traits, reproductive behaviors, somatic chromosome count, habitat, and geographic distribution.
  • Construct a scientific explanation, based on evidence, for which species of Canid is most closely related to gray wolves (African wild dog, Maned wolf, or Coyote), and which is most distantly related. (related to HS-LS4-2) 


The class revisits the definition of a species and the mechanisms that can account for why new species emerge.   The class revisits the different species on the Case Study board, and make predictions about which of these species is most closely related and which is most distantly related to gray wolves.

Students are assigned to groups of 3 to research one topic area to compare these species (African wild dog, Maned wolf, or Coyote).   They summarize the similarities and differences of this species compared to the gray wolf.  They report out their findings to their topic group of three and record the other members’ findings.  They create a ranking for which species is most closely and most distantly related to gray wolves based on this information.

Then students are reassigned (jig-sawed) to join a group of 4 students, where they are the topic experts for the area their old group researched.  Each member reports out their rankings, and supporting evidences and all group members summarize each other’s rankings.  Then, as a group they analyze the ranking for each topic area to determine their summative claim for which species is most closely related and which is mostly distantly related to wolves.  They add this information to an evolutionary tree diagram and provide written summaries of the evidence that supports their claim, and an explanation of the evolutionary mechanisms that may have been responsible for the formation of these species.

Optional:  You might find it productive to have students may present and defend their final arguments to their classmates.

Using the Unit in Your Classroom

The activities in this unit have been pilot-tested in several high school biology classes in the last few years. Based on our own research and observations, and feedback from teachers and students, we have revised existing activities, introduced new ones, and replaced activities that were not particularly productive for students. These implementations have provided us with insights to develop a better understanding of how we can leverage these computational models to design activities that are intellectually accessible, insightful and engaging for students.

First, we have noticed that these models and the explorations we have designed help students develop a deep understanding of the content. The visualization in the model coupled with the dynamically updating plots provide students with real moment-by-moment feedback on how a certain evolutionary mechanism plays out in the model. This dynamic feedback in turn provides insight into the content. Moreover, using these models as testing beds to run experiments and test their own theories in class, either independently or in small groups, enables students to refine their own understanding of the content. It is not uncommon for students to devise experiments beyond the outlined ones in the activity in order to test a hunch or “figure out” an idea with their partner.

The participatory simulations in which groups of students interact with each other within the space of a single model are particularly exciting and intellectually productive for students for several reasons. For one, when students engage in these simulations, they enact the mechanisms that underlie the evolutionary phenomena under investigation. For instance, when students play the role of a bird breeder, they enact mechanisms of selective breeding by using the information about the phenotype or genotype of birds to select which ones to breed, and which ones to release into the wild. We have found that this interaction gives students first-hand experience of the content, thereby fostering a meaningful understanding of the content. Participatory simulations are also particularly enjoyable because of the embedded game-like elements that make them engaging. For instance, the bug hunt camouflage model in which students click on bugs generates tremendous excitement in class as the bugs become better camouflaged and harder to spot.