Introduction to Stasis Theory
1 How Stasis Theory Helps You Write a Better Paper
By Stacie Draper Weatbrook
Stasis theory can do three things for you in organizing your writing:
- It can help you organize the flow of your paper by giving background information and context in a way the audience will better understand.
- It can re-define what the argument should be about.
- It can help you narrow your topic so you (and your audience) don’t get overwhelmed by all the information out there.
You’ve been given a writing assignment. You research. You read. You prepare to write. But how do you get the gazillion pieces of information organized in a way that makes sense to you and, ultimately, your audience? The answer involves understanding and being able to classify the types of arguments being made.
Let’s stop here and define “argument.” In rhetoric, an argument is “a claim with reasons,” not a fight or disagreement, as we tend to use the word in everyday language.
A lot of information goes into the topics and discussions you will research. A lot of claims are being made all at once. If you were researching bees, for example, you might find the following claims in multiple sources as you did research:
- Pesticides should be banned
- Everyone should plant flowers to attract bees
- Mold and viruses threaten bees
- The bee population is declining due to colony collapse disorder
- Almonds and apples are almost entirely pollinated by bees
- “Murder Hornets” attack honey bees
- Local honey helps seasonal allergies
- Honey bees are displacing native bees
- Bees are a keystone species
- Planting native wildflowers helps native bees
- Decreased bee populations hurt the economy
- People can’t survive without bees
- Monoculture is bad for the environment
- Pesticides and toxins threaten bees
- Bees are essential to one-third of the food consumed in the United States
Shopping the Clearance Rack: Identifying and Classifying Claims
Notice these claims are all over the place? Sorting through the information is just as difficult as shopping the clearance rack at Kohls or Macy’s: it’s not an activity for the faint of heart. You’re looking for a great bargain—and it’s there to be found—but the women’s shirts are mixed in with teen graphic tees, career jackets, and pajamas. The different sizes are supposed to be organized on racks by size but are usually more random than not.
When you write, it’s your job to organize and control the flow of information. Your audience will not have the patience to sort through a confusing collection of ideas. That’s your job as a writer. So, just like shopping a clearance rack and sorting through the sizes, colors, and types of clothes for that great deal, you will need to sort through the types of claims you find and settle on a clear claim (does the term “thesis statement” sound familiar?) and supporting reasons. Types of claims can be classified into five different levels or stases. Below, the five levels of argument are listed with examples of possible research questions for each of the stases:
FACT ― This level establishes what happens (happened) and verifies details in question.
“Is the overall bee population declining?”
DEFINITION ― This level seeks to classify and name an occurrence.
“Are honey bees actually an invasive species?”
CAUSE & EFFECT ― This level shows the precursors and/or results of an issue.
“Can local honey prevent allergies?”
VALUE ― This level argues how important, common, serious, or widespread an issue is.
“How extensive is colony collapse disorder?”
“How dangerous are murder hornets to bees?”
POLICY ― This level proposes an action or solution to an issue.
“How can gardeners be encouraged to plant native flowers to attract native bees?”
The ability to classify claims being made in an argument gives clarity to the situation and can lead to discussion and understanding of the issue.
Ancient Greeks and Romans used the stases to thoroughly discuss matters, especially legal matters. They wouldn’t move onto the next level if a previous level wasn’t resolved. How do these stases play out in everyday life and writing?
Only after a doctor is fairly certain of the symptoms (FACT/DEFINITION), causes (CAUSE & EFFECT), and severity (VALUE) of those symptoms will they suggest a course of treatment or write a prescription (POLICY).
Classical rhetoricians used stases as a way to logically classify and understand the accusations and counter-arguments in legal cases. A judge will not sentence a defendant accused of homicide until the evidence of the case has been established (FACTS). Once the homicide has been classified as felony murder rather than a first degree murder (DEFINITION), the judge can apply the law (CAUSE & EFFECT/VALUE) and hand down a sentence (POLICY).
You would like to go to a new restaurant for lunch but your friends have heard it’s expensive and they don’t want to spend a lot of money. To convince your friends to go, you present them with information they were not aware of―that the lunch menu is actually a good deal, especially if you order the daily special (FACT/DEFINITION). You tell them the atmosphere is fun and modern and it’s worth at least trying (CAUSE & EFFECT/VALUE). Then, you propose going to the restaurant (POLICY).
A student writing a paper proposing bee-friendly gardening tips (a policy-level argument) might first use the stases to help the audience understand the big picture of the issue:
Most people don’t realize it, but bees are vital to food production because they pollinate plants. In the last ten years, beekeepers have reported losing over 30% of their bees. Native bumble bee species are also declining. Most people also are shocked to learn that most bees do not live in hives; nearly 70% of native bee species are ground dwelling. While pesticides are commonly blamed for decreased bee populations, colored mulches and barks also pose a significant risk to bees because the synthetic dyes contain toxins.
This paragraph flows from the facts (bee populations are decreasing and are vital to food supply) to definition (most bees are ground dwellers) to cause and value (pesticides and colored mulches are a significant risk). The audience could then reasonably accept a thesis proposing suggestions or policy for keeping their gardens bee-friendly:
For this reason, it’s essential to use bee-friendly products in your garden.
The rest of the document could focus on the policy of adopting bee-safe gardening practices.
Using stasis theory in the introduction can help move the audience through an orderly set of information in order to introduce the thesis. It can also serve as an outline to discuss each level of the issue.
Static Cling And Waterproof Bath Towels: Start Where the Audience Is
The idea of stasis theory is audience-centered, meaning that in traditional argument or exploration, the writer (also called the rhetor) shouldn’t move past the point where the audience is.
The word “stasis” shares the same root as the word “static” (as in “static electricity” and “static cling”). So, when you don’t start where your audience is, it’s just as bad as getting halfway through a job interview and discovering a random sock clinging to the outside of your dress slacks.
Disagreement often happens when parties aren’t talking at the same level or stasis. When this disagreement happens, it can be a time for contentious name calling or it can be a time for open-minded discussion and discovery. Stasis theory gives a system for identifying when parties are giving claims at cross purposes:
Your spouse or housemate: “Let’s get grey countertops.”
You: “Do our countertops need to be replaced? Are they really that old?”
Here, one party is discussing policy: which color should we choose for the new countertops? Meanwhile, the other isn’t sure of the facts/definition: do we even need new countertops?
Stasis theory helps identify the point where discussion needs to occur: do our countertops really need to be replaced? Rhetorician Keith Grant-Davie explains, “The word ‘stasis’ (plural ‘stases’) literally means a ‘slowing down’ or a stopping point. In rhetoric, a stasis is an issue that may be contested or a question that needs to be resolved before the argument can proceed.” As in our example of the bees or the countertops, an audience will be much more receptive to changes they can make if they understand why it’s important.
Even if you present information in a logical order according to the stases, your audience will not always buy into the flow of information you present. Not all information moves smoothly through the stases from fact to policy. Sometimes audiences get “stuck” on a stasis (think static cling again) and will take issue or outright reject a stasis level you take for granted. Notice how this mock Kickstarter campaign derails in its attempt to logically go through the stases levels to encourage the audience to adopt the policy to buy a Fabulous Waterproof Towel:
As you know, there are over 327 million people in the United States, many of whom bathe or shower regularly. Our market research has shown that wet bath towels can be a problem because they are thick and difficult to dry, allowing mold to colonize, especially in more humid parts of the country. Because of this problem, our department has developed the Fabulous Waterproof Towel as a solution. Please contribute to this project today!
The remainder of the Kickstarter campaign would–we can only assume since it’s contrived—focus on why people should adopt the policy to buy into the Waterproof Towel technology.
But alas, this is one idea that’s probably not going to get much traction. Here’s an analysis of how an audience would likely react to the stases of this dubious Waterproof Towel proposal:
As you know, there are over 327 million people in the United States, many of whom bathe or shower regularly.
Here, the audience isn’t likely to disagree. They can quickly look up the population of the United States and because of the qualifier “many” will not disagree that a large number bathe or shower. There seems to be no fact or definition issue here.
Our market research has shown that wet bath towels can be a problem because they are thick and difficult to dry …
The audience might still be on board. Bath towels are thick and do take a long time to dry. That a bath towel will get wet is an effect the audience will likely accept. No issue here, move along.
… allowing mold to colonize, especially in more humid parts of the country.
The audience might take issue at this point, the value stasis. Here is the stopping point: the audience probably doubts the claim that wet bath towels are the huge problem they are made out to be. After all, how many cases of death by bath towel mold have been reported? Yes, bath towels get wet, but they usually dry within a few hours to a day, even in humid climates. Of course, the audience probably knows a simple thing to do is to put the bath towel in the wash after use or simply hang it to dry. Not a big deal. The audience will likely not find the problem of wet bath towels a pressing issue. Here, at the value stasis is the “stopping point,” where the issue needs to be resolved. But how can it be resolved? It’s a waterproof towel, an undeniably useless invention.
Because of this problem, our department has developed the Fabulous Waterproof Towel as a solution. Please contribute to this Kickstarter campaign today!
Because the audience wasn’t convinced at the value stasis that wet bath towels are a widespread and difficult issue, the policy argument, “contribute to this Kickstarter campaign” isn’t likely to be successful. At least we should hope not.
Obviously, the waterproof bath towel example is fabricated, but think of situations in your own life and in the public sphere where people disagree. When this discord happens, it can be a time for shouting, contention, oversimplification, and caricatures or it can be a time for thoughtful listening, open-minded discussion, and respect for differing viewpoints.
What Can Stasis Theory Do For You?
Stasis Theory Helps Organize the Flow of Information.
You can organize your paper along the natural order of the stases to help your audience follow the information you present. Using stasis theory helps you organize information to help the audience understand the state of the issue.
When you understand the natural levels of argument—fact, definition, cause & effect, value, and policy—it makes it easier to think about your purpose (what you want to have happen as a result of your document) and how your audience will interact with the information presented.
Stasis Theory Helps Writers Find the Interesting Angles.
Understanding how claims are classified helps writers identify how individual claims fit into the overall debate. It’s this ability to sort through information for the audiences that helps us deliver a clear message.
But stasis theory can do more than just help us organize; it can help us identify interesting and surprising angles in a debate. Careful research can help you move beyond the obvious arguments to find new facets in the debate.
Trust me. Your instructor will appreciate a new take on your subject.
Stasis theory not only helps you organize your thoughts, it also helps you redefine the issue and show other ways to look at a problem. To find new ways to look at issues and look for clarification or re-interpretation of facts, new definitions, little-known causes, surprising effects, events and statistics showing overwhelming importance, and the innovative solutions of an issue.
Being able to carefully analyze an issue and classify the associated claims will help you find new ways to look at old subjects.

When we encounter mountains of information about our topic, we often feel compelled to dump everything we know into one paper (true story: my first draft of this paper was over 7000 words). Understanding stasis theory helps pare down the issue to a manageable level and concentrate the bulk of the paper on the necessary stasis. That means you don’t have to cover every stasis or even most of them in detail. Hopefully, that helps you breathe easier. That’s not to say that after focusing your paper about the definition or causes of your issue, your instructor won’t ask you to add some background in the introduction or a conclusion briefly suggesting a solution, but it should be an immense relief to know it’s okay to focus on just a small part of the issue.
Conclusion
Ideally, issues of policy should be decided in public discourse only when all parties can agree on the earlier stases. After all, the intent of this ancient rhetorical strategy was to help audiences arrive at consensus at each level. As you know, however, in the case in our society, polite, respectful discourse aimed at consensus is nowhere near a reality. All sides seem too quick to try to pass laws and enact policy without coming to a proper understanding on the complexities of issues. Rhetoricians Jeanne Fahnestock and Marie Secor explain the value of understanding the stasis of arguments and assert that policy arguments are often premature (5). Still, they insist that stasis theory is an essential tool for discussion and understanding, saying, “We argue about many issues that cannot be resolved well enough for action to follow, but that can be clarified to the extent that we come to know what we do not know” (5). Coming to “know what we do not know” is a powerful literacy skill to help us examine issues and understand their complexity and relevance in personal and public discourse.
Works Cited
Fahnestock, Jeanne R., and Marie J. Secor. “Grounds for Argument: Stasis Theory and the Topoi.” Conference Proceedings—National Communication Association/American Forensic Association (Alta Conference on Argumentation), Jan. 1983, pp. 135–142.
Grant-Davie, Keith “Stasis Theory.” White paper. www.coursehero.com/file/27255076/Stasis-Theory-KGDpdf/.
Attributions
“How Stasis Theory Helps You Write a Better Paper” by Stacie Draper Weatbrook is licensed under CC BY-NC 4.0
Feedback/Errata


5.5. Neoclassical
Brian Fedorek
Modern deterrence theory is perhaps the most dominant philosophy of the American criminal justice system. Deterrence theory tries to change a person’s behavior through laws and punishments. As a form of social control, there is a belief that perceived punishments will serve as a warning of possible consequences, which would hopefully deter the person from committing the crime. There are two types of deterrence: general deterrence and specific deterrence. General deterrence uses punishment to deter crime among people in the general population. It uses punishment as an example for those people not punished. For example, capital punishment can serve as an example to other would-be offenders if they were thinking about murder. Specific deterrence uses punishment to reduce the crime of particular persons. The effect of the punishment depends on the nature of the punishment and who is punished.
News Box. In 1994, Oregon voters passed Measure 11, which established mandatory minimum sentencing for several serious crimes. Besides removing the judge’s ability to give a lesser sentence, Measure 11 prohibited prisoners from reducing their sentence through good behavior. Additionally, any defendant 15 years old or older who was accused of a Measure 11 offense was automatically tried as an adult. Recently, the Oregon Justice Resource Center reported the effects of Measure 11 on juveniles, especially minorities. Below are links to the news article and the report itself.
The Oregonian – “New Report Calls Measure 11 Sentences for Juveniles ‘Harsh and Costly'”
Measure 11 Exercise
After reading the above box and hyperlinks, please explain why many juveniles are not deterred from committing serious crimes in Oregon.
Classical ideology was the dominant paradigm for over a century, but it was eventually replaced by positivist approaches that seek to identify the causes of criminal behavior. However, classical ideology had a resurgence during the 1970s in the United States. Neoclassical theory recognizes people experience punishments differently, and a person’s environment, psychology, and other conditions can contribute to crime as well. Therefore, crime is a choice based on context. Many crime-prevention efforts used classical and neoclassical premises to focus on “what works” in preventing crime instead of focusing on why people commit criminal acts.
Cornish and Clarke (1986) proposed a Rational Choice Theory to explain criminals’ behavior.[1] They claimed offenders rationally calculate costs and benefits before committing a crime and assumed people want to maximize pleasure and minimize pain. The theory does not explain motivation, but instead, it expects some people will always commit a crime when given the opportunity. They do not assume offenders are entirely rational, but they do have bounded rationality. Bounded rationality is the constraint of both time and relevant information; offenders must decide in a timely fashion with the information at hand. Offenders cannot wait forever nor can they wait for more information before committing a crime. For example, if you were walking down a street and noticed an open window in a parked car, you may contemplate looking in. If you saw something inside, you may then consider stealing it. An entirely rational person may look around to see if there are any witnesses, try to determine if the owner is coming back soon, and so on. Ideally, you may wait until nightfall. However, you may miss your opportunity. Thus, you need to make a quick decision with the relevant facts at that time.
That was an example of a “crime-specific” model. All crimes have different techniques and opportunities. Additionally, they assume all crime is purposeful to benefit the offender. To dissuade offenders, Rational Choice Theory emphasizes the significance of informal sanctions and moral costs. The theory advocates for a situational crime prevention approach by reducing opportunities. Reducing opportunities is much easier to manipulate and change compared to changing society, culture, or individuals. Ultimately, situational crime prevention strategies try to crime a less attractive choice.
Another neoclassical theory is the Routine Activity Theory. Cohen and Felson (1979) claimed changes in the modern world have provided more opportunities for offenders.[2] Since the conclusion of World War II, more people have entered the workforce, and more people spend time away from home. Cohen and Felson stated that three things must converge in time in space for a crime to be committed – a motivated offender, a suitable target, and the absence of a capable guardian.
The motivated offender is considered to be a given as there will always be people who will seize opportunities to commit criminal offenses. Besides, there are a variety of theories to explain why people commit a crime. Suitable targets can be vacant houses, parked cars, a person, or any item. In reality, almost anything can be a suitable target. Finally, the absence of a capable guardian facilitates the criminal event. What can serve as a “capable” guardian? A plethora of people and things can serve as guardians. For example, police officers, security guards, a dog, being at home, increased lighting to allow other people to see, CCTV, alarm systems, and deadbolt locks can each reduce opportunities by serving as a capable guardian. Routine activity theory concentrates on the criminal event instead of the criminal offender.


64 Parthenon’s East Pediment
Dr. Beth Harris and Dr. Steven Zucker provide a description, historical perspective, and analysis of the Sculpture from the East Pediment of the Parthenon, possibly carved by Phidias.
Phidias (?), Sculpture from the East Pediment of the Parthenon, marble, c. 448–432 BCE, Classical Period (British Museum, London).
The identification of the Parthenon’s pediment figures remains unsettled. It is thought that the east pediment depicted the birth of the goddess Athena (fully grown) from the head of her father, Zeus, though these central figures are now lost.
Scholars have tentitively deduced the identities of the existing figures as follows (left to right):
- Helios (god of the sun), only the shoulder and arm survive
- Horse, which was part of a quadriga (four-horse chariot) pulling Helios
- Dionysus (god of wine), lounging
- Persephone (daughter of Zeus, abducted by Hades), seated beside her mother Demeter
- Demeter (goddess of the law, marriage, the seasons, and the harvest), seated between her daugther and the standing figure of Artemis
- Artemis (goddess of the hunt), shown turning from the central scene
- a gap, which likely would have been occupied by Zeus and Athena
- Hestia (goddess of the hearth, later Roman equivilent was Vesta), seated beside Dione
- Dione seated beside Hestia provides a lap for her daugther Aphrodite. Her name is the feminine varient of Zeus, she is sometimes seen as an equivelent of Gaia, goddess of the Earth
- Aphrodite (goddess of love and beauty), leans against her mother Dione
- Horse, thought to belong to either the setting moon (Selene) or night (Nyx)


65 Robert Frost, “The Lockless Door,” 1920
It went many years,
But at last came a knock,
And I thought of the door
With no lock to lock.
I blew out the light,
I tip-toed the floor,
And raised both hands
In prayer to the door.
But the knock came again
My window was wide;
I climbed on the sill
And descended outside.
Back over the sill
I bade a “Come in”
To whoever the knock
At the door may have been.
So at a knock
I emptied my cage
To hide in the world
And alter with age.
Robert Lee Frost (March 26, 1874 – January 29, 1963) was an American poet. His work was initially published in England before it was published in America. He is highly regarded for his realistic depictions of rural life and his command of American colloquial speech. His work frequently employed settings from rural life in New England in the early twentieth century, using them to examine complex social and philosophical themes. One of the most popular and critically respected American poets of the twentieth century, Frost was honored frequently during his lifetime, receiving four Pulitzer Prizes for Poetry. He became one of America’s rare “public literary figures, almost an artistic institution.” He was awarded the Congressional Gold Medal in 1960 for his poetic works. On July 22, 1961, Frost was named poet laureate of Vermont.


Teaching Reproducibility to First Year College Students:
Reflections From an Introductory Data Science Course
Brennan Bean, Ph.D.
Abstract
Modern technology threatens traditional modes of classroom assessment by providing students with automated ways to write essays and take exams. At the same time, modern technology continues to expand the accessibility of computational tools that promise to increase the potential scope and quality of class projects. This paper presents a case study where students are asked to complete a “reproducible” final project in an introductory data science course using the R programming language. A reproducible project is one where an instructor can easily regenerate the results and conclusions from the submitted materials. Experiences in two small sections of this introductory class suggest that reproducible projects are feasible to implement with only a little increase in assessment difficulty. The sample assignment presented in this paper, along with some proposed adaptations for non-data science classes, provide a pattern for directly assessing a student’s analysis, rather than just the final results.
Keywords: data science, reproducibility, programming, assessment
1 Introduction
Academic progress relies on the ability to build upon existing knowledge. This concept is reinforced in classrooms where instructors challenge their students to demonstrate their understanding of course information in a final report, experiment, or presentation. However, effectiveness of classroom assessments is reduced when students are unable to replicate or reproduce their submitted results. Unfortunately, issues with reproducibility are common. For example, Baker (2016) reported from a survey of 1,576 scientific researchers that:
- 90% felt that there was a slight to significant “reproducibility crises” in the sciences,
- 70% have tried, and failed, to reproduce (i.e. replicate) another scientist’s experiments,
- more than 50% have failed to reproduce their own experiments.
The widespread difficulty with scientific reproducibility has resulted in multiple instances of high profile researchers building careers on falsified/altered data (Dahlberg, 2018; Kim, 2023). While Fanelli (2018) argues these reported difficulties in reproducibility fall short of a crises, these statistics and stories highlight the importance of teaching our students how to conduct analyses that can be reproduced and/or replicated by others.
The notion of reproducibility is sometimes conflated with the terms repeatability and/or replicability. The National Academies of Sciences Engineering and Medicine (NASEM, 2019) distinguish these terms as:
- Reproducibility: obtaining consistent results using the same input data; computational steps, methods and code; and conditions of analysis.
- Replicability: obtaining consistent results across studies aimed at answering the same scientific questions, each of which has obtained its own data.
The NASEM definition of reproducibility motivates a classroom-centric definition of reproducibility:
- Classroom Reproducibility: the ability of an instructor to easily regenerate the results and conclusions of a student report from the submitted materials.
Use of the term “easily” in this definition suggests that the student has appropriately organized the submitted materials so that little manual or computational effort is required on the part of the instructor to regenerate the results. The definition implies that the instructor is able to evaluate both the final report, as well as the analysis that preceded it. The need for reproducibility in classroom assignments stems from recent technological advances that threaten traditional norms of assessment. To illustrate this, Figure 1 proposes a model of classroom assessment that is adapted from many of analysis workflows that exist in data science (Stodden, 2020; Wing, 2019; Keller et al., 2020; Boenig-Liptsin et al., 2022) and mathematical modeling literature (Doerr et al., 2017; Anhalt et al., 2018). This includes a mathematical modeling workflow in the Common Core State Standards for Mathematics (CCSSM, 2010).
Figure 1 is a workflow designed to apply across disciplines and assessment types. For example, many students use course materials (information) and feedback on previous assignments (experience) to evaluate exam question prompts (analysis) and provide final answers (insight). On term projects, students couple course materials (information) with their personal interests (experience) to propose and answer a research question (analysis) as documented in a final report (insight). Two key components of the workflow are that (1) analysis (i.e., learning) is more than a simple regurgitation of information and (2) analysis and insight are related, yet separate and distinct, steps in the workflow. Ideally, the communicated insight from the project will provide the student and others with new information and experiences that will benefit future analyses.
Most classroom assessments focus on evaluating student insight. Such assessments implicitly assume that the communicated insight is directly reflective of the analysis that preceded it. However, online resources and modern technology obscure the relationship between analysis and insight. For example, ChatGPT (openAI, 2023) has already proven to perform better than average on tests across many disciplines (Lo, 2023) and has been used to write student essays (Stokel-Walker, 2022) and scientific research papers (Stokel-Walker, 2023). While modern artificial intelligence (AI) systems may provide correct answers to assessments, those answers do not imply an understanding of the material being assessed. This fact is admitted by ChatGPT itself in a reply to the query “Do you understand the meaning of the things that you tell me?”:
When the connection between analysis and insight is lost, so is the efficacy of traditional classroom assessment. That in mind, there is evidence to suggest that AI has potential to improve learning and educational outcomes (Chen, Jensen, Albert, Gupta, & Lee, 2023). This includes the use of AI systems to teach computer programming syntax (Perkel, 2023). Rather than ban AI use in the classroom, this paper proposes modes of assessment that more directly assess a student’s analysis, rather than just the communicated insight. This paper illustrates the feasibility of this approach in an introductory data science course, where students are able to create a reproducible final project in the R programming language.
This paper proceeds with a brief history on the notion of reproducible reports along with a summary of existing software tools that facilitate the creation of such reports. This is followed by a description of a reproducible final project as administered in an introductory data science course at Utah State University (USU). This paper concludes with a reflection on the potential opportunities, adaptations, and limitations of expanding and generalizing reproducible assignments to other courses. The article demonstrates the feasibility of incorporating reproducibility into assignments with only small adjustments to traditional assessment approaches.
2 Literature
Discussions regarding computational reproducibility have been ongoing since at least the mid-1990s, when Knuth (1992) used the term literate programming to describe a combination of computer code and text as a way of making a computational analysis easier for humans to read and understand. This was followed by Buckheit and Donoho (1995), who described really reproducible research as one in which the software environment and code would be made widely available for others to inspect, modify, and apply. Gentleman and Lang (2007) built upon these ideas when they proposed the idea of a research compendium, which is a combination of data, software and dynamic documents that allow others to reproduce all research results. It is the idea of the research compendium that motivates the final project described later in this paper.
Dynamic documents contain text, code, and data that can be quickly recalculated each time the document is generated. Perhaps the most popular example of software for creating dynamic documents is Jupyter Notebooks (Jupyter, 2023). These notebooks allow users to integrate text with code from over 40 different programming languages that can be run interactively. Another popular dynamic document software is Rmarkdown (Allaire et al., 2023), which is designed to work with the Rstudio Integrated Development Environment (IDE) (Posit, 2023b) for the R programming language (R Core Team, 2023). (Please see Chapter 40 of (Irizarry, 2022) for additional details about using Rmarkdown in reproducible data analysis projects.) There are also several extensions/companions of Rmarkdown designed for creating dynamically generated slides and lecture notes for teaching (Dogucu & Çetinkaya Rundel, 2022). Continual improvements to these and other software implementations make these dynamic document generating tools increasingly accessible to larger and larger audiences. For example, Bryant et al. (2019) demonstrated the successful use of Jupyter Notebooks to teach programming to middle school students with little prior programming experience.
Modern technological advances continue to increase the accessibility of dynamic document software while simultaneously reducing the computation time necessary to render them. This increased accessibility prompted Somers (2018) to call the scientific paper “obsolete” in favor of a future world filled with dynamic documents that communicate research results interactively. Some academic journals have partially caught hold of this idea by now insisting that the results of submitted papers be reproducible (Nature, 2018; JASA, 2022; R Journal, 2023). However, a review of the literature suggests that the push for reproducibility in both research and teaching has been concentrated in statistics, data science, and computer science. This may be due to the perceived difficulty of incorporating computer programming into non-computer programming courses. Section 3 of this paper aims to illustrate that the implementation of reproducible reports in an introductory course may be more accessible to both students and instructors than might be initially perceived.
3 Case Study: Stat 1080 Final Projects
STAT 1080: Foundations of Data Science is a course that satisfies USU’s quantitative literacy (QL) general education requirement. The course is designed to be accessible to students of all majors with minimal prerequisites beyond remedial mathematics. The course uses R programming to teach key concepts of statistics and data science. The final project described in this paper has been administered to two small sections of this course—one taught in the Fall 2022 semester (eight students) and another in the Spring 2023 semester (five students). Student backgrounds have varied significantly—from first semester freshman and/or students with little programming or statistics experience, to last semester seniors with extensive statistics and/or programming experience.
Throughout the semester, students complete four homework assignments where they demonstrate the ability to clean, shape, visualize, and analyze data. All data that are necessary to complete homework assignments are made available either in the dslabs (Irizarry & Gill, 2021) R package, available on the Comprehensive R Archive Network (CRAN, 2023), or the stat1080r package (Bean, 2022), which is a software package available at https://github.com/beanb2/stat1080r. Students install this software on their machine and answer prompts in an Rmarkdown (.Rmd) file, which renders an .html report. Figure 2 (top) shows a snippet of a .Rmd file as opened in the Rstudio IDE, while Figure 2 (bottom) shows the corresponding .html output. Notice that the computer code in Figure 2 includes comments that are preceded by a #. Code comments provide students with an opportunity to provide verbal explanations of their code or links to references where they obtained sample code. The key feature of the .Rmd file is the ability of the student to provide the code used for analysis alongside their written insight in a single document.
Students are required to submit the completed .Rmd file on Canvas, which is USU’s current Learning Management System (LMS). The instructor then downloads the .Rmd files and renders each file to its corresponding .html output prior to assessment. The rendering from .Rmd to .html by the instructor ensures that all the code submitted by each student is fully executable. Students are assessed on both the correctness of their text responses along with the validity of the executed code. For homework assignments, 10% of the assignment points are awarded based on the proper formatting and successful execution of the .Rmd document.
The biggest difference between a .Rmd submission and a more traditional Canvas submission is the need for the instructor to download and regenerate the .html report on their own computer. This prevents the instructor from using the convenient document preview features that are common in many LMSs, which may increase grading time. This potential increase in grading time is offset by the natural way that the .Rmd file gives the instructor to evaluate the work of the student, which is especially useful for partial credit assessments.
3.1 Final Project Description
The homework assignments are designed to prepare students for the reproducible final projects, which are completed in groups of 3–4 students. Students are asked to analyze an external dataset of their choosing, often found on websites such as Kaggle (https://www.kaggle.com/). Students first submit a project proposal that briefly describes their dataset along with the questions they intend to explore. The proposal ensures that students select data sources already organized in tables, with rows representing observations and columns representing variables. This avoids handling more complicated data forms, (e.g. images and sound) that tend to have much larger file sizes and require analysis techniques that fall beyond the scope of an introductory course. Students are also encouraged to analyze datasets with 10,000 observations or less in order to reduce the logistical difficulties of uploading and downloading large file sizes on the LMS. These recommendations could be relaxed in smaller, more advanced, courses with students who have prior experience with database management.
Students are encouraged to follow the general principles of a research compendium (Gentleman & Lang, 2007) using the ever-improving software tools available in R (Marwick, Boettiger, & Mullen, 2018). Students are expected to pattern their submissions after the example available at the following link:
https://github.com/beanb2/stat1080 final project example
For convenience, Figure 3 provides a screenshot of this repository. Students are encouraged, though not required, to adopt identical folder names for their projects. A brief summary of each file/folder is provided below. Note that this proposed file organization is simpler than other file organization structures proposed for use in course/workshop projects using R (Mehta & Moore, 2022; Ball et al., 2022).
- data-raw/ This folder contains all original data files relevant to the final project report. Students are discouraged from making any alterations to the original data files besides those that are scripted in the .Rmd code. For data that requires significant cleaning prior to use, students may elect to write a separate .R script that creates a clean version of the data for use in their markdown file.
- scripts/ As previously mentioned, large datasets and complicated analyses are discouraged for use in STAT 1080 projects. That in mind, there is still the possibility that students need to perform computations that take a long time to run. In more advanced courses, students may also need to write custom programming functions to accomplish tasks. The scripts folder provides a space for students to include code that is too computationally intensive to include in the .Rmd report. Any interim datasets that are created by .R files in this folder should be saved in the data-raw folder.
- final_project_report.Rmd/html These files constitute the final report that will be regenerated by the instructor at the time of grading. As illustrated in Figure 2, the .Rmd file contains the text and code while the .html file contains the output of the executed .Rmd file. In order for the analysis to be reproducible, the instructor should be able to run the .Rmd file and regenerate the .html without having to alter any of the files.
- stat1080 final project example.Rproj This file is for convenience in working with projects involving R code. Opening a .Rproj file creates a new R Studio IDE session with the working directory set to the location of the .Rproj file. This file is not necessary, however, as Rstudio always uses the location of the .Rmd file as the working directory when rendering the .html file.
The specification of a working directory via the .Rproj file allows for the use of relative file paths when reading and writing other files within the project. Unlike full file paths, which are unique for every computer and user, relative file paths do not need to be altered when the project is moved to another computer. For example, the R code for reading in a data file from the example project on any computer using relative file paths would simply be
read.csv("data-raw/kc_house_data.csv").
Additional details on file paths can be found in Chapter 5 of Irizarry (2022).
3.2 Final Project Assessment
Students are required to submit a compressed folder (.zip) of their final project on the LMS. The LMS restricts the file upload type to ensure that students do not only submit a single file. The instructor then completes the following steps:
- Download and decompress the submitted zip folder.
- Open the .Rproj file.
- Open the .Rmd file within the R project.
- Run an automatic check for proper code formatting using the lintr package (Hester et al., 2022).
- Render the .html file from the .Rmd file.
- Assess the .html file like any other final report.
Steps 1–5 take less than one minute to complete, making the increased grading time minimal compared to a more traditional assessment workflow that starts at Step 6. This process could be easily adapted to other dynamic document types, such as Jupyter notebooks. Proper formatting of the project and successful rendering of the code constitutes 10% of the final project grade. The submitted code, along with any errors generated when the instructor attempts to run the code, provide a record of student effort that aids the instructor when assessing the appropriateness of the analysis and drafting a detailed instructor review.
The instructor review follows the pattern used for peer-reviewed journals, where students are required to articulate what changes they made to each instructor comment using a different colored font. Students are provided with a template review response document that includes the following instructions and example:
You will be given the opportunity to resubmit your assignment for full points if you address my comments. Please include this response to review document inside of your R project when you resubmit. You should provide a response, colored in red, outlining how you addressed each comment. Here is a generic example of how this might look (this comment is not specific to any submission):
The interpretation of your p-value in your “Methods” section is not fully correct. The p-value is NOT the probability that the null hypothesis is true. Please revise.
The p-value interpretation has been revised to indicate that it represents the probability of observing something as far (or farther) away from the assumed average.
Students who sufficiently improve their project submissions based on instructor feedback and appropriately respond to review receive full points on the final project. The approach of assigning full points after a successful response to review is inspired by the “ungrading” ideas outlined in (Blum, 2020), though a full discussion of this approach to assessment falls outside the scope of this paper.
4 Reflections, Limitations, and Adaptions
So far in STAT 1080, the management and assessment of the reproducible final projects has proceeded with almost no difficulty beyond what would be typical for a regular final project report. All students have been able to successfully create reproducible final projects with little intervention on the part of the instructor. This success highlights the ability of students to effectively learn how to organize and execute a reproducible analysis. Further, the submission format for both final project and homework assignments has proven beneficial for assigning partial credit to student responses. This is because the work (i.e. computer program) underlying each answer must be provided by the student. This allows the instructor to quickly pinpoint an error in student work by interactively running portions of the submitted code. This type of interactive error checking is something that would not be possible if students only reported on the final output. However, assessment can be difficult in instances where the student’s .Rmd files fail to properly render to an .html file, as this requires the instructor to identify and remove the error-prone code before evaluating the remainder of the document.
One limitation of the reproducible final projects is the need for students to know or learn basic computer programming. That in mind, many software programs, such as SAS Enterprise Guide (Hemedinger & McDaniel, 2005), provide ways to generate computer code based on point-and-click actions taken by the user. Another potential way to circumvent this issue is to use more common software systems, such as Microsoft Excel, for analysis. The final project example described in Section 3.1 provides an example of an excel workbook in the data-raw that includes a visual similar to one of the visuals in the rendered .html file. The six steps of assessment presented in Section 3.2 would be nearly identical for an Excel submission, except that students would need to provide an already “rendered” .docx or .pdf document that copies/pastes the visuals provided in the excel file into the final report. Keep in mind that any assignment using Excel as the primary means of analysis would be at risk of the all-too-common copy/paste errors associated with point-and-click software systems (Horton, Alexander, Parker, Piekut, & Rundel, 2022; Perkel, 2022).
A third way this project could be adapted would be to have the student provide an analysis journal. An analysis journal is similar to the idea of using an electronic portfolio as a means of assessment (Buzzetto-More, 2010) and may include:
- transcripts of any ChatGPT inquiries and output related to the project,
- a step-by-step description of all changes that were made to the original data using point-and-click software,
- a daily or weekly project log where students describe key moments in their research progress over time,
- a review response document where students outline the changes they made to their final draft based on feedback from a writing tutor or peer.
The assessment of the analysis journal would be similar to assessing any other technical writing. Emphasis would be placed on writing that clearly communicates the student’s progression from initial idea to final product. Instructors may choose to relax formatting requirements for these documents as long as the formatting does not distract from the student’s articulation of their research steps. The critical element of any reproducible project adaptation is a way for the student to clearly communicate the process by which the final report was developed though the submission of secondary files.
Another potential issue with reproducible final projects is that such projects require that students and instructors use the same software versions. While many programming languages and their associated IDE’s are freely available, there is the potential for an increased burden on the part of the instructor to troubleshoot specific student installation issues. Hopefully, these issues would be concentrated in the first two weeks of the semester. One way to overcome this issue is to use cloud-based computing platforms, such as those as employed by the introductory data science class at the University of California, Berkeley (UCB, 2023). For R users, one convenient option is Posit cloud, which includes an instructor-level subscription service (Posit, 2023a).
One final limitation of reproducible final projects specific to STAT 1080 is the prevailing culture of making data science projects publicly accessible, also called open-source. While open-source projects accelerate learning and research, they also mean there are many community contributed analysis examples that students could try to copy for their final projects. One potential solution to this problem is to have students collect and use their own data, perhaps collected throughout the semester, for their final projects. For example, STAT 1080 includes a personal data collection project based on the Feltron Annual Reports (e.g. http://feltron.com/FAR13.html) that could potentially be expanded into a reproducible assessment that replaces the current final projects in the course.
5 Conclusions
Several scholars have expressed the idea that “writing is thinking” (McCullough, 2002; Mintz, 2021). This paper argues that computer programming is a form of modern writing that can be directly evaluated in reproducible assignments. This is not to suggest that all students need to be expert programmers, but simply that all students should learn basic skills in project organization, and perhaps computer programming, that allows their ideas to be reproduced and enhanced by others. Experience in STAT 1080 suggests that students can quickly capitalize on the many tools that make reproducibility feasible with minimal training. This paper has described the implementation of a final project in an introductory data science class that fosters reproducibility and proposed adaptations to the implementation to work for non-programming audiences. The proposed adaptations only require minor adjustments by the instructor for grading, namely downloading and decompressing a zip folder instead of using a LMS document preview feature. In so doing, this paper has demonstrated the feasibility with which reproducibility can be taught and assessed in undergraduate courses. It seems inevitable that the societies and economies of tomorrow will be increasingly characterized by AI, automation, and computation. No academic discipline will be immune to the increased demands for computational ability from their graduates. Small steps, such as the teaching of basic computer programming skills for the purpose of creating reproducible projects, will teach students critical skills in project organization and management that will prepare them to thrive within the computational systems shaping modern life. Further, such assignments will improve our ability to evaluate student learning in a technology-saturated world that blurs the line between output and understanding.
References
Allaire, J., Xie, Y., Dervieux, C., McPherson, J., Luraschi, J., Ushey, K., . . . Iannone, R. (2023). rmarkdown: Dynamic documents for R [Computer software manual]. Retrieved from https://github.com/rstudio/rmarkdown (R package version 2.22)
Anhalt, C. O., Cortez, R., & Bennett, A. B. (2018). The emergence of mathematical modeling competencies: An investigation of prospective secondary mathematics teachers. Mathematical Thinking and Learning, 20 (3), 202-221. Retrieved from https://doi.org/10.1080/10986065.2018.1474532
Baker, M. (2016, May 01). 1,500 scientists lift the lid on reproducibility. Nature, 533 (7604), 452-454. Retrieved from https://doi.org/10.1038/533452a
Ball, R., Medeiros, N., Bussberg, N. W., & Piekut, A. (2022). An invitation to teaching reproducible research: Lessons from a symposium. Journal of Statistics and Data Science Education, 30 (3), 209-218. Retrieved from https://doi.org/10.1080/26939169.2022.2099489
Bean, B. (2022). stat1080r: Functions and datasets for stat 1080: Foundations of data science [Computer software manual]. Retrieved from https://github.com/beanb2/stat1080r (R package version 0.1.0)
Blum, S. D. (2020). Ungrading: Why rating students undermines learning (and what to do instead). West Virginia University Press. Retrieved from https://www.wvupressonline.com/ungrading
Boenig-Liptsin, M., Tanweer, A., & Edmundson, A. (2022). Data science ethos lifecycle: Interplay of ethical thinking and data science practice. Journal of Statistics and Data Science Education, 30 (3), 228-240. Retrieved from https://doi.org/10.1080/26939169.2022.2089411
Bryant, C., Chen, Y., Chen, Z., Gilmour, J., Gumidyala, S., Herce-Hagiwara, B., . . . Rebelsky, S. A. (2019). A middle-school camp emphasizing data science and computing for social good. In Proceedings of the 50th acm technical symposium on computer science education (p. 358–364). New York, NY, USA: Association for Computing Machinery. Retrieved from https://doi.org/10.1145/3287324.3287510
Buckheit, J. B., & Donoho, D. L. (1995). Wavelab and reproducible research. In A. Antoniadis & G. Oppenheim (Eds.), Wavelets and statistics (pp. 55–81). New York, NY: Springer New York. Retrieved from https://doi.org/10.1007/978-1-4612-2544-75
Buzzetto-More, N. (2010). Assessing the efficacy and effectiveness of an e-portfolio used for summative assessment. Interdisciplinary Journal of e-Learning and Learning Objects, 6 (1), 61–85.
CCSSM. (2010). Common core state standards for mathematics. Retrieved from https://www.thecorestandards.org/Math/ (Page 72. Accessed: 6-20-2023)
Chen, Y., Jensen, S., Albert, L. J., Gupta, S., & Lee, T. (2023). Artificial intelligence (AI) student assistants in the classroom: Designing chatbots to support student success. Information Systems Frontiers, 25 (1), 161–182. Retrieved from https://doi.org/10.1007/s10796-022-10291-4
CRAN. (2023). The Comprehensive R Archive Network. Retrieved from https://cran.r-project.org/ (Accessed: 6-16-2023)
Dahlberg, B. (2018). Cornell food researcher’s downfall raises larger questions for science. Retrieved from https://www.npr.org/sections/thesalt/2018/09/26/651849441/cornell-food-researchers-downfall-raises-larger-questions-for-science (Accessed: 6-23-2023)
Doerr, H. M., Ärlebäck, J. B., & Misfeldt, M. (2017). Representations of modelling in mathematics education. Mathematical modelling and applications: Crossing and researching boundaries in mathematics education, 71–81. Retrieved from https://doi.org/ 10.1007/978-3-319-62968-1 6
Dogucu, M., & Çetinkaya Rundel, M. (2022). Tools and recommendations for reproducible teaching. Journal of Statistics and Data Science Education, 30 (3), 251-260. Retrieved from https://doi.org/10.1080/26939169.2022.2138645 doi: 10.1080/26939169.2022.2138645
Fanelli, D. (2018). Is science really facing a reproducibility crisis, and do we need it to? Proceedings of the National Academy of Sciences, 115 (11), 2628–2631. Retrieved from https://doi.org/10.1073/pnas.1708272114
Gentleman, R., & Lang, D. T. (2007). Statistical analyses and reproducible research. Journal of Computational and Graphical Statistics, 16 (1), 1-23. Retrieved from https://doi.org/10.1198/106186007X178663
Hemedinger, C., & McDaniel, S. (2005). The new world of SAS: Programming with SAS enterprise guide. In Proceedings of the thirtieth annual SAS users group international conference. Retrieved from https://support.sas.com/resources/papers/proceedings/proceedings/sugi30/050-30.pdf (Accessed: 6-16-2023)
Hester, J., Angly, F., Hyde, R., Chirico, M., Ren, K., Rosenstock, A., & Patil, I. (2022). lintr: A ’Linter’ for R code [Computer software manual]. Retrieved from https://CRAN.R-project.org/package=lintr (R package version 3.0.2)
Horton, N. J., Alexander, R., Parker, M., Piekut, A., & Rundel, C. (2022). The growing importance of reproducibility and responsible workflow in the data science and statistics curriculum. Journal of Statistics and Data Science Education, 30 (3), 207-208. Retrieved from https://doi.org/10.1080/26939169.2022.2141001
Irizarry, R. A. (2022). Introduction to data science: Data analysis and prediction algorithms with R. Retrieved from https://rafalab.dfci.harvard.edu/dsbook/ (Last Book Update: 12-05-2022)
Irizarry, R. A., & Gill, A. (2021). dslabs: Data science labs [Computer software manual]. Retrieved from https://CRAN.R-project.org/package=dslabs (R package version 0.7.4)
JASA. (2022). The JASA reproducibility guide. Retrieved from https://jasa-acs.github.io/repro-guide/ (Accessed: 6-28-2023)
Jupyter. (2023). Project Jupyter. Retrieved from https://jupyter.org/ (Accessed: 6-16-2023)
Keller, S. A., Shipp, S. S., Schroeder, A. D., & Korkmaz, G. (2020, feb 21). Doing data science: A framework and case study. Harvard Data Science Review, 2 (1). (https://hdsr.mitpress.mit.edu/pub/hnptx6lq)
Kim, J. (2023). Harvard professor who studies dishonesty is accused of falsifying data. Retrieved from https://www.npr.org/2023/06/26/1184289296/harvard-professor-dishonesty-francesca-gino (Accessed: 6-23-2023)
Knuth, D. E. (1992). Literate programming. CLSI Publications. Retrieved from https://web.stanford.edu/group/cslipublications/cslipublications/site/0937073806.shtml
Lo, C. K. (2023). What is the impact of ChatGPT on education? A rapid review of the literature. Education Sciences, 13 (4). Retrieved from https://www.mdpi.com/ 2227-7102/13/4/410
Marwick, B., Boettiger, C., & Mullen, L. (2018). Packaging data analytical work reproducibly using r (and friends). The American Statistician, 72 (1), 80-88. Retrieved from https://doi.org/10.1080/00031305.2017.1375986
McCullough, D. (2002). David McCullough quotes. Retrieved from https://www.goodreads.com/author/quotes/6281688.David McCullough (Accessed: 6-27-2023)
Mehta, C. C., & Moore, R. H. (2022). Third time’s a charm: A tripartite approach for teaching project organization to students. Journal of Statistics and Data Science Education, 30 (3), 261-265. Retrieved from https://doi.org/10.1080/26939169.2022.2118644
Mintz, S. (2021). Writing is thinking. Retrieved from https://www.insidehighered.com/blogs/higher-ed-gamma/writing-thinking (Accessed: 6-27-2023)
NASEM. (2019). Reproducibility and replicability in science. National Academies Press. Retrieved from https://nap.nationalacademies.org/catalog/25303/ reproducibility-and-replicability-in-science (Accessed: 6-28-2023)
Nature. (2018). Does your code stand up to scrutiny? Retrieved from https://www.nature.com/articles/d41586-018-02741-4 (Accessed: 6-28-2023)
openAI. (2023). Introducing ChatGPT. Retrieved from https://openai.com/blog/chatgpt (Accessed: 6-27-2023)
Perkel, J. M. (2022). Cut the tyranny of copy-and-paste with these coding tools. Nature. Retrieved from https://doi.org/10.1038/d41586-022-00563-z
Perkel, J. M. (2023, June). Six tips for better coding with ChatGPT. Nature. Retrieved from https://doi.org/10.1038/d41586-023-01833-0
Posit. (2023a). Friction free data science. Retrieved from https://posit.cloud/ (Accessed: 6-29-2023)
Posit. (2023b). RStudio IDE. Retrieved from https://posit.co/downloads/ (Accessed: 6-16-2023)
R Core Team. (2023). R: A language and environment for statistical computing [Computer software manual]. Vienna, Austria. Retrieved from https://www.R-project.org/
R Journal. (2023). How to submit your article. Retrieved from https://journal.r-project.org/submissions.html (Accessed: 6-28-2023)
Somers, J. (2018). The scientific paper is obsolete. The Atlantic. Retrieved from https://www.theatlantic.com/science/archive/2018/04/the-scientific-paper-is-obsolete/556676/ (Accessed: 6-23-2023)
Stodden, V. (2020). The data science life cycle: A disciplined approach to advancing data science as a science. Commun. ACM, 63 (7), 58–66. Retrieved from https://doi.org/10.1145/3360646
Stokel-Walker, C. (2022, December). AI bot ChatGPT writes smart essays—should professors worry? Nature. Retrieved from https://doi.org/10.1038/d41586-022-04397-7
Stokel-Walker, C. (2023, January). ChatGPT listed as author on research papers: many scientists disapprove. Nature. Retrieved from https://doi.org/10.1038/d41586-023-00107-z
UCB. (2023). Data 8: The foundations of data science. Retrieved from https://www.data8.org/ (Accessed: 6-29-2023)
Wing, J. M. (2019, July). The Data Life Cycle. Harvard Data Science Review, 1 (1). (https://hdsr.mitpress.mit.edu/pub/577rq08d)
Acknowledgement
The author would like to thank Dr. Brynja Kohler for providing some mathematical modeling literature. Further, the author would like to thank Dr. Brynja Kohler and Dr. Carrie Bala for providing comments and insights on preliminary drafts of this manuscript that improved the final version.


W. Nee
THOU hast said Thou art the Vine, Lord,
And that I’m a branch in Thee,
But I do not know the reason
Why I should so barren be.
2
Bearing fruit is my deep longing,
More Thy life to manifest,
To Thy throne to bring more glory,
That Thy will may be expressed.
3
But I fail to understand, Lord,
What it means – “abide in Me,”
For the more I seek “abiding,”
More I feel I’m not in Thee.
4
How I feel I’m not abiding;
Though I pray and strongly will,
Yet from me Thou seemest distant,
And my life is barren still.
5
Yet Thou art the Vine, Thou saidst it,
And I am a branch in Thee;
When I take Thee as my Savior,
Then this fact is wrought in me.
6
Now I’m in Thee and I need not
Seek into Thyself to come,
For I’m joined to Thee already,
With Thy flesh and bones I’m one.
7
Not to “go in” is the secret,
But that I’m “already in!”
That I ne’er may leave I’d ask Thee,
Not how I may get within.
8
I am in, already in Thee!

There’s no need for prayer or struggling,
God Himself the work has wrought.
9
Since I’m in, why ask to enter?

Now with praise and much rejoicing
For Thy Word, I dwell therein.
10
Now in Thee I rest completely,
With myself I gladly part;
Thou art life and Thou art power,
All in all to me Thou art.


Appendix 4: Buffer formulations
- COMMONLY-USED STOCK SOLUTIONS
The following stock solutions are commonly used in the preparation of many reagents used in molecular biological procedures. Remember to use aseptic technique with sterile stocks. Use deionized or glass-distilled water to make reagents. Decrease volumes made as appropriate. It is also useful to maintain a store of steriledeionized water.
ß-mercaptoethanol (BME)
BME is purchased as a liquid at a concentration of 14.4 M. Store at 4 ˚C in a dark bottle. Do not autoclave BME or buffers containing it. Open BME in a hood.
1.0 M Calcium Chloride
Dissolve 14.7 g of CaCl2• 2H2O in 80 mL of deionized water. Adjust the volume to 100 mL with deionized water. This may be stored at room temperature indefinitely.
100 mM Calcium Chloride(for preparation of competent cells)
Add 50.0 mL of 1.0 M CaCl2to 450 mL of deionized water and mix. Sterilize by autoclaving. Store at 4 ˚C.
0.5 M EDTA, pH 8.0
Dissolve 186.1 g of disodium ethylenediaminetetraacetate•2H2O in 800 mL of deionized water that is being mixed on a magnetic stirrer. Adjust the pH to 8.0 with NaOH (about 20 g of pellets). The EDTA will not completely dissolve until the pH has reached 8.0. Add the NaOH slowly so as not to adjust the pH above 8.0. Adjust to 1000 mL with deionized water. Dispense into appropriate containers and sterilize by autoclaving. Store at room temperature.
10 mg/ mL Ethidium Bromide
Dissolve 0.25 g of ethidium bromide in 25.0 mL of deionized water. Stir at room temperature for several hours to ensure that the dye is completely dissolved. Store in a foil-wrapped or brown glass bottle at room temperature.
3.0 M Sodium Acetate (pH 5.2) (anhydrous MW = 82.03)
Add 24.6 g of sodium acetate (anhydrous) to 70 mL of deionized water and mix to dissolve. Adjust the pH to 5.2 with glacial acetic acid. Make to 100 mL with deionized water. Sterilize by autoclaving and store at room temperature.
5.0 M Sodium Chloride
Dissolve 292.2 g of NaCl in 700 mL of deionized water. Heat may be necessary to completely dissolve the NaCl. Adjust to 1000 mL with deionized water and sterilize by autoclaving. Store at room temperature.
20% SDS
Add 200 g of molecular biology grade sodium dodecyl sulfate (often called sodium lauryl sulfate) to 800 mL of deionized water. Dissolve with heating on a hot plate. Adjust the pH to 7.2 with a few drops of 6N HCl. Adjust to 1000 mL with deionized water. Do not autoclave this stock. Store at room temperature.
4.0 N Sodium Hydroxide
Add 160 g of NaOH pellets to 800 mL of deionized water. Dissolve on a stir plate as the solution will get hot from an exothermic reaction. After all pellets are dissolved, allow the solution to cool and adjust to 1000 mL with deionized water. Store at room temperature in a polypropylene bottle (NaOH should not be stored in glass bottles).
1.0 M Tris, pH 8.0
Dissolve 121.1 g of Tris base in 800 mL of deionized water. To avoid inhalation, wear a mask when weighing out the dry powder. Adjust the pH to 8.0 with concentrated HCl (about 42 ml). Cool the solution to room temperature and adjust to 1000 mL with deionized water. Dispense into appropriate containers and sterilize by autoclaving. Store at room temperature.
NOTE: The pH of Tris buffers is temperature-dependent. Make all measurements at room temperature. The pH will decrease approximately 0.03 pH units for each degree Celsius that the temperature increases.
NOTE: Many pH electrodes do not accurately measure the hydrogen ion concentration of Tris buffers. Be sure that the electrode you are using is capable of measuring Tris.
50x TAE
242 g Tris base
57.1 mL glacial acetic acid
100 ml of 0.5 M EDTA (pH 8.0)
- DNA AND ENZYME SOLUTIONS
DNA solutions (plasmids, lambda, etc.) are generally supplied at a known concentration in TE buffer (10 mM Tris, pH 8.0; 1 mM EDTA). Dilutions of DNA stocks should be made into TE buffer. Wear gloves when handling DNA stocks and exercise caution to avoid nuclease contamination. Store DNA solutions at 4 ˚C if you are using them frequently, or at -20 ˚C for long-term storage.
Restriction enzymes, ligase, and many other DNA modifying enzymes are prepared in buffers containing 50% glycerol and must be stored at -20 ˚C. The concentrations of commercially available enzymes varies from 5-20 units/ μL, but it is best not to dilute them for use. Dilution often results in rapid loss of activity and is time-consuming. Addition of an excess amount of enzyme makes reactions proceed faster. Some enzymes are purchased as dry powders and are prepared as follows:
Lysozyme (10 mg/ mL in 10 mM Tris, pH 8.0)
Make lysozyme solution immediately (1-4 hours) before use. To 11.9 mL deionized water add, 0.12 mL of 1.0 M Tris, pH 8.0 and 0.12 g lysozyme. Dissolve the lysozyme and keep the solution on ice.
Proteinase K (10 mg/ ml)
Dissolve 25 mg of proteinase K in 2.5 mL of sterile, deionized water. Dispense into sterile microcentrifuge tubes in 500 μL aliquots and store at -20 ˚C.
RNase A (10 mg/ mL in 10 mM Tris, pH 7.6, 15 mM NaCl)
Add 50.0 μL of 1.0 M Tris, pH 7.6 , 15.0 μL of 5 M NaCl, and 50 mg of RNase A to a total volume of 5.0 mL of deionized water:
Dissolve the RNase A and place in boiling water bath for 10 minutes to inactivated any DNase that is a contaminant. Transfer to sterile microcentrifuge tubes in 500 μL aliquots and store at -20 ˚C.
Gibson cloning recipes
Gibson Master Mix Isothermal Reaction Buffer:
Makes approximately 9 mL. Store in 350 μL aliquots at -20C.
| Component | Amount |
| 1M Tris-HCl pH 7.5 | 3 mL |
| 1M MgCl2 | 300 μL |
| 100 mM dNTP | 60 μL |
| PEG-8000 | 1.5 g |
| NAD | 19.9 mg |
| 1M DTT | 300 μL |
| Water | 2.22 mL |
Gibson Master Mix:
Mix up the reagents well. The solution is rather viscous, so pipette slowly.
Make 100 uL aliquots and store at -20C.
| Component | Amount |
| Isothermal Reaction Buffer | 320 μL |
| T5 exonuclease (10U/μL) | 0.64 μL |
| Phusion DNA Polymerase (2 U/μL) | 20 μL |
| Taq DNA Ligase (40 U/μL) | 160 μL |
| Water | 700 μL |
III. MEDIA
LB (Luria-Bertani) Medium
Add to 1000 mL deionized water:
10.0 g tryptone
5.0 g yeast extract
10.0 g NaCl
Dissolve all ingredients and adjust the pH to 7.2 with NaOH (about 1 mL of 4 N NaOH). Sterilize by autoclaving. Prepare agar plates by adding 15 g/L agar prior to sterilization.
The following sterile stocks should be aseptically added to autoclaved and cooled (to 55 C) media. For cold storage, aliquot stocks into small volumes to avoid repeated freezing and thawing.
100 mg/mL IPTG
Dissolve 1.0 g of isopropylthio-ß-D-galactoside (IPTG) in 8.0 mL of deionized water. Adjust the volume to 10.0 mL with deionized water. Sterilize through a 0.2 µm membrane filter and dispense in 2-3 mL aliquots in sterile vials or tubes. Store at -20 ˚C. Add 1.0 mL per liter ofsterilizedmedium that has cooled to 55 ˚C.
NOTE: IPTG can be left out of media used for alpha-complementation if pUC or pGEM-type vectors are being used. These are such high copy number vectors that there is enough expression of the a-fragment of ß-galactosidase to obtain activity (i.e.blue colonies).
40 mg/mL X-gal
Dissolve 0.4 g of 5-bromo-4-chloro-3-indoyl-ß-D-galactoside (X-gal) in 10 mL of dimethlyformamide (DMF) in a glass or polypropylene tube. DMF WILL DISSOLVE POLYCARBONATE. Store in 2-3 mL aliquots in foil-wrapped vials at -20 ˚C. Do not sterilize. Add 1.0 mL per liter of sterilizedmedium that has cooled to 55 ˚C, giving a final concentration of 40 µg/mL.
50 mg/ mL Kanamycin
Dissolve 0.5 g of Kanamycin (sodium salt) in 10 mL of deionized water. Sterilize through a 0.2 µm membrane filter. Dispense in 2-3 mL aliquots in sterile 1-mL vials or sterile tubes. Store at -20 ˚C. Add 1.0 mL per liter of sterilizedmedium that has cooled to 55 ˚C, giving a final concentration of 50 µg/ mL. Adjust the volume added accordingly for different concentrations.
Kanamycin is stable for about a month as a stock or in agar plates stored in the refrigerator.
Buffers Needed for SDS-PAGE
For the SDS-polyacrylamide gels you poured, we provided the following reagents:
- 10% SDS Solution: 10 g of SDS dissolved in a final volume of 100 mL of deionized water;
- 40% Acrylamide Solution: This solution is 37.5:1 Acrylamide: Bis-acrylamide.
- 10% Ammonium Persulfate Solution: 0.1 g of ammonium persulfate diluted to a final volume of 1 mL with deionized water;
- TEMED: use as a neat solution;
- 4x Resolving Gel Buffer: Combine 45.42 g Tris Base and1 g SDS then add deionized water to a final volume that is almost 250 mL ,carefully adjust the pH to 8.8 with HCl, and then add enough water to bring the final volume to 250 mL.
- 4x Stacking Gel Buffer: Combine 15.14 g Tris Base and 1g SDS then add deionized water to a final volume that is almost 250 mL, carefully adjust the pH to 6.8 with HCl, and then add enough water to bring the final volume to 250mL.
- 4x SDS sample buffer: For 10 mL: Combine 2 mL 1M Tris pH 8, 0.8g SDS, 4 mL 100% glycerol, 1 mL 0.5M EDTA, and 8 mg of Bromophenol Blue and then add deionized water to final volume. Add a denaturing agent if required, such as 5% BME.
- 5X Laemmli Running Buffer:Combine 152 g Tris base, 720 g glycine, and 50 g SDS add water to a final volume of 10L. This buffer should be pH 8.5, and normally should not be adjusted;
- Staining solution: Combine 450 mL dH2O, 450 mL methanol and 100 mL glacial acetic acid. Add 1.0 g of Coomassie Blue R250. The stain can be re-used a few times but the gel may need to stay in used stain a little longer than in fresh.
- Destaining solution: Combine 875 mL dH2O, 50 mL methanol and 75 mL glacial acetic.
Buffers used for the Ni column (Lab 7)
Resuspension buffer:
50 mM NaH2PO4
300 mM NaCl
Adjust pH to 8.0 with NaOH
You are responsible for deciding on appropriate equilibration, wash and elution buffers for use on the column, so those recipes are not provided here.
Protein Buffer:
50 mM Tris, pH 7.8
0.1 M K2SO4


Unit 4: Animal Structure and Function
24.1.  Both methods have advantages and disadvantages. Asexual reproduction produces offspring that are genetically identical to the parent because the offspring are all clones of the original parent. A single individual can produce offspring asexually and large numbers of offspring can be produced quickly. In a stable or predictable environment, asexual reproduction is an effective means of reproduction because all the offspring will be adapted to that environment. In an unstable or unpredictable environment asexually-reproducing species may be at a disadvantage because all the offspring are genetically identical and may not have the genetic variation to survive in new or different conditions. On the other hand, the rapid rates of asexual reproduction may allow for a speedy response to environmental changes if individuals have mutations. An additional advantage of asexual reproduction is that colonization of new habitats may be easier when an individual does not need to find a mate to reproduce.
Asexual Reproduction
Asexual reproduction occurs in prokaryotic microorganisms (bacteria) and in some eukaryotic single-celled and multi-celled organisms. There are a number of ways that animals reproduce asexually.
Fission
Fission
, also called binary fission, occurs in prokaryotic microorganisms and in some invertebrate, multi-celled organisms. After a period of growth, an organism splits into two separate organisms. Some unicellular eukaryotic organisms undergo binary fission by mitosis. In other organisms, part of the individual separates and forms a second individual. This process occurs, for example, in many asteroid echinoderms through splitting of the central disk. Some sea anemones and some coral polyps (Figure 24.2) also reproduce through fission.
Budding
Budding is a form of asexual reproduction that results from the outgrowth of a part of a cell or body region leading to a separation from the original organism into two individuals. Budding occurs commonly in some invertebrate animals such as corals and hydras. In hydras, a bud forms that develops into an adult and breaks away from the main body, as illustrated in Figure 24.3, whereas in coral budding, the bud does not detach and multiplies as part of a new colony.
Concept in Action
Watch a video of a hydra budding.
Fragmentation
For example, in many sea stars, asexual reproduction is accomplished by fragmentation. Figure 24.4 illustrates a sea star for which an arm of the individual is broken off and regenerates a new sea star. Fisheries workers have been known to try to kill the sea stars eating their clam or oyster beds by cutting them in half and throwing them back into the ocean. Unfortunately for the workers, the two parts can each regenerate a new half, resulting in twice as many sea stars to prey upon the oysters and clams. Fragmentation also occurs in annelid worms, turbellarians, and poriferans.
Note that in fragmentation, there is generally a noticeable difference in the size of the individuals, whereas in fission, two individuals of approximate size are formed.
Parthenogenesis
Some vertebrate animals—such as certain reptiles, amphibians, and fish—also reproduce through parthenogenesis. Although more common in plants, parthenogenesis has been observed in animal species that were segregated by sex in terrestrial or marine zoos. Two female Komodo dragons, a hammerhead shark, and a blacktop shark have produced parthenogenic young when the females have been isolated from males.
Sexual Reproduction
Sexual reproduction is the combination of (usually haploid) reproductive cells from two individuals to form a third (usually diploid) unique offspring. Sexual reproduction produces offspring with novel combinations of genes. This can be an adaptive advantage in unstable or unpredictable environments. As humans, we are used to thinking of animals as having two separate sexes—male and female—determined at conception. However, in the animal kingdom, there are many variations on this theme.
Hermaphroditism
Hermaphroditism occurs in animals where one individual has both male and female reproductive parts. Invertebrates such as earthworms, slugs, tapeworms and snails, shown in Figure 24.5, are often hermaphroditic. Hermaphrodites may self-fertilize or may mate with another of their species, fertilizing each other and both producing offspring. Self fertilization is common in animals that have limited mobility or are not motile, such as barnacles and clams.
 Individuals homozygous for X (XX) are female and heterozygous individuals (XY) are male. The presence of a Y chromosome causes the development of male characteristics and its absence results in female characteristics. The XY system is also found in some insects and plants.
Avian sex determination is dependent on the presence of Z and W chromosomes. Homozygous for Z (ZZ) results in a male and heterozygous (ZW) results in a female. The W appears to be essential in determining the sex of the individual, similar to the Y chromosome in mammals. Some fish, crustaceans, insects (such as butterflies and moths), and reptiles use this system.
The sex of some species is not determined by genetics but by some aspect of the environment. Sex determination in some crocodiles and turtles, for example, is often dependent on the temperature during critical periods of egg development. This is referred to as environmental sex determination, or more specifically as temperature-dependent sex determination. In many turtles, cooler temperatures during egg incubation produce males and warm temperatures produce females. In some crocodiles, moderate temperatures produce males and both warm and cool temperatures produce females. In some species, sex is both genetic- and temperature-dependent.
 If the individual is female first, it is termed protogyny or “first female,” if it is male first, its termed protandry or “first male.”
Summary
Reproduction may be asexual when one individual produces genetically identical offspring, or sexual when the genetic material from two individuals is combined to produce genetically diverse offspring. Asexual reproduction occurs through fission, budding, and fragmentation. Sexual reproduction may mean the joining of sperm and eggs within animals’ bodies or it may mean the release of sperm and eggs into the environment. An individual may be one sex, or both; it may start out as one sex and switch during its life, or it may stay male or female.
 Which form of reproduction can result from damage to the original animal?
A) asexual
B) fragmentation
C) budding
D) parthenogenesis
3. Which form of reproduction is useful to an animal with little mobility that reproduces sexually?
A) fission
B) budding
C) parthenogenesis
D) hermaphroditism
4. Genetically unique individuals are produced through ________.
A) sexual reproduction
B) parthenogenesis
C) budding
D) fragmentation
Sexual reproduction produces a new combination of genes in the offspring that may better enable them to survive changes in the environment and assist in the survival of the species.
The presence of the W chromosome in birds determines femaleness and the presence of the Y chromosome in mammals determines maleness. The absence of those chromosomes and the homogeneity of the offspring (ZZ or XX) leads to the development of the other sex.
Glossary
- asexual reproduction
- form of reproduction that produces offspring that are genetically identical to the parent
- budding
- form of asexual reproduction that results from the outgrowth of a part of a cell leading to a separation from the original animal into two individuals
- fission
- (also, binary fission) method by which multicellular organisms increase in size or asexual reproduction in which a unicellular organism splits into two separate organisms by mitosis
- fragmentation
- cutting or fragmenting of the original animal into parts and the growth of a separate animal from each part
- hermaphroditism
- state of having both male and female reproductive parts within the same individual
- parthenogenesis
- form of asexual reproduction where an egg develops into a complete individual without being fertilized
- sexual reproduction
- mixing of genetic material from two individuals to produce genetically unique offspring


Worship
F.J. Crosby
HOLY, holy, holy is the Lord!
Sing, O ye people, gladly adore Him;
Let the mountains tremble at His word,
Let the hills be joyful before Him;
Mighty in wisdom, boundless in mercy,
Great is Jehovah, King over all.
Holy, holy, holy is the Lord!
Let the hills be joyful before Him.
2
Praise Him, praise Him, shout aloud for joy,
Watchman of Zion, herald the story;
Sin and death His kingdom shall destroy;
All the earth shall sing of His glory;
Praise Him, ye angels, ye who behold Him
Robed in His splendor, matchless, divine.
3
King eternal, blessed be His name!
So may His children gladly adore Him;
When in heav’n we join the happy strain,
When we cast our bright crowns before Him;
There in His likeness joyful awaking,
There we shall see Him, there we shall sing.


Science
104 Lineage Tracing in Zebrafish with CRISPR Prime Editing
Sahar Kanishka and James A. Gagnon (School of Biological Sciences)
Faculty Mentor: James Gagnon (School of Biological Sciences, University of Utah)
All embryos develop from a single cell. We use lineage tracing to map the relationships between individual cells and back to the initial founding cell. These lineage trees can help us understand how cells acquire their fates during normal development, and how that can go wrong in human disease. An emerging method for lineage tracing in embryos uses cellular barcodes. Cellular barcodes individually tag cells with a unique set of mutations specific to that cell. As cell divisions occur, the barcode is passed on to the progeny cells and a lineage tree can constructed based on cells that share similar barcodes. The CRISPR-Cas9 system for gene editing is an ideal tool for creating a huge diversity of cellular barcodes in embryos. However, there are limitations with CRISPR-Cas9, including unpredictable indel formation and difficulties in recovering barcodes from cells. In this project, a modified CRISPR system known as prime editing will be applied in zebrafish, and utilized for lineage tracing. Prime editing allows for precise genome editing by inserting user-specified genetic sequences at a target site in the genome. I hypothesize that we can use prime editing to insert a huge library of user-specified barcodes into the genome of developing zebrafish. Because these barcodes are defined by the experimenter, they can be recovered at the end of the experiment using RNA in situ hybridization. In principle, lineage tracing with prime editing will allow us to discover the spatial arrangement of related cells in intact embryos and tissues. We hope to use lineage tracing with prime editing to understand the mechanisms of heart regeneration in zebrafish.


13 Posterior Lower Extremity
Learning Objectives:
By the end of this lab, students will be able to:
- Identify the muscles of the gluteal region, posterior thigh, superficial and deep posterior compartments of the leg, plantar layers of the foot, and name their actions.
- Using the muscle charts as a guide, identify the action, origin, insertion, and innervation for the muscles of the gluteal region, posterior thigh, superficial and deep posterior compartments of the leg, and plantar layers of the foot.
- Describe how structure governs function and provide examples based on muscle orientation and actions.
- Identify the sacroiliac joint, pubic symphysis, and hip joints, including ligaments and capsules.
Terms to Know
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Muscles of the Lower Extremity
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Intrinsic muscles of the foot
Joints of the Lower Extremity Part I
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Introduction
Today you will explore the muscles of the gluteal region, posterior thigh, posterior leg, and plantar layers of the foot. You will use videos from the digital atlas, lower extremity dissections, and image slideshows to explore the muscles of the gluteal region, posterior thigh, and plantar layers of the foot.
Here are a few important tips before learning about these muscles:
- You should know the origins, insertions, actions, and innervations presented in the muscle charts for these and all muscles of the lower extremity. The muscle chart is color-coded, and the information about what we expect you to know from the muscle table is described in the chart document itself. Please read that information. We will ask you questions about the function, attachment site, and/or innervation of muscles on the exam.
- As you are studying, I recommend using landmarks to understand the attachment sites, action, and sometimes the innervation. Follow the muscle to its attachment site if it is visible. Notice the joint the muscle crosses and the side of the joint it is on, and that will give you information about the muscle’s action. In some cases, you can see the nerve go to or even through the muscle it innervates. These visual cues can help you remember the information from the muscle tables.
Lab Activities
Activity 1: Gluteal Region and posterior thigh
- Explore the Sacroiliac joint and pubic symphysis: The sacroiliac joint is the joint between the sacrum and ilium. It is a highly-stable joint capable of only a small amount of gliding movement. This is where the lower extremity meets the spinal column. The pubic symphysis is located between the right and left pubic bones. There is a thick fibrocartilaginous disc between the two pelvic bones at this location.
- Explore the Coxal (hip) joint: First, observe the iliofemoral, ischiofemoral, and pubofemoral ligaments. Be sure to notice which bone of the pelvis they are attaching to, as this will tell you which ligament you are viewing. These ligaments all contribute to the capsule of the hip joint. Also, observe the ligamentum teres, or ligament to the head of the femur. This ligament contains the artery to the head of the femur. The acetabulum is the “socket” of the “ball-and-socket” joint. It is made up of all three bones of the os coxae.
- Explore muscles of the gluteal region: In the gluteal region, first, observe the gluteus maximus. This is the largest and most superficial of the gluteal muscles. Just deep to this is the gluteus medius. The gluteus minimus is the deepest and smallest of the gluteal muscles. The piriformis is an important lateral rotator of the hip. There are 5 other small lateral rotator muscles of the hip. While they are listed in the muscle chart, you will not be asked to identify these muscles in class.
- Explore the muscles of the posterior thigh. The posterior thigh muscles are collectively called the hamstring muscles. The hamstring muscles originate on the ischial tuberosity. Two muscles travel to the medial aspect of the knee. The semimembranosus has a thicker muscle belly and a shorter tendon. The semitendinosus has a thinner muscle belly and a longer tendon. It sits just superficial to the semimembranosus. The biceps femoris has two heads. The long head of biceps femoris originates on the ischial tuberosity, but the short head of biceps femoris originates on the femur. The two heads merge into a common tendon and insert onto the fibular head.
Activity 2: Posterior Leg
The leg can be divided into four compartments. The compartments are separated by a thick, fibrous layer of tissue. Each compartment has an associated nerve, artery, and muscles.
- Superficial posterior compartment of the leg: The most superficial posterior leg muscle is the gastrocnemius. It has a medial and lateral head that cross the knee to insert on the femur. This muscle aids knee flexion and is the primary plantarflexor of the foot. The soleus sits deep to the gastrocnemius and originates on the tibia. The gastrocnemius and soleus tendons merge to form the calcaneal (Achilles) tendon. The plantaris is a small muscle with a tiny muscle belly deep to the gastrocnemius and a long, thin tendon that extends toward the calcaneus. This muscle is not present in all individuals.
- Deep posterior compartment of the leg: There are four muscles of the deep posterior compartment of the leg. The tibialis posterior runs along the posterior aspect of the tibia and acts to plantarflex and invert the foot. Flexor digitorum longus tendons extend to digits 2-5 and flexes these digits. Flexor hallucis longus originates on the posterior fibula, and it’s tendon wraps around the medial aspect of the ankle before it reaches the distal great toe. This long path gives the muscle a mechanical advantage and makes it a powerful flexor of the first digit. The muscles Tibialis posterior, flexor Digitorum longus, and flexor Hallucis longus usually travel in a specific order around the medial malleolus. You can remember the order of these tendons using the mnemonic Tom, Dick, an Harry; “an” stands for posterior tibial Artery and tibial Nerve. Tibialis posterior is most anterior/superior, and flexor hallucis is most posterior/inferior.
The last muscle of the posterior compartment of the leg is the popliteus. This muscle is difficult to see on the tissue, but you can see part of it on the deep dissections. It sits on the superior aspect of the tibia and crosses the knee joint. It functions to medially rotate the tibia and “unlock” the knee from full extension in the first few degrees of flexion.
activity 3: Plantar layers of the foot
Explore the muscles of the foot.
- Intrinsic muscles of the foot: The intrinsic muscles of the foot are muscles that act on the foot and are entirely located within the foot. The muscles that we just examined in the leg would be considered extrinsic muscles of the foot. The plantar aspect can be divided into four layers containing a total of ten muscles or categories of muscles. The layers are just a way to organize the information. We will not ask you to identify which muscle is in which layer.
- Plantar fascia: This thick layer of fascia is superficial to the muscles of the plantar aspect of the foot. It has been cut in both wet specimens, but you can observe how it would attach to the calcaneus in anatomical position. This fascia can become inflamed with plantar fasciitis.
- Plantar muscles layer 1: The flexor digitorum brevis muscle is deep to the plantar fascia and flexes digits 2-4. The abductor hallucis is the large muscle on the medial aspect of the great toe. It abducts the great toe. Likewise, the abductor digiti minimi is located on the lateral aspect of the 5th digit and abducts that digit.
- Plantar muscles layer 2: The muscles of this layer attach to the tendon of flexor digitorum longus. Quadratus plantae runs from the calcaneus to the tendons of flexor digitorum longus to adjust the angle of pull of these tendons. Because the flexor digitorum longus runs around the medial malleolus, without the adjustment from quadratus plantae, this muscle would cause the toes to flex in a medial direction. The quadratus plantae aligns these tendons so that the toes flex within the sagittal plane. The lumbricals of the foot are similar to those of the hand. They insert on to the flexor digitorum longus tendons distally and flex the MP and extend the PIP and DIP joints.
- Plantar muscles Layer 3: The adductor hallucis is similar to the adductor pollicis of the hand. It is “7” shaped, with transverse and oblique heads, and it adducts the great toe. The flexor hallucis brevis and flexor digiti minimi muscles flex the great toe and 5th digit, respectively. These muscles can be observed on the deep dissection.
- Plantar muscles layer 4: The deepest layer of muscles on the plantar aspect of the foot is composed of the dorsal and plantar interossei. Like the hand, the Dorsal interossei Abduct the toes, while the Plantar interossei Adduct the toes (DAB and PAD). However, be sure not to mix up the name of these muscles with those of the hand! In the foot, the interossei that adduct are called the plantar interossei, while in the hand, they are the palmar interossei. These muscles cannot be seen on the dissected tissue, but they can be observed in other images.
Wrap up and clinical connection
For today’s clinical connection, you will see two videos discussing injuries to muscles of the posterior leg. The first video discusses hamstring injuries, and the second video reviews an injury to the Achilles tendon. Use your understanding of origins, insertions, and innervation to help you answer questions on the slideshow.