Becoming "data conversant" is only growing in importance as data-related practice becomes increasingly ingrained in public and academic discourse. Learning data-related skills, like reading, working with, analyzing, and arguing with data, is often viewed as a purely technical process that centers mastery of coding or data analysis software.
Instead, this course will take a justice-centered approach that examines how systems of power affect and are affected by data. Students will gain practical experience through low-tech explorations of real-world data, but we won't shy away from or gloss over data's inherent complexities. And data are complex, just like the people who are responsible for their creation, curation, and use.
To help us navigate these murky waters, and to move past number crunching to deeper critical analysis, we'll be drawing on the expertise of scholars, practitioners, and enthusiasts from an array of disciplines and backgrounds.
There are no prerequisites for this course.
By completing this course, students will have gained:
- Strategies for reading and working with data, as well as experience performing simple data analysis and visualization,
- An understanding of how societal and social factors impact the creation, analysis, and presentation of data,
- Experience leveraging data resources to formulate research inquiries and narratives.
Our guiding text for the course will be:
Data Feminism by Catherine D'Ignazio and Lauren F. Klein
- Free web version: https://data-feminism.mitpress.mit.edu/
- Free PDF version: https://doi.org/10.7551/mitpress/11805.001.0001
- ISBN: 9780262044004 (hardcover); 9780262547185 (paperback)
Note
Additional readings will include book chapters, articles, blog posts, and podcasts. Links to all readings will be provided on the course's Moodle page.
To help explore data in commonly used file formats, it will be useful to have both a spreadsheet app and a text editing app.
MS Excel, OpenOffice or LibreOffice Calc, or Google Sheets
Note
It's not really a spreadsheet app, but OpenRefine is a powerful spreadsheet-like tool that's worth getting familiar with if you work with data regularly.
Windows and Mac OS both have default text editors, Notepad and TextEdit, but I'd recommend something with a bit more power like:
- Windows/Mac: SublimeText
- Mac only: BBEdit
- Windows only: Notepad++
Note
VS Code, which is frequently used by other programs, is a really powerful text editor but its level of functionality might be overwhelming.
This class relies heavily on guided group discussions and/or hands-on activities and explorations, so in-class attendance and participation are essential to the successful completion of the course. The weighting of assignments reflects this, and I expect each student to participate in class discussions and activities. This might not look the same for everyone, and that's okay.
Since this is a smaller class, I hope to evaluate absences on a case-by-case basis. Accommodations will be made for illness, religious observances, and other concerns as outlined in Kenyon's Conduct of Courses, and I can work with you to make up missed in-class activities. Of course, it's much easier to be accommodating if I know what's going on, so please let me know of any anticipated absences as early as possible.
All that being said, this is an 8-week class and 4 or more absences represents a significant portion of the course. Therefore, beginning with your 4th absence, your participation grade will be negatively affected. Also, per college policy, any student missing more than 25% of class meetings (in our case 6 classes) for any reason will not meet the minimal academic standards of a class and will not be eligible to complete the course.
Aside from in-class activities and readings, the primary sequence of assignments for this course culminates in a data-driven presentation exploring a particular dataset in relation to a community or population.
A short paper (2-3 pages) introducing a selected dataset and discussing how it came into existence. It should outline information such as who is responsible for the dataset's creation and its original intended purpose. A good place to start will be with the Five Ws: Who, What, When, Where, and Why. Readings will provide additional guidance.
A short paper (2-3 pages) which presents and discusses a research question inspired by your examination of a selected dataset. This does not need to be the same dataset chosen for the previous assignment. You will be discussing what you saw in the dataset that led to the research question you selected. You should also identify (or speculate on) what additional resources (datasets, books, articles, etc.) that would be required to fully examine the research question.
A short paper (4-5 pages) reflecting on the research process along with a draft slide deck/ script/other draft presentation materials. This assignment should outline the process that you have gone through in the first two assignments and address the steps you would take in order to investigate the question proposed in your Research Inquiry assignment.
As part of your reflection, I am especially interested in your response to the following questions: How did the Data Biography or our in-class activities affect your research question? How might they affect the way you'd plan to investigate that question?
An in-class presentation (5 minutes) along with the final draft of your research reflection (4-5 pages).
The written portion of the above assignments should be formatted as follows:
- 1" margins on all sides
- 11 pt Calibri/Arial/Helvetica (or 12 pt Times New Roman)
- Double spacing
- Document header including name, date, and name of the assignment
Written assignments should be submitted via Moodle as Word documents or PDFs. Aside from the above, I do not require a particular citation or formatting style. Instead, I suggest you follow a style relevant to your future academic or professional plans. If you aren't sure, I can help you figure out what might be appropriate.
- Participation: 35%
- Data biography: 10%
- Research inquiry: 10%
- Draft presentation/reflection: 10%
- Final presentation/reflection: 35%
- Data biography: Friday, September 8
- Research inquiry: Friday, September 22
- Presentation draft/reflection: Monday, October 9
- Final presentations: Wednesday, October 18 & Friday, October 20
| A (93 to 100%) | A– (90 to 92%) | B+ (87 to 89%) |
| B (83 to 86%) | B– (80 to 82%) | C+ (77 to 79%) |
| C (73 to 76%) | C– (70 to 72%) | D+ (67 to 69%) |
| D (63 to 66%) | D– (60 to 62%) | |
| F (59% or below) |
Aside from time spent on assignments and readings, there may be in-class activities and discussions that require some preparatory work. With rare exceptions, these shouldn't require much time or effort, and will be announced at the end of the previous class and listed on the course's Moodle page. Anything more involved will be announced several classes in advance and will be discussed in-class at greater length.
Assignments will be due at the beginning of class. Late assignments will be considered on a case-by-case basis but, without a strong justification for an assignment's lateness, your final grade for the assignment will be marked down by up to 1 point per day late. This is an 8-week class so making sure assignments are in on time is especially important in keeping us on track.
Ground rules for engaging with social justice topics 1
- Controversy with civility – Conflict and disagreement happen when a diverse community discusses social justice topics, but these discussions strengthen rather than weaken the community. As a group, we recognize that our goal is cooperative movement towards shared understanding and common goals.
- Own your intentions and your impact – Both the intention and the impact of what we say and do matters, but positive intentions do not guarantee positive impact. What's more, positive (or neutral) intentions are not "more important than" negative impact.
- Challenge by choice – Each of us determines for ourselves if and to what degree we feel comfortable participating in a given discussion or activity, and that determination will be honored by the rest of the group.
- Respect – We all want to be respected, and to demonstrate respect for others. What constitutes a demonstration of respect may vary, so be thoughtful and communicative about your feelings in this regard.
- No attacks – Personal attacks are an extreme form of disrespect and counterproductive in discussions around social justice. However, there is a difference between an attack and a challenge which causes discomfort.
I am subject to these ground rules just as much as you are, and I hope we will all hold each other accountable to these guidelines. I recognize the inherent power imbalance between myself as instructor and you as students, but I hope that will not dissuade you from letting me know, through some means, if you feel I am failing to follow my own guidelines.
That being said, I am also responsible for maintaining the classroom as an environment in which learning can take place, and so I may need to halt or steer the conversation away from (or towards) a particular topic. If you feel I am over- or under-managing classroom discussions in this way, please let me know.
At Kenyon College we expect all students, at all times, to submit work that represents our highest standards of academic integrity. It is the responsibility of each student to learn and practice the proper ways of documenting and acknowledging those whose ideas and words they have drawn upon (see Academic Integrity and Questions of Plagiarism in the Course Catalog). Ignorance and carelessness are not excuses for academic dishonesty.
Kenyon College values diversity and recognizes disability as an aspect of diversity. Our shared goal is to create learning environments that are accessible, equitable, and inclusive. If you anticipate barriers related to the format, requirements, or assessments of this course, you are encouraged to contact the office of Student Accessibility and Support Services (SASS) and to meet with me to discuss accommodation options or adaptations
We will be studying and/or discussing a number of issues that may cause discomfort or distress. If you wish to speak with me about any readings, assignments, or class discussions, please understand that I may be required to report information about sexual misconduct, discrimination, and discriminatory harassment to the Civil Rights & Title IX Coordinator. Confidential support options include the Cox Health and Counseling Center, the College chaplains, and New Directions Domestic & Sexual Violence Support Center.
We are required to follow the Kenyon College and CDC guidelines with respect to COVID-19 exposure:
- Anyone with known exposure to COVID-19 must wear a mask for 10 days when in public indoor spaces.
- Students who are sick with COVID-19 must notify the Cox Center, who will guide the student through a period of self-isolation and masking.
Footnotes
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Adapted from Arao & Clemens (2013), "From safe spaces to brave spaces," in The Art of Effective Facilitation ↩