Syllabus review
Task
Choose a syllabus (or two!) to examine. Read through the syllabus, making a note of anything that stands out to you, any questions you have.
How did the instructor balance data literacy content, technical details, and disciplinary content? Is this balance the same as you want to achieve, or different?
Are there objectives in the course that align with the data literacy competencies from the Tulane libguide? Those were:
Databases and Data Formats
Discovery and Acquisition of Data
Data Management and Organization
Data Conversion and Interoperability
Quality Assurance
Metadata
Data Curation and Reuse
Data Preservation
Data Analytics
Data Visualization
Ethics
Are there elements of the course you could/should emulate? For example
Policies
Order of topics
Pacing of material
Number of assignments, mixture of high- and low-stakes assignments
Readings– number of readings, mixture of academic and popular audience work, specific reading assignments
Not all syllabi include details of assignments. If the one(s) you are examining do, consider whether there elements of those you could/should emulate.
Syllabi to review
Here are a few suggested sample syllabi to examine, from least to most technical (“do humanities students need to know how to code?”):
PSYCG1514: Research Methods and Design (PDF download). Kate Jansen, Midwestern University. (no code)
DH285: Introduction to Digital Humanities. Kristen Mapes, Michigan State University. (no code: Flourish, Ondo)
DGHM150: Archaeology in a Digital Age. Leigh Anne Lieberman, Claremont McKenna. (no code?)
DH201: Introduction to Digital Humanities. Miriam Posner, UCLA. (low code, has a little HTML/CSS/p5.js exploration)
ENG790: Quantitative Literary Analysis: Theory and Practice. Lauren Klein and Ben Miller, Emory University. (limited programming but does use Python)
IS312: Reading and Writing Data. Ryan Cordell, University of Illinois Urbana-Champaign. (R or Python programming)
BUS607: Data-Driven Decision-Making. Saylor Academy. (limited programming in R)
STAT336: Data Communication and Visualization. Amelia McNamara, University of St Thomas. (programming in R)
LING334: Introduction to Computational Linguistics. Rob Voigt, Northwestern University. (programming in Python)
If none of those speak to you, here are a few more places to look for syllabi:
The Society for the Teaching of Psychology Project Syllabus collection.
Humanities Commons CORE (narrow search to “Syllabus”)
Saylor Academy (lots of business classes) I don’t know anything about this site, but it seems relatively legit.
You can also feel free to pull examples from your own syllabi! We have a wealth of knowledge in this room, let’s leverage it.