Types of Partnerships
At the core of the Digital Integration Teaching Initiative model is an ethos of collaboration: we aim to help CSSH faculty integrate digital proficiencies into the curriculum of their courses. The DITI team will work carefully with you on this integration: we don’t just parachute into a course to teach a discrete unit on a digital skill disconnected from the rest of the course’s contents. The integrative model we support takes time, careful planning, and collaborative work on the part of faculty members and the DITI team.
We offer several types of partnerships between faculty and DITI-trained graduate students to incorporate computational and digital skills into existing course content:
Types of Partnerships
DITI team members will visit the course during one or more days to teach a workshop on digital or computational skills. Workshops can either present new content—created in collaboration with the faculty partner—or be adapted from existing materials. Developing new workshop materials will require additional time. Visit our example materials page to explore some previous workshops.
One or more DITI team members will work one-on-one with the faculty partner to develop an assignment that incorporates digital or computational skills. Usually, this involves adding a digital component to an existing assignment (e.g. mapping, Excel, visualizations, websites), but developing a new assignment is also a possibility. Visit our example materials page to explore some multi-class assignments.
This partnership involves a more in-depth assignment that spans the course semester. This sustained assignment will help students become more proficient with a particular digital or computational skill and apply it to a long-term project. DITI team members will work with the faculty partner throughout the semester. This may also involve guest lectures and workshops run by DITI members and will result in final computationally or digitally enhanced projects by students.
We are also able to accommodate other types of partnerships, with sufficient advance notice. Please note that some partnerships will take longer than others to develop, especially if the content is new. For all partnerships, however, both the class date and type of partnership must be specified before the semester begins.
To ensure that we are able to accommodate all requests, we have established a timeline for DITI partnerships. Partnerships begin early in the semester before the class is offered in order to provide sufficient time to create class materials, reserve times for class visits, and modify materials based on faculty partner feedback. After the initial consultation, DITI team members will remain in touch throughout the planning and teaching processes to ensure the success of digital modules.
When you have completed the CFP intake form, the DITI team will reach out to schedule a planning consultation. We will also send information on how you can reserve a week or weeks for a class visit. We can only successfully do a limited number of class visits per week, and weekly reservations are done on a first-come first-served basis. Note that some weeks are historically more popular than others, particularly during the beginning and middle of the semester, so reserve your slot early if you want our visit to be early in the semester. We will make every effort to accommodate your schedule, but please be advised that we may not be able to schedule you during your desired week(s) if you are unable to meet us with or confirm the timing and logistics of your visit.
- By April 1st: let us know if you are interested in a DITI partnership for the Fall by filling out this brief survey. You do not need to know full details about your course to submit the form.
- By May 15th: an in-person or virtual meeting will be held to collect course details and plan for the partnership. A specific date or course syllabus is not needed at this time, but the initial meeting will serve as the foundation for determining which types of partnerships best suit the class goals, creating a timeline, and clarifying expectations for what can be taught during the given timeframe.
- By November 1st: let us know if you are interested in a DITI partnership for the Spring by filling out this brief survey. You do not need to know full details about your course to submit the form.
- By December 15th: an in-person or virtual meeting will be held to collect course details and plan for the partnership. A specific date or course syllabus is not needed at this time, but the initial meeting will serve as the foundation for determining which types of partnerships best suit the class goals, creating a timeline, and clarifying expectations for what can be taught during the given timeframe.
You do not need any specialized technical knowledge or skills to include a digital module in your course. That’s what the DITI team members are for! Our goal is for instructors to work closely with the DITI team so that in the future they will be able to teach the modules themselves, but DITI team members can remain available for assistance and ongoing planning. To ensure the module is successful and to help you understand what to expect, we have set out a few guidelines. Faculty members should plan to:
- Attend the class during workshop days and guest lectures. This helps faculty partners learn the material themselves, and address any course-specific questions from students as they arise.
- Distribute the appropriate materials, arrange downloads of data/software, and send advance instructions to students so they are well-prepared for the class as needed.
- Reserve time that works best for both the course and the DITI team members’ schedules; without sufficient lead time, DITI team members may not be able to accommodate a specific date.
DITI team members span multiple disciplines and their familiarity with data in disciplines other than their own may be limited. We recommend that faculty partners select useful data for workshops, projects, and presentations during advance planning for the module. Faculty partners should plan to provide or point to datasets that are relevant to the course and to consult with DITI team members on what kinds of data are needed for different assignments or workshops. In some cases, the DITI team may be able to assist with data gathering. If faculty are unable to provide data resources, then DITI team members may be able to supply datasets; however, such data may not always be the most relevant for the course.
The DITI is guided by three principles: open data, analyzable data, and archivable data. If datasets are not arranged in an open, standard, analyzable format, then users of that data might have difficulty accessing it in the short- or long-term. We strive to remove all unnecessary restrictions over the data that we create, use, and share in the classroom and on our GitHub Digital Showcase. If at all possible, we would like faculty to follow these principles when it comes to selecting datasets, though we will do our best to work with files in any form. We prefer faculty send us data that are analyzable and non-proprietary, so we can avoid problems like: major software updates causing datasets to become inaccessible, difficulty with reading files on different operating systems and with different software, or proprietary data types becoming obsolete.
The DITI follows data and file formatting guidelines that allow for long-term storage and wide-range accessibility. If you have any questions about these data considerations, please contact a DITI member.
Below are lists outlining the data file formatting standards we recommend at the DITI:
Data File Formatting
- JPEG 2000
Below are the data values we observe at the DITI and more resources explaining the reasoning behind these guidelines:
Data Values & Resources
- Standardize all coded and null values within a dataset.
- Use an explicit value for missing or no data, rather than an empty field.
- For numeric fields, represent missing data with a specified extreme value (e.g., -9999), the IEEE floating point NaN value (Not a Number), or the database NULL. Be advised that NULL and NaN can cause problems, particularly with some older programs. For character fields, use NULL, “not applicable”, “n/a” or “none”.
- If there are multiple reasons that cells might not contain values, include a separate code for each.
- The null value(s) should be consistently applied within and among data files.
- If data values are encoded, be sure to provide a definition in the metadata. We recommend using UTF-8 when possible.
- Don’t include rows with summary statistics. It is best to put summary statistics, figures, analyses, and other summary content into a separate companion data file.
- “Data and File Formatting,” Axiom Data Science. 2017. https://www.axiomdatascience.com/best-practices/DataandFileFormatting.html
- Tauberer, Joshua. “Analyzable Data in Open Formats (Principles 5 and 7).” Open Government Data: The Book. Second Edition, 2014. https://opengovdata.io/2014/analyzable-data-in-open-formats/
Type of Program
Links and Resources