The goal of the Collaboratory Fellows Fund is to support innovative curriculum development that meets the data and computational literacy needs of a given discipline, set of disciplines and/or cohort of students at Columbia.
Application Deadline: Wednesday, April 13, 2022
Send Application to: Collaboratory@Columbia.edu
VIDEO: Info Session Recording from Wednesday, March 11, 2022
2022 Info Session Recording
VIDEO: 2021 Past (but still relevant) Info Session (40 minutes)
2022 ADDED REQUIREMENT – Please note our strengthened focus on diversity, inclusion, and anti-racist projects requirements for this year’s proposals (details in this year’s RFP). To help you with your proposals, we offer this rich compilation of race and data science resources collected by Collaboratory Fellow Desmond Patton (Associate Prof. of Social Work and Assoc. Director of Diversity, Equity, and Inclusion at DSI).
How Does it Work?
The program will award grants to pairs of instructors (teams can be larger), one with disciplinary/area expertise and one with data-science/computational expertise, to collaborate on the development and teaching of new material that embeds data or computational science into a more traditional domain. We are also encouraging proposals that suggest the reverse: courses that embed business, policy, cultural, and ethical topics into the context of a data or computer science curriculum.
The new content should use pedagogy, instruction, and delivery methods that are fitting for the specific student cohort. Example curricula offerings might include classes, workshops, studios, labs, out-of-semester offerings, and/or “boot-camps.”
Student cohorts can be undergraduate students, MS and Ph.D. students, or graduate students undergoing professional training. The goal is to create diverse course offerings that are accessible to students at all levels, including those who have no previous data science exposure.
Create curricula aimed at undergraduates
Integrates Genomics and data science
All proposals must provide a statement on how the course will contribute to a more diverse and inclusive class, department, school, and University.
Proposals are welcome from all Schools at Columbia University. Because the goal of the Fellows Fund is to support data literacy and the contextual used of data as an important element of a Columbia University education, it is intended that all developed material be integrated into Columbia’s instructional offerings.
– Cover page with executive summary
– Budget and budget justification
– Proposal (limit 5 pages)
– Letters of support from deans and department chairs (the letters of support must include a commitment by your dean to provide financial resources to continue the course well beyond the life of the grant funding — assuming successful completion of the proposed course’s pilot launch).
– CV for each instructor (limit 2 pages each)
Suggested Proposal Contents include justification for the proposed offering, description of materials to be developed, description of the targeted audience, explanation of how materials will be delivered, outline of each instructor’s role, implementation timeline, and evaluation criteria.
Grantees are required to co-develop and co-teach proposed materials, which must be integrated into Columbia’s instructional offerings within 2 years of the receipt of funding support. Grantees are also required to attend cohort gatherings about twice a semester to share lessons learned and best practices. Granted funds must be expended within 3 years.
Who Is This For?
Applications must be submitted by a pair of instructors (or more if justification is provided), each of whom must have the authority to assume scholarly, administrative, and financial responsibility for their individual award. Those eligible to apply are: full-time officers of instruction, professors of practice, lecturers within discipline and/or adjunct professors of Columbia University. At least one member of the instructional team must be appointed full-time. All full-time members on the team must hold primary appointments at Columbia University.