Quick Win Research Grants
The Office of Academic Innovation invites University of Michigan (U-M) faculty and students to apply for a “Quick Win” research grant to support small-scale projects on special topics in the areas of higher education and academic innovation. Proposals should consider how the focus of the work aligns with Academic Innovation (AI) initiatives and key priorities, and discuss how outcomes will complement ongoing work at AI.
Excellent proposals will: describe how the proposed research project fits the call topic, include clear research questions, outline the data sources and methodologies to be used, and highlight how this work can impact teaching and learning. With the goal of growing the academic innovation community, applications from those who have not yet collaborated with AI will be prioritized for support.
Proposals will be reviewed three times a year, on January 15, June 15, and September 15. Typically funding is capped at $5000. Requests for larger amounts of support should consider applying to our Academic Innovation Fund.
We have organized the call into three tracks, and we encourage you to consider which one might be best suited to the idea or topic you want to pursue through the grant:
- Diversity, equity, and inclusion in learning environments
- Supporting communities in informal and/or formal learning environments
- Hybrid learning
The call is organized by theme to support resource sharing among grantees and to allow for thematic presentations of research outcomes. These are the three tracks for the 2018-2019 round, but we look forward to considering new tracks in the future and welcome suggestions.
Please review the application form and submit it by one of the three deadlines. Notices regarding status will be sent out no more than four weeks after the proposal deadline.
For more information please contact Caitlin Holman (email@example.com)
What are examples of types of projects that would be well-suited for a “Quick Win” grant?
- Pilot studies of implementing new technology or pedagogy in the classroom
- Experiments or approaches you’ve tried out in your classroom, but have not yet had a chance to study
- Secondary analysis of an educational dataset
What can this funding be used for?
- Paying hourly wages for students/contractors
- Transcription services
- Software fees
- Open access fees
- Stock photography
Conference attendance/travel is not supported at this time. Please ask if you have questions regarding what this money can be used for.
Can this funding be tied to other grants?
Yes! In that instance, please make sure to highlight what about this funding request makes it fit as a Quick Win grant. For instance, is it new work that is coming out of previously-funded work? Is this grant intended to kick off work and then lead to additional funding? We’d love to support that kind of work.
What do I need to produce as a report on this work?
We would like to receive a final version of any publications or presentations you produce via this funding. We also understand that while many of the things explored with this funding may not be quite ready for publication, we would very much like to learn from the work you have done. With that goal in mind, we ask that all projects share a 3-4 page summary of work, describing what work was done, what was discovered, what you see as next steps for this work, and any challenges faced to enable us to support others better in doing this work. Ideally this document would be shared with AI within 2 months following the conclusion of the work, but no later than one year after the grant award.
In addition, we invite you to contribute to knowledge sharing and institutional learning in one or more of the following ways:
- Give an Academic Innovation at Michigan Analytics presentation (public talk to the U-M community)
- Promote the work with a blog post on the AI blog describing the work done and initial findings
- Come discuss your work with AI staff over a Research Brown Bag meeting (casual lunch talk)
- Join the staff of AI for an “Innovation Hour” (internal to AI talk, potential to be more casual or more formal)
We’d love to brainstorm other ways for you to share your work back with us – and are happy to customize as appropriate for the work.