[Associated Colleges of the Midwest (ACM)](https://acm.edu)

Closed (2015–2016 cycle)

$9,300 per award; one-year project cycle typical

Supports collaborative development of interdisciplinary, adaptable undergraduate data science course materials aligned with ASA 2014 Guidelines.

Only ACM member institution faculty/teams eligible.

--- ## Description This opportunity supports the development of collaborative, interdisciplinary course materials in data science, specifically targeting undergraduate statistics education at liberal arts colleges. The goal is to bridge the gap between current statistics curricula and the demands of a data-driven society by creating case studies and activities rooted in real-world data and research questions from multiple disciplines. These materials emphasize modern data analysis techniques, ethical considerations, and advanced data visualization, and are designed to be accessible online and easily integrated into existing courses. The project promotes hands-on experience with complex, messy datasets and fosters the communication of statistical concepts to diverse audiences, supporting the adoption of new pedagogical models across ACM institutions. --- ## Due Dates - Closed (2015–2016 funding cycle) - No current or upcoming application deadlines are announced. --- ## Funding Amount - Typical award: $9,300 per project - Funding is generally for a one-year cycle. - The number of awards is limited and based on available program funding. --- ## Eligibility - Applicants must be faculty or teams from institutions that are members of the [Associated Colleges of the Midwest (ACM)](https://acm.edu/about/). - Projects must focus on undergraduate, interdisciplinary data science education. - Proposals should align with the [2014 ASA Guidelines for Undergraduate Programs in Statistical Science](http://www.amstat.org/education/curriculumguidelines.cfm). - Materials must be adaptable and accessible for use across multiple ACM colleges. --- ## Application Process - Proposals typically require: - Project narrative describing objectives, activities, and alignment with ACM and ASA guidelines - Timeline and dissemination plan - Budget and justification - Team member CVs and institutional support letters - Submission is normally through the ACM’s program or project submission portal. - For future cycles, monitor the [ACM program funding page](https://acm.edu/program_fund/face/) for updates. --- ## Additional Information - Funded projects are expected to: - Develop 6–9 case studies for use in introductory and advanced statistics/data science courses - Incorporate ethical, societal, and technical aspects of data science - Be tested and revised based on classroom feedback - Disseminate materials publicly, such as via the [Stat2Labs website](http://web.grinnell.edu/individuals/kuipers/stat2labs/index.html) and conference presentations - Prior projects have involved collaborative teams from Grinnell College, Carleton College, and Lawrence University. --- ## External Links - [ACM Project Page](https://acm.edu/project/54) - [Stat2Labs Project-Based Materials](http://web.grinnell.edu/individuals/kuipers/stat2labs/index.html) - [2014 ASA Guidelines for Undergraduate Programs in Statistical Science](http://www.amstat.org/education/curriculumguidelines.cfm) - [ACM FaCE Program Funding](https://acm.edu/program_fund/face/) --- ## Contact Information | Name | Institution | Email | |---------------------|--------------------|---------------------------------------| | Shonda Kuiper | Grinnell College | [kuipers@grinnell.edu](mailto:kuipers@grinnell.edu) | | Adam Loy | Lawrence University| [adam.m.loy@lawrence.edu](mailto:adam.m.loy@lawrence.edu) | | Laura Chihara | Carleton College | [lchihara@carleton.edu](mailto:lchihara@carleton.edu) | | ACM General Contact | ACM | [ACM Contact Page](https://acm.edu/contact-us/) | | ACM Phone | ACM | +1 (312) 263-5000 |

Planning for Collaborative Courses in Data Science

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