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

Closed (Last cycle: 2015–2016)

$9,300 total award; one-time funding for project-based curriculum development

Supports development of collaborative, interdisciplinary undergraduate data science course materials that emphasize real-world analytical skills.

--- ## Description This grant from the Associated Colleges of the Midwest (ACM) supports the planning and creation of interdisciplinary, collaborative course materials in data science for undergraduate education. The initiative aims to bridge the gap between traditional statistics curricula and the practical demands of modern data analysis, emphasizing hands-on experience with complex, messy, and large datasets. The project specifically targets the development of adaptable case studies and resources that integrate ethical considerations, programming, problem-solving, and communication skills. Materials are intended to be widely disseminated and easily incorporated into a variety of existing courses, with the goal of equipping students across disciplines with essential data-based decision-making abilities. --- ## Due Dates - Closed (Last funding cycle: 2015–2016) *Note: This grant appears to have been a one-time funding opportunity. Researchers should check the [ACM grants page](https://acm.edu/projects/) for any new or recurring opportunities.* --- ## Funding Amount - Award: $9,300 total for the project - Funding was provided as a one-time grant for the development, testing, and dissemination of curricular materials over approximately one academic year (2015–2016). --- ## Eligibility - Intended for faculty at ACM member institutions (14 private liberal arts colleges in the Midwest: Colorado, Illinois, Iowa, Minnesota, Wisconsin). - Collaborative, cross-institutional teams from mathematics, statistics, computer science, and related disciplines are encouraged. - Projects must focus on undergraduate education and be adaptable to multiple institutions and course formats. --- ## Application Process - Application was through ACM’s Faculty Career Enhancement (FaCE) program. - Proposals needed to outline project goals, timeline, deliverables (such as case studies), and dissemination strategies. - Required collaboration across disciplines and/or institutions. - Review focused on alignment with 2014 ASA Guidelines and the ability to create adaptable, impactful curricular materials. --- ## Additional Information - Projects were expected to address the 2014 ASA Guidelines for Undergraduate Programs in Statistical Science, emphasizing: - Programming and database skills (e.g., R, Python) - Working with real, messy, or big data - Ethical and societal considerations - Communication and visualization of statistical results - Deliverables included 6–9 case studies, online instructor resources, and presentations/publications for dissemination. - Materials were tested in classes at Grinnell, Carleton, and Lawrence and made publicly available via the [Stat2Labs website](http://web.grinnell.edu/individuals/kuipers/stat2labs/index.html). --- ## External Links - [Project page at ACM](https://acm.edu/project/54) - [Stat2Labs: Project-based curricular materials](http://web.grinnell.edu/individuals/kuipers/stat2labs/index.html) - [2014 ASA Curriculum Guidelines](http://www.amstat.org/education/curriculumguidelines.cfm) - [ACM FaCE Program](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 Univ. | [adam.m.loy@lawrence.edu](mailto:adam.m.loy@lawrence.edu) | | Laura Chihara | Carleton College| [lchihara@carleton.edu](mailto:lchihara@carleton.edu) | | ACM General Info | ACM | [Contact ACM](https://acm.edu/contact-us/) | | ACM Phone | ACM | +1 (312) 263-5000 |

Planning for Collaborative Courses in Data Science

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