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

Closed (2015–2016 cycle)

$9,300 total; one-year project

Supports creation of interdisciplinary, project-based data science curricular materials and case studies for undergraduate education.

--- ## Description This opportunity supported the development of collaborative, interdisciplinary curricular resources in data science for undergraduate courses. The focus was on designing six to nine adaptable case studies that bridge the gap between textbook exercises and real-world data challenges, as recommended by the 2014 American Statistical Association (ASA) Guidelines for Undergraduate Programs in Statistical Science. The materials aimed to teach students essential skills in programming, data manipulation, algorithmic problem-solving, ethical considerations, and effective communication of statistical concepts. The project emphasized collaboration across institutions and disciplines, with the goal of making these resources widely accessible online and easy for instructors to integrate into a variety of statistics and data science courses. Dissemination included public posting on the [Stat2Labs website](http://web.grinnell.edu/individuals/kuipers/stat2labs/index.html), presentations at major conferences, and potential publication in educational journals. --- ## Due Dates - Closed (2015–2016 cycle) --- ## Funding Amount - Total award: $9,300 - Funding was provided for a one-year project cycle. --- ## Eligibility - Faculty at ACM member institutions, especially those involved in statistics, mathematics, or computer science. - Preference for collaborative, cross-institutional, and interdisciplinary teams. - Projects needed to address undergraduate education and align with ASA curriculum guidelines. --- ## Application Process - Applications were submitted through the ACM [FaCE (Faculty Career Enhancement) Program](https://acm.edu/program_fund/face/). - Proposals required a project description, timeline, budget, and dissemination plan. - Emphasis was placed on collaboration, adaptability, and the potential for broad impact. --- ## Additional Information - The developed materials are publicly available via the [Stat2Labs project-based statistics materials site](http://web.grinnell.edu/individuals/kuipers/stat2labs/index.html). - The project encouraged instructor feedback and iterative refinement, with class testing at multiple institutions. - Although this specific funding cycle is closed, similar ACM or FaCE program opportunities may arise in the future. --- ## External Links - [Associated Colleges of the Midwest (ACM) Project Page](https://acm.edu/project/54) - [Stat2Labs Project-Based Statistics Materials](http://web.grinnell.edu/individuals/kuipers/stat2labs/index.html) - [R Tutorials in Data Science](http://web.grinnell.edu/individuals/kuipers/stat2labs/RTutorials.html) - [ACM FaCE Program](https://acm.edu/program_fund/face/) - [ASA Curriculum Guidelines for Undergraduate Programs in Statistical Science](http://www.amstat.org/education/curriculumguidelines.cfm) --- ## Contact Information | Name | Institution | Department | Email | |------------------|--------------------|---------------------------|---------------------------------------| | Shonda Kuiper | Grinnell College | Mathematics & Statistics | [kuipers@grinnell.edu](mailto:kuipers@grinnell.edu) | | Adam Loy | Lawrence University| Statistics | [adam.m.loy@lawrence.edu](mailto:adam.m.loy@lawrence.edu) | | Laura Chihara | Carleton College | Mathematics & Statistics | [lchihara@carleton.edu](mailto:lchihara@carleton.edu) | | ACM Main Office | ACM Consortium | - | [Contact Form](https://acm.edu/contact-us/)
+1 (312) 263-5000 |

Planning for Collaborative Courses in Data Science

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