The College of Liberal Arts and Sciences invites proposals to develop a standalone, 2000-level introductory course on artificial intelligence suitable for students across all CLAS majors. The course should provide a foundation for understanding AI and using it critically, ethically, and responsibly, while preparing interested students for more advanced AI-related coursework.
This call builds on the recommendation of the CLAS AI Curriculum Committee to provide students with a foundation for understanding AI and using it critically, ethically, and responsibly.
Who Should Apply: Individual CLAS faculty members or faculty teams across disciplines and campuses.
Deadline: Wednesday, Nov. 25, 2026
Purpose
As AI becomes part of students’ daily lives and future work, students need to understand both its practical uses and the concepts underlying its operation. The proposed course should help students recognize what AI can and cannot do, why it succeeds or fails, and how to validate the information it produces. It should connect this understanding to responsible use, academic integrity, and the risks of relying on AI without critical evaluation.
Who Can Apply
Proposals are welcome from individual CLAS faculty members or faculty teams across disciplines and campuses. Faculty already considering or developing a similar course are encouraged to apply, as are those interested in combining expertise to design and deliver a new course.
Course Expectations
The proposed course should:
- Be a standalone, full-semester course at the 2000 level, suitable for students in all CLAS majors.
- Be accessible to students with diverse academic backgrounds, including those with limited prior experience or interest in science or computing.
- Use accessible materials, ideally including science blogs and videos that engage students from a wide range of backgrounds.
- Provide a foundation for subsequent AI-related courses while offering a complete introduction for students who do not pursue further study in AI.
Minimum Learning Objectives
At a minimum, the course should enable students to:
- Explain major historical developments in AI and their conceptual underpinnings.
- Explain the capabilities and limitations of AI.
- Teach methods for assessing the quality and reliability of AI-generated information.
- Provide analyses of ethical, social and economic issues surrounding AI use.
- Provide opportunities to apply AI tools responsibly in service of education and learning.
Proposal Requirements
Proposals should follow the format required for a new course proposal in the CourseLeaf CIM system and clearly describe:
- The proposed course title, description, level, and intended student audience.
- The course rationale and its relevance to students across CLAS majors.
- Learning objectives that address the minimum objectives outlined above.
- Definition of success of the course in terms of enrollment numbers and distribution of students.
- The course structure and topics, including lectures, weekly homework, and practical exercises.
- Proposed instructional materials and methods for making the course accessible to students from varied backgrounds.
- Support requested, if any, for course development.
Reporting
Award recipients must submit:
- Preliminary report: June 30, 2028.
- Final report: June 30, 2029.
Submit Your Proposal
Proposals are due Wednesday, Nov. 25, 2026, through the CLAS proposal submission portal.