AI Literacy Course Redesign Stipend
AI Literacy Course Redesign – Faculty Expectations
Faculty participating in the AI literacy course redesign are expected to meaningfully integrate AI literacy into their course design in ways that support student learning, transparency, and ethical use. Faculty completing the training, redesigning the course following the expectations listed below, and offering the revised course to students will receive a stipend. This document outlines shared expectations to guide course redesign efforts. It is not a scoring rubric.
Purpose of These Expectations
These expectations are designed to:
- Clarify what qualifies as a substantive AI literacy course redesign
- Support academic freedom while establishing shared standards
- Help faculty focus on learning design rather than tools
- Ensure redesigned courses are eligible for stipend consideration
1. Meaningful Integration of AI Literacy
AI literacy should be intentionally integrated into the course—not added as a single tool or topic. Students should encounter AI literacy in ways that are connected to disciplinary content, practices, and ways of thinking.
2. Clear AI-Related Learning Outcomes
Courses should include learning outcomes that explicitly address what students should understand or be able to do related to AI. Outcomes may include evaluating AI limitations, applying ethical reasoning, or making informed judgments about AI use within the discipline.
3. Assessment Design That Assumes AI Is Present
At least one major assessment should be designed or revised with the assumption that AI tools are available. Assessments should prioritize thinking, decision-making, process, or authentic application rather than attempting to prevent students from using AI entirely.
4. Transparent Student Expectations for AI Use
Students should receive clear, student-centered guidance about when and how AI may be used in the course. Expectations should emphasize learning, trust, and equity rather than surveillance or punishment. Alternatives to AI-dependent tasks, assignments and/or assessments should be provided.
5. Attention to Student Thinking and Reflection
Courses should include opportunities for students to reflect on their thinking, decision-making, and critical understanding about AI use. This may include reflection prompts, process documentation, or metacognitive activities.
6. Ethical, Inclusive, and Responsible AI Framing
Courses should address ethical considerations relevant to AI use, including accuracy, bias, accessibility, equity, environmental impact, or disciplinary implications where appropriate.
7. Clear Documentation of the Redesign
Faculty should provide clear documentation of redesigned elements (e.g., syllabus sections, assignments, learning activities, or brief design rationale) so the redesign can be reviewed and sustained.
Connection to Stipends
Course redesign stipends recognize the time and expertise involved in substantial instructional redesign. Courses that demonstrate strong alignment with these expectations may be eligible for a $500 or $1,000 stipend, depending on the depth and quality of integration reflected in the submitted materials.
Redesigned courses are expected to be taught within one year of stipend distribution.
Eligibility will be determined with the use of the rubric found in the supporting documentation.
Support & Academic Freedom
These expectations are intentionally flexible and respect disciplinary differences and academic freedom. There is no single required AI tool or teaching method. Multimodal Education Center staff are available to support faculty in designing, documenting, or refining AI literacy integration.
Supporting Documentation and Application:
Multimodal Learning Course Development Grant Application for AI Literacy*
AI Literacy Course Redesign Rubric
*Please note that a letter of support from the faculty's chair will be needed as part of the application process.
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