AI@Conn Course Development Stipends is sponsored by Connecticut College (AI@Conn). Supports faculty in redesigning courses to address AI, focusing on critical analysis of AI's societal impact, integrating AI tools, or structured dialogue about AI's role in their discipline.

Your Course, Your Terms: How AI@Conn Funding Supports Your Specific AI Position – Engage You’ve attended the workshops. You’ve been thinking about AI and your teaching. Maybe you’re experimenting with tools like Gemini or BoodleBox, exploring how AI might enhance student learning.

Maybe you’re reading about AI’s implications for your field (e.g., labor displacement, algorithmic bias, environmental costs) and want students to grapple with these questions. Or maybe you’re somewhere in between, interested in both the possibilities and the problems AI presents. Now you’re wondering: should I redesign my course to address AI?

The answer depends less on your technical expertise and more on what questions you think your students need to explore. Whether through hands-on tool use, critical analysis of AI’s societal impact, or structured dialogue about AI’s role in your discipline, the AI@Conn Course Development Stipends can help support the work you are already doing.

What the Course Development Stipends Actually Support AI@Conn’s course development program isn’t asking you to become a computer scientist. It’s asking you to bring your disciplinary expertise to a technology that desperately needs it.

The program offers three tiers of support , each designed for different levels of course transformation: Tier 1: Adding a Unit or Activities – You have a course that works well but could benefit from exploring AI-related challenges or integrating AI tools into one unit. Maybe you want students to critically examine AI-generated content in your field, or use AI tools for a specific assignment.

Tier 2: Substantial Course Modifications – You’re ready to rethink major components of an existing course. This might mean redesigning assignments to leverage AI tools, restructuring assessments to account for AI capabilities, or adding significant AI literacy components throughout the semester.

Tier 3: Creating Entirely New Courses – You see an opportunity to develop a course specifically focused on AI topics or applications in your discipline. This is for faculty who want to explore questions that don’t fit into existing course structures. The beauty of this structure?

It meets you where you are. Whether you’re dipping your toe in the water or diving deep, there’s funding to support your work. The Real Question: Why Should You Apply?

Let me answer this with four stories from colleagues who already have. “I Needed to Solve a Specific Teaching Problem” Marc Zimmer in Chemistry faced a challenge familiar to anyone teaching large-enrollment courses: how do you provide individualized support to 100+ students learning complex material? His Tier 3 proposal developed custom GPT tutors for CHM 103 -104: General Chemistry.

Not because AI was trendy, but because it solved a real pedagogical problem. Students now have access to 24/7 tutoring that’s patient, never judgmental, and always available for another explanation of molecular orbital theory. Further, Zimmer has surveyed students about their use of the AI tutor and its impact on their learning as a means to continually improve his methods.

The key insight? Zimmer started with the teaching problem, not the technology. AI was the solution he discovered, not the goal he imposed.

“I Wanted to Explore Disciplinary Questions AI Makes Urgent” Timothy Becker in Computer Science secured Tier 2 funding to incorporate environmental analysis of AI into an existing course. His question wasn’t “how do we use AI? ” but rather “what does my discipline need to reckon with now that AI exists?

” For Computer Science, that means confronting the energy consumption, carbon footprint, and resource extraction required to train and run large language models. A key component for student learning was “our students will be in the position to consider the ethics of training a chatGPT versus how much energy was used. At what point in energy draw is it worth it to have a openAI tutor?

For example if you know that the tutor uses 1KW per student what will openAI or our institution do to offset that energy and carbon? ” For your discipline, it might mean examining how AI changes professional practices, raises ethical questions, or challenges fundamental assumptions. AI@Conn funding supports this kind of critical inquiry.

You’re not required to be a cheerleader for the technology. Instead you can be its most thoughtful critic. “I Saw an Opportunity to Prepare Students for an Uncertain Future” David Chavanne in Economics developed a Tier 3 course tackling a question few faculty have articulated so directly: how do we prepare students for an economy that doesn’t exist yet?

“It seems obvious to me that we should immediately start doing some rigorous thinking with respect to how this technology will change the world and, by extension, all of our lives,” he wrote in his proposal.

ECO 445: AI and the Economy doesn’t just teach students about AI; it teaches them to analyze markets as they’re becoming, to design research studying public opinion about AI adoption, and to navigate economic uncertainty with analytical rigor. The course structure itself is adaptive, adjusting dynamically based on what emerges in the rapidly evolving AI landscape. This isn’t about integrating a tool into existing pedagogy.

It’s about fundamentally rethinking what economics education should accomplish when students are graduating into an AI-shaped labor market. The funding allowed Chavanne to build a course that embraces uncertainty while maintaining academic rigor, ultimately preparing students not just to enter that economy, but to shape it.

“I Wanted to Deepen Learning Through Strategic AI Integration” Luz Nick in Hispanic Studies co-teaches SPA 200 Intermediate Spanish with Professor Jessica Koehler, which Nick describes as “a mastery-oriented review of selected Spanish grammar topics, with a primary emphasis on developing functional listening, speaking, reading, and writing skills. ” But Nick saw an opportunity to go beyond traditional language instruction.

With course development support, she integrated AI into the course to “deepen grammatical proficiency and develop critical digital literacy. ” The centerpiece? Five custom bots in BoodleBox that scaffold the learning experience.

Students don’t just practice Spanish—they “learn to use generative AI ethically and effectively for language production, iterative practice, and critical analysis of language production in Spanish. ” They analyze AI-generated content alongside traditional media, developing the critical eye to evaluate AI outputs while leveraging AI tools for practice.

This exemplifies what the stipend program really offers: permission and resources to experiment thoughtfully with pedagogical innovation . Nick reimagined how students develop language proficiency in a world where AI translation and language assistance are ubiquitous. Beyond the Stipend: What Else You Get The financial support is tangible, but the intangible benefits may matter more: Individualized Consultation – The Harold F.

Wiley Generative AI Fellow and members of the AI@Conn Advisory Committee are available to consult on implementation of the proposed activities. When you apply, you’re getting a thought partner. Professional Development – The AI@Conn initiative provides several awareness and application workshops to help aid faculty in the development of integrated conversations and/or activities in courses.

Recognition and Visibility – Your work gets showcased in an annual Faculty AI Showcase, on the AI@Conn website, and through other public means. This positions you as a thought leader in your discipline. What Makes This Different from Other Teaching Grants?

Most course development grants ask you to improve teaching within existing paradigms. AI@Conn asks you to question the paradigms themselves . Should we still assign five-page essays when AI can generate competent ones in seconds?

How do we assess learning when students have access to tools that can solve problems we once used to measure understanding? What does it mean to teach critical thinking when machines can generate seemingly thoughtful analysis? These aren’t technical questions—they’re philosophical, pedagogical, and disciplinary questions.

And they’re exactly the kind of inquiry that faculty in the liberal arts are trained to pursue. The stipend program provides resources to explore these questions seriously, in the context of your actual teaching practice, with support from colleagues doing similar work. Addressing the Hesitations Let’s be honest about the concerns you might have: “I’m not technical enough.

” Good. We need humanists, social scientists, and artists shaping how AI gets used in a liberal arts education. The most important questions about AI aren’t technical—they’re ethical, social, and cultural.

Your disciplinary expertise matters more than your coding skills. “I’m worried about academic integrity. ” So is everyone else.

That’s precisely why we need thoughtful course redesign. The stipend program supports you in developing assignments that are meaningful even in an AI-saturated world. You’re not alone in figuring this out.

“What if my experiment fails? ” Then you’ll have learned something valuable, and you’ll share that learning with colleagues so we all benefit. The initiative expects experimentation, which means some experiments won’t work as planned.

That’s not failure, that’s research. “I don’t have time. ” This is the real concern, and it’s legitimate.

But consider: you’re already spending time thinking about AI’s impact on your teaching. The stipend provides resources to channel that thinking into concrete course improvements rather than abstract worry.

The Application Process Made Simple Faculty interested in applying should submit a detailed proposal that includes: A description of the proposed course or modifications to an existing course A detailed explanation of the type and extent of AI content to be integrated, including how it will be incorporated into assignments, lectures, or projects Note: provide evidence to support statements of need of discourse or application The anticipated impact on student learning and engagement A timeline for course development and implementation Any plans for collaboration with other faculty or departments NOTE: Individuals who have received funding through Course Development stipends are ineligible to apply for this round of funding.

Timeline Call for Proposals Released: February 2, 2026 Proposal Submission Deadline: March 23, 2026 Committee Review Period: March 24-April 3, 2026 Award Notifications: April 6, 2026 Course Development Period: May 2026 – December 2026* Final Report Submission: December 18, 2026**Tier 3 course development stipends will have an adjusted development period and final report submission date to align with IFF procedures.

Course development funding isn’t about forcing AI into your teaching. It’s about supporting you in determining whether and how AI might enhance what you’re already trying to accomplish. Maybe you’re frustrated with assessment methods that no longer measure what they claim to measure.

Maybe you see opportunities to provide students with practice they wouldn’t otherwise get. Maybe you want to teach the critical analysis skills students will need in an AI-saturated world. Maybe you’re worried about equity and want to ensure all students can benefit from these tools.

Whatever your motivation, the AI@Conn course development program provides resources, community, and institutional support to help you explore it seriously. Contact Susan Purrington, Harold F. Wiley Generative AI Teaching and Learning Fellow, at spurringt@conncoll.

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