SPARK
What is SPARK?
SPARK is an intensive program designed to help faculty and staff apply artificial intelligence to their own research, teaching, or administrative work. SPARK is intended to help you build a working AI tool or workflow to solve a real problem from your work.
Participants work alongside colleagues from across disciplines and administrative units, learning both from instructors and from each other.
No programming experience required.
SPARK is open to all CUA faculty and staff. No prior programming experience or technical background is required. You just bring a research project, a course, or an administrative task that you want to improve.
We especially encourage applications from interdisciplinary teams (2 or more members) that cross departments.
Participants are supported throughout the program.
Present your work at the fall AI SPARK Symposium.
Full coverage of AI platform costs during the program (Claude Pro, ChatGPT Plus, or similar tools).
Technical support and coaching throughout the program.
Access to a peer cohort of up to 16 faculty and staff from across CUA's humanities, social sciences, natural sciences, and administrative units.
Five sessions · Tuesdays 3–6 PM · June 2026 · In-person.
Foundations & Data Architecture
Participants map their data ecosystems, write Data Specifications describing what an AI agent should read and produce, construct Logic Maps that define the steps from input to output, and begin thinking about how to evaluate the output of an AI agent for their tool or workflow.
Agentic AI Across Disciplines
Participants work in parallel tracks focused on quantitative research, qualitative research, and teaching or administrative workflows. The emphasis is on building a prototype that is relevant to the participant's own disciplinary or operational context and needs.
Rapid Prototyping, Synthesis & Ethics
Participants complete a functional prototype, evaluate the quality of their prototype's output, use tools for cross-document synthesis, and work through a structured ethics seminar on hallucinations, privacy, publication policy, and responsible use of institutional and student data.
Refinement, Documentation, and Usability
Faculty participants develop tools for course design and teaching, while staff and faculty with administrative responsibilities build assistants for recurring workflows such as document processing, scheduling, reporting, and meeting support. By the end of Day 5, each participant has refined the tool through peer critique and instructor coaching, written a one-page Tool Guide, and prepared an outline for the fall symposium presentation.
Submit answers to four short questions by May 20, 2026.
Applying as a team? Designate one contact person and include the names of all members.
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A brief description of your work.
Your role, department or unit, and the kinds of tasks and projects that occupy most of your professional time. Two to three sentences are sufficient.
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The problem you intend to solve.
Describe a specific challenge, task, or area of your work where you believe an AI-powered tool or workflow could make a meaningful difference. Be as specific as you can: who experiences this problem, how does it currently affect your work, and why does it matter?
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A preliminary plan.
Describe the tool or workflow you envision — what it would do, who would use it, and what a successful outcome looks like. Applicants who can articulate both the problem and a plausible path toward a solution will be prioritized.
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What you hope to gain.
In a few sentences, tell us what success looks like for you at the end of the program.
Specificity of problem and plan are prioritized.
Participants will be selected to ensure a balance of disciplines, roles, and problem types across the cohort. Applications are reviewed with a focus on the specificity of the problem you identify and the details of your plan. You do not need a comprehensive plan — but your application should provide a clear sense of what you want to build and why.
If you have questions about CUA SPARK, please contact John Choy or Richard Kelley.