AICC: UF AI Course Designation Terms and Requirements Reference Guide

UF AI course designation is an approved and required part of the UF course approval system. Courses are reviewed by the AI Curriculum Committee (AICC). The AICC is comprised of leading UF AI faculty representing all colleges at UF and AI2 Center staff.  

Through the AI course designation process, AI courses are reviewed and vetted to assure they meet UF AI course content requirements as well as receiving one of the five AI categories. The AI categories Use-AI, Know-AI, Build-AI, Ethical-AI, and Enable-AI allow students to consistently identify AI courses across campus and the type/level of AI content expected in a course. The AI designated courses include assignments that directly address SLOs aligned with the five AI Literacy categories

Before submitting your course for review, select an AI course designation category and ensure your syllabus is aligned with the requirements listed below. If you have any questions or concerns, please reach out to Mackenzie Donovan at Mackenzie.Donovan@aa.ufl.edu .

Submit for AI Course Designation

Currently, AI course designation is only open to new and existing undergraduate courses. Review processes for graduate and professional courses are coming soon.

To submit your course materials for review, use the AI Course Submission Form corresponding to link that best describes your course:

Submit a new course for AI course designation: New Undergraduate Course

Submit an existing course for AI course designation: Existing Undergraduate Course

AI ARTIFICIAL INTELLIGENCE (AI)

The term “artificial intelligence” means a machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations, or decisions. One way to think of AI is as a computer system that can perform tasks that would typically require human intelligence, such as understanding natural language, recognizing objects in images, making decisions, and playing games. AI systems can be trained using large amounts of data and a process called machine learning and can improve over time as it is exposed to more data.

In a university course on AI, students will typically learn about topics including but not limited to:  

• The history and foundations of AI
• Problem-solving techniques, such as search and planning
• Knowledge representation and reasoning, including formal logic and ontologies
• Machine learning, including supervised, unsupervised, and deep learning
• Natural language processing, including you understand and generate human language
• Perception, including computer vision and sensor-based AI
• Robotics, including robot planning and control
• Ethical, legal, policy, and other social implications of AI
• How to design and implement AI systems
• Theoretical and practical issues related to AI systems 

If you teach a course that you are submitting for AI designation and do not see your course AI topic listed, please contact us at ai@ufl.edu. 

AI Categories

Indicate the requested AI category designation for this course. Categories Know-AI, Use-AI, Build-AI, and Ethical-AI require 50% of course content to be related to AI and faculty must indicate which category best fits the course content. Category AI5 would be selected if greater than 10% and less than 50% of the course content is related to AI.

Most courses fit into only 1 primary category designation, however, if you want to request multiple AI categories, contact the chair of the UF AI Curriculum Committee at ai@ufl.edu for guidance. For example, a course containing 100% AI-related content wanting to choose two designations could be a course that has content that contains 50% AI know and understand and 50% AI ethics.

• Know-AI 
  Know & Understand AI: Know the basic functions of AI and to use AI applications. AI course content is over 50%
• Use-AI
  Use & Apply AI: Applying AI knowledge, concepts, and applications in different scenarios. AI course content is over 50%
• Build-AI
  Evaluate & Create AI: Higher-order thinking skills (e.g., evaluate, appraise, predict, design) with AI applications. AI course content is over 50%
• Ethical-AI
  AI Ethics/Policy: Human-centered considerations (e.g., policy, fairness, accountability, transparency, ethics, safety). AI course content is over 50%
• Enable-AI
  AI Enabled: Courses that are not completely AI-focused, but rather are enriching and enabling AI knowledge and skills through complementary skills and/or knowledge. AI course content is 10-49%

Student Learning Outcomes (SLOs)

The AI SLOs describe the knowledge, skills, and attitudes that students are expected to acquire while completing an AI course at the University of Florida. 

The inclusion of the verbatim statements for the SLO(s) corresponding to the AI category is a required component of AI courses and syllabi. 

FOR EACH SELECTED SLO, additional information is required including a proposed assessment of the SLO with a specific course assignment. 

Know-AI: Know & Understand 

• SLO1. Identify, describe, and/or explain the components, requirements, and/or characteristics of AI. 
• SLO2. Recognize, identify, describe, define, and/or explain applications of AI in multiple domains. 
• Use-AI: Use & Apply 
  SLO3. Select and/or utilize AI tools and techniques appropriate to a specific context and application. 
• Ethical-AI: AI Ethics/Policy
  SLO4. Develop, apply, and/or evaluate contextually appropriate ethical frameworks to use across all aspects of AI. 
• Build-AI: Evaluate & Create 
  SLO5. Assess the context-specific value or quality of AI tools and applications. 
• SLO6. Conceptualize and/or develop tools, hardware, data, and/or algorithms utilized in AI solutions. 
• Enable-AI: AI Enabled 
  Any of the six SLOs previously mentioned. The difference here is simply in the amount (%) of content covered in the course. Any of the above AI types can be covered under the AI Enabled category.  

UF AI Course Syllabi Requirements

• Include AI category and verbiage associated with the category.
• Inclusion of the verbatim statements for the SLO(s) corresponding to the AI category is a required component of AI courses and syllabi. 
• Must include a weekly schedule of topics and some description of each assignment. Topics and assignments that directly relate to meeting SLO(s) should be clearly noted with the specific SLO(s) in the syllabi. See the template below.

Required Documents

Please upload the syllabus after the request has been created and submitted. You may use the "Add Document" button to upload.

Example of Successful AI Designated Syllabus

Tips / Form Translation:

On the second page of the form….

• “Title of request” enter – the Course Title Course Prefix and Number
• “Description of request” enter – “Requesting AI Course Designation”