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Basics about Artificial Intelligence (AI) and teaching can be found on FCTL’s page on AI. Those looking for more information and some hands-on practice might wish to enroll in one of our programs that offer a deeper dive:

  • AI Fundamentals for Educators Course – this face-to-face “course” uses both modules in Webcourses and eight weeks of in-person meetings on the main Orlando campus. The meetings are two hours long, with the second hour serving as a hands-on lab. It uses a cohort model, so sign ups only happen near the start of each semester (summer, fall, and spring). Those who complete the course (do all readings and attend 7 of the 8 sessions) will receive an informal paper certificate.
  • AI Essentials for Faculty Online Modules – this is a fully-online, asynchronous exploration of AI tools and how to use them. Since this is self-paced, faculty can enroll themselves at any time, with no deadline for completion. This option does not lead to a certificate.

As each cohort completes the F2F “AI Fundamentals” course, the names of those with completion certificates will be listed here.

Elements of the AI Fundamentals Course:

  • Class One: Introduction to LLM Models and Prompt Engineering – We’ll begin by discussing and demonstrating how LLM models work, and exploring the similarities and differences in ChatGPT, Bard/Genesis, CoPilot (Bing Chat), and Claude. Then, we’ll look at the art of prompt engineering through a series of steps for a variety of disciplines. Participants will leave with an understanding of how GenAI LLM’s work, and how students can use them for existing (pre-GenAI tools) assessments and assignments.
  • Class Two: Introduction to Image, Audio, and Video Generation Tools – In this class, we’ll demonstrate how to generate images (and check for bias) with Dall-E, Adobe Firefly, Stable Diffusion, and Canva. We’ll also show how to create interactive audio experiences with Duet AI and how to create videos with Imagen Video. Finally, we’ll show apps that can ensure your course meets digital accessibility requirements, including Murf.ai and Natural Reader (both convert text to audio/speech) and Otter (generates audio to text, real-time transcripts, integrates with Zoom).
  • Class Three: Altering/Creating Assignments and Assessments – Now that we know what GenAI tools can—and can’t—do for students regarding our course content, we’ll look at how to alter assignments that require students to use GenAI tools in a transparent, informed manner. These assignments will be created to increase a student’s AI fluency while requiring them to engage in tools they’ll likely use in their careers, disciplines, or other related venues outside of the course. Participants will bring assignments and leave with altered assignments that include GenAI tools AND assignments that are unable to be completed by GenAI tools.
  • Class Four: Interactive F2F Classroom Teaching – Create more interactive learning opportunities for students by leveraging GenAI tools in the classroom. We’ll model various activities using various GenAI tools, including presentation support (generate interactive concept maps, graphs, tables, diagrams, images); real-time polling; gamification (impromptu Q&A contests with surprise AI bot questions, escape room scenarios); and interactive role-playing (business case studies, scenario evaluations/interviews/debates). Then, we’ll brainstorm ideas for your individual courses.
  • Class Five: Interactive Online Teaching – GenAI tools can help make an online course feel more personal. In this section, we’ll look at how to use GenAI tools to create interactive Q&A sessions in real time via chat (for help outside of office hours), deliver instant automated feedback on submitted assignments (enabling students to revise and resubmit faster), and produce visual lecture/content recaps (combine transcriptions, key images/charts/audio snippets, etc.) 
  • Class Six: Using AI Tools for Research – AI apps extend beyond GenAI tools. In this section, we’ll look at Research Rabbit, Semantics Scholar, QuillBot, SuperSymmetryAI, Claude, and ChatGPT to work through how students—and faculty—can use these tools to find, understand, and summarize discipline-specific academic papers and research. We also look at ways to teach students how to use GenAI tools to generate ideas and outlines for research topics, analyze data (and display it visually), and cite sources correctly (and check work for plagiarism).
  • Class Seven: Customizing AI Models – Various AI tools can help you create a chatbot customized for your course. This chatbot acts as a personal assistant to you and a tutor for your students. Some features we’ll demonstrate are how you can use it to answer student questions related to content, deliver customized feedback and support, individualize explanations and student guides, generate prompts and sample problems, and automatically send customized emails to students based on assessment performance. Note: while some of these tools are free, many aren’t, but faculty may consider their subscription prices (most around $20/month) a worthwhile investment due to their time-saving abilities.
  • Class Eight: Teaching Students AI Fluency – In this wrap-up class, we’ll discuss how we can take what we’ve learned during this course and use it to help students become more fluent in AI. We’ll also talk about how to create AI course policies, lead ethical discussions on AI, generate transparency templates, and incorporate AI into grading rubrics. And we’ll all showcase the tools we’ve implemented during this course and share our plans for moving forward.

Registration for the F2F Fundamentals of AI Course

Classes are capped at 25 participants.

Spring 2024 registration is full. We will offer Summer and Fall 2024 options soon, which will be announced on our listserv.

Email fctl@ucf.edu with any questions.