ICYMI! Recap of the AI Course Redesign Institute

  • Publication date August 24, 2025

How can we be both champions and critics of AI in education? What does it mean to redesign our courses thoughtfully in an era of rapid technological change? In our recent AI Course Redesign Institute, faculty from across UTA explored these essential questions while gaining practical tools and strategies for integrating AI into their teaching practice.

What We Covered

The institute brought together faculty for a full day of learning, discussion, and hands-on work. Pete Smith from Modern Languages opened with a thought-provoking keynote about being both “crusaders” and “critics” of AI—embracing the technology’s potential while maintaining the critical lens that academia demands. The CRTLE team then guided participants through policy development, instructional strategies, and practical applications, with special sessions on Khanmigo, AI chatbots, and effective prompting techniques.

Key Takeaways

  • Live in the Complexity. Pete Smith challenged us to sit with the contradiction of being both AI advocates and critics. As he noted, we can champion these tools while still asking hard questions about bias, environmental impact, hidden labor, and the concentration of power in “big seven” tech companies.
  • Policy as Foundation. Dr. Peggy Semingson emphasized that clear AI policies aren’t restrictions—they’re roadmaps. The institute provided copy-and-paste policy templates that faculty can adapt immediately for their syllabi, establishing transparency and expectations from day one.
  • Beyond the Hype, Into the Classroom. Karen Magruder and Heather Philip showed practical ways to redesign traditional assignments into AI-inclusive learning experiences. Think: students using AI as a thought partner rather than a replacement for thinking, with alternative assessments that showcase genuine learning.
  • Tools That Scale. The team introduced Khanmigo’s Canvas integration—an AI teaching assistant that helps with everything from lesson planning to rubric creation. As Melissa Roach and Joseph Rutledge demonstrated in the July webinar, these tools are instructor-facing only and have been vetted for security and accessibility.
  • Work Time = Real Progress. The institute wasn’t just talk—participants spent dedicated time redesigning actual course materials and creating personal action plans for AI integration. Some redesigned traditional essays into AI-collaborative projects; others developed comprehensive AI literacy modules.

Part One of the Panelists

The initial panel focused on redesigning an AI course, emphasizing the dual role of supporting AI advancement while critically examining its societal impacts, biases, and ethical concerns.

Part One Big Ideas (summarized by Microsoft CoPilot):

  • Course and policy introduction: The session begins with an overview of free AI-related resources and outlines the agenda, including policy crafting and instruction discussions. 1
  • Balancing enthusiasm and critique: The speaker highlights the challenge of being both advocates for AI and critical evaluators, especially in academia, encouraging reflection on this dual stance. 2
  • Historical context of language models: Large language models have been used in modern languages and translation since the early 2000s, with tools like Google Translate as early examples, evolving significantly since 2017. 2
  • Focus on multilingual performance: The course track emphasizes how language models perform across various languages beyond English, such as Spanish, Swahili, Icelandic, and Indonesian. 2
  • Critical voices and scholars: Key critics like Gary Marcus, Emily Bender, and Noam Chomsky are introduced, raising questions about model understanding, biases, fairness, and the ethical implications of AI development. 2
  • Ethical and labor concerns: The discussion addresses issues such as gender bias, hidden labor exploitation in AI training data, corporate control of AI technologies, and intellectual property disputes. 2
  • Environmental impact awareness: The environmental costs of AI, including data center construction and energy use by companies like Meta, are acknowledged as a growing concern in the AI community. 

Part Two of the Panelists

Summary of Key Ideas from Part Two (summary from Microsoft Co-Pilot):

The main topics discussed include the environmental impact of large language models and data centers, the use of AI in education, and the development of AI literacy among students.

  1. Environmental Impact of AI:
    • Pete Smith highlighted concerns about the environmental impact of large language models and data centers, including their power and water consumption. Examples include data centers being built by Meta, Tesla, and AIX, and the potential political and ecological issues they cause
    • The importance of considering the ecological impact of AI and data centers is emphasized, with references to experts like Satya Lucione and Henry Spike-sentra
  2. AI in Education:
    • Ideas about the integration of AI in educational settings, including the use of AI tools for generating ideas, brainstorming, revising, and editing were shared.
    • Various AI tools like Adobe Firefly, ChatGPT, Midjourney, and Canva are mentioned for creating images, graphics, and videos
    • The importance of accessibility in AI-generated content is highlighted, including the need for alt text and color contrast
  3. AI Literacy and Ethical Use:
    • Ideas about stressing the need for developing AI literacy among students, including understanding the ethical use of AI and the potential risks and drawbacks were shared.
    • The importance of transparency and context in using AI is discussed, with examples of how AI can be used appropriately in different contexts
  4. Practical Applications and Teaching Strategies:
    • Several practical examples of using AI in the classroom are provided, such as generating case studies, refining assignment directions, creating rubrics, and developing discussion topics
    • Ideas were shared about the use of AI for role plays, critiquing AI responses, and making assignments more engaging and innovative
  5. Resources and Further Reading:

Overall, part two provided a comprehensive overview of the current state of AI in education, the environmental impact of AI, and the importance of developing AI literacy and ethical use among students.

Want to Get Started?

Here are the resources shared at the institute to help you dive in:

Join the Conversation

We’d love to hear from you! How are you balancing enthusiasm and skepticism about AI in your courses? What redesigns have you tried? Share your thoughts, questions, and experiences in the comments below. Let’s keep the conversation going!