GenAI EDU Panel Series

January 23, 2025

The Unizin Faculty Development Subcommittee has launched a panel discussion series on Generative AI in Education. The webinars will explore the ethical principles that have been developed over the past year by the committee (with input from the consortium at large).

• The first session was held on Nov. 6, 2024, covering Principle 1: "Generative AI should prioritize educational relevance in the learning context." Panelists, including our own Dr. John Jordi, explored how generative AI can be used effectively and ethically in education, with a focus on:
  • Aligning AI tools with curriculum and learning goals
  • Ethical considerations like data privacy and student engagement
  • Integrating AI to supplement—not replace—student work
  • Using AI to foster collaborative learning
• The second session was held on Dec. 4, 2024, covering Principle 2: "Instructors should be transparent about their acceptance of Generative AI use in the learning process.” The topic goals included:
  • Learn how to communicate when and how Generative AI will be used in your course to foster trust, uphold academic integrity, and promote ethical practices.
  • Understand how to educate students about the roles, capabilities, and limitations of AI tools, and how to address biases in AI-generated outputs.
  • Explore strategies for instructors to model responsible AI use in the classroom,
    demonstrating both its strengths and limitations.
  • Discover ways to engage students in discussions about AI, including feedback
    mechanisms to assess its effectiveness and accuracy.
• The third session will be held on Jan. 30, 2025 at 11am (Registration form) for Principle 3: "Generative AI should be taken into account when developing educational uses (e.g. activities, assessments and assignments).” In this 60-minute webinar, they’ll explore how generative AI can enrich the learning experience by supporting creativity, critical thinking, and knowledge retention, with a focus on:
  
  • Enhancing Learning with AI: Highlighting strategies to integrate AI
    meaningfully or reduce its dependency through innovative assessments and activities.
  • Design and Evaluation Best Practices: Learn how to design assignments, projects,
    and rubrics that effectively balance AI's capabilities with academic integrity.
  • Consistency and Collaboration: Emphasize the importance of departmental
    alignment in AI policies and practices to ensure consistency across courses.

This post will be updated with future session dates as they become available.