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Webinar Resources: Generative and Agentic AI for Teaching and Learning

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Webinar Description

As Artificial Intelligence moves from simple text generation to autonomous agentic workflows, the potential impact for higher education is greater than ever. Join us for a session showcasing real-world applications of AI at Arizona State University (ASU). We will explore how multi-step agents, lifelike avatars, and immersive tools are reshaping curriculum design and student engagement.
Resource Sharing
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Description
These are the slides the presenter used to present.
This links directly to the presentation video on YouTube.
This is the mission that drives our desire to expand learning opportunities.
Agentic AI example:
This is a current example of agentic AI discussed during the presentation (requires subscription).
Agentic AI example:
This is a current example of agentic AI discussed during the presentation (requires subscription).
Agentic AI example:
This is a current example of agentic AI discussed during the presentation (requires subscription).
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Questions from the audience
Question
Response
Trust, Autonomy & Governance of Agentic AI: As agentic AI systems become more autonomous, how can organizations build trust, ensure appropriate oversight, and strategically integrate generative and agentic AI into higher education while maintaining academic integrity?
Open
Infrastructure & Building AI Agents (Technical Capacity): Are there free or open frameworks available for building AI agents, and what are their practical limitations—especially in resource-constrained institutions?
Open
The Future of Assessment & the University Model: If both faculty and students use generative and agentic AI extensively, how will this reshape examinations, learning outcome assessment, and the overall value and structure of university education in the next 5–10 years?
Open
Agentic AI Acting as “Student Agents” (Einstein Example): What is the impact of autonomous “student agents” (e.g., tools that log into LMS platforms, complete coursework, and submit assignments), and how should institutions respond in terms of assessment design and academic integrity?
Open
Designing Autonomous Student-Support Agents: What would a responsible, autonomous student-support AI agent look like in higher education—one that proactively detects risk, coaches students, and escalates concerns appropriately?
Open
Leveraging Multiple AI Agents for Teaching, Research & Humanities: How can educators strategically leverage the unique strengths of different AI agents for research, case writing, humanities scholarship, and teaching, and how should they evaluate which tools are most appropriate?
Open
Deep Research: What is the meaning of deep research? Is it a single tool?
Open
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