Afternoon Exploration Sessions: Insights from CWRU partners, Panel Discussion
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Afternoon Exploration Sessions (1:30-3:30 PM)
Generative AI in teaching, learning, and research across campus
Faculty Course Planning and GenAI: Making Decisions that Work for My Class and My Students
Matthew Garrett, UCITE
1:30 - 1:50 PM
It seems that just about everywhere you look, there’s new information to digest about the use of GenAI tools in higher education. With all of that “information overload,” faculty may want to pause and consider IF GenAI tools are appropriate for a given course, and how to communicate intentions and guidelines with students. We will briefly explore decision-making ideas for including GenAI tools in courses and examine faculty colleagues’ ideas for syllabus statements. Bring a laptop or tablet to explore options together with our group.
Empowering Research Writers: Integrating GenAI Literacy into Writing Projects
Martha Schaffer, CWRU Writing Program
1:55 - 2:15 PM
In this session, Martha Schaffer, of the Writing Program, will share ways to develop research writing projects that actively engage students with their research topics and make use of GenAI in the writing process. Martha will share perspectives and experiences from her course "Writing & AI" as well as examples of activities and best practices for teaching and learning AI literacy in the context of a research project.
AI in Action: Boosting Your Course Design and Admin Workflows
Indra Wangsawiredja and Razan Badran, Teaching and Learning Technologies
2:20 - 2:40 PM
The session is designed to demonstrate the power of Gen AI tools, equipping you with practical techniques to enhance course design, streamline administrative tasks, and save valuable time.
Generative AI and CWRU Research Computing
E.M. Dragowsky, High Performance Computing Team, Research Computing
2:45 - 3:05 PM
Generative AI (artificial intelligence) capabilities have emerged from decades of research efforts intended to mimic human learning. The advent of using graphical processing hardware to implement the 'machine learning' (ML) algorithms allowed breakthroughs in classification and prediction. We will briefly review the compute hardware resources that make this possible, and provide an overview of work by CWRU researchers that implements these methods. Finally, a description of resources at CWRU Research Computing and external institutions will provide context for current and future research developing and leveraging ML/AI methods and applications.
Questions and Discussion
3:05 - 3:15 PM
BREAK
3:15 - 3:30 PM
Panel Discussion
3:30 - 4:30 PM
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Tina Oestreich, Teaching and Learning Technologies
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Matthew Garrett, UCITE
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Kimberly Emmons, Writing Program
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E.M. Dragowsky, Research Computing
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Yolanda Cooper, Kelvin Smith Library
Hosted By
Co-hosted with: Explore
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