Integrating Generative Models in the Classroom: Exploring Risks and Benefits

Introduction to Generative Models (1 hour)

• Overview of generative models and their applications
• Explanation of different types of generative models (e.g., GANs, VAEs)
• Discussion on the potential benefits and risks in educational contexts

Benefits of Generative Models in Education (1.5 hours)

• Enhancing creativity and critical thinking skills among students
• Fostering student engagement through interactive learning experiences
• Personalizing educational content to cater to individual student needs
• Encouraging exploration and experimentation in complex subjects

Risks and Ethical Considerations (1 hour)

• Discussion on potential risks associated with generative models in education
• Addressing issues of data privacy, security, and responsible AI usage
• Examining potential biases and ethical implications in generative model outputs
• Strategies for mitigating risks and promoting responsible use of generative models

Practical Implementation of Generative Models in the Classroom (2 hours)

• Exploring various tools and platforms for generative model integration
• Collaborative activity: Creating a generative model project for a specific subject area
• Group discussions on challenges and best practices for implementation
• Sharing successful case studies and real-world examples

Hands-on Session: Building and Interacting with Generative Models (2.5 hours)

• Step-by-step guidance on using generative model frameworks and libraries
•  Hands-on activity: Training a simple generative model using provided datasets
• Experimenting with model parameters and observing the generated outputs
• Reflection and discussion on potential classroom applications

Wrap-up and Closing Remarks (30 minutes)

• Recap of key insights and takeaways from the workshop
• Addressing participant questions and concerns
• Sharing additional resources for further exploration and learning

Benefits:

• Enhance student engagement and motivation by introducing interactive learning experiences.
• Foster creativity and critical thinking skills among students through generative model projects.
• Enable personalized learning experiences tailored to individual student needs.
• Empower students to participate in the creation and exploration of educational content actively.
• Explore the potential of generative models to simplify complex concepts and promote understanding.

Risks:

• Data privacy concerns regarding student information and generated content.
• Potential biases in generative model outputs that need to be carefully addressed.
• Ethical considerations related to responsible AI usage, transparency, and fairness.
• Technical challenges in implementing and integrating generative models in the classroom.
• The need for educators to acquire sufficient knowledge and expertise to utilize generative models effectively and responsibly.

Secretariat

• Virginia Stever (ub-iad@buffalo.edu)

Organizing Committee:

• David Doermann (doermann@buffalo.edu)
• Margarete Jadamec (mjadamec@buffalo.edu)
  
• Matthew Hertz (mhertz@buffalo.edu)