Join us in August at [CrowdCast Link] for an insightful and interactive 2-hour panel session, where emerging technology leaders will explore the potential of Web3 and its three layers: Blockchain, Machine Learning, and AI (Generative Models) as tools to accelerate education, and how they can be leveraged to enhance both student and teacher performance. The session will be divided into three parts, with each focusing on a different layer of the Web3 data model, and real-world examples of its application in the classroom. Our panelists are technology leaders in each of these fields and will share their insights and knowledge on how to use these technologies to revolutionize both teaching and learning.

Event Description:

Join us for a 2-hour interactive panel session that dives into the world of Web3 and its tools, and how they can revolutionize both teaching and learning. This event will explore how blockchain, machine learning, and generative AI can be leveraged as tools in the classroom, giving educators and students a competitive edge in the digital age.

The session will be divided into three distinct parts, each focusing on a different layer of the Web3 data model. Attendees will learn how each layer works, its relevance in the educational sector, and real-world examples of its application in the classroom. The overall theme emphasizes the potential of these technologies to accelerate education, and how they can be harnessed to enhance both student and teacher performance.

Event Agenda:

Title: "Leveraging Web3 Technologies to Accelerate Education: A 2-Hour Level Three Educational Panel Session"

Objective: To explore and understand the potential of Web3 technologies, specifically Blockchain, Machine Learning, and Generative AI, as tools to accelerate both student and teacher development in the education sector. The audience will learn about the real-world applications and benefits of these technologies and leave with a deeper understanding of how to leverage these tools in the classroom.

1. Introduction (5 minutes)
   • Welcome and opening remarks by the session host
   • Overview of the panel session and its objectives
   • Introduction Script
2. Session 1: Introduction to Web3 and Its Three Layers (30 minutes)
   • Presentation on the three layers of Web3: Data Layer (Blockchain), Interpretation Layer (Machine Learning), and Presentation Layer (Generative AI)
   • Exploration of how these layers interact and their role in the Web3 landscape
   • Presenter: Shai Perednik, Web3 & Emerging Technology Leader
3. Break (5 minutes)
4. Session 2: Blockchain and Education (30 minutes)

   • Panel discussion on the applications and benefits of blockchain technology in education, driving Education 3.0

     Q1: How can blockchain technology be used to create secure and transparent educational records for both students and teachers?

     • Follow-up 1: What are the potential benefits of implementing blockchain-based educational records, in terms of efficiency and data security?

     Q2: How does blockchain technology promote collaboration and resource sharing among educational institutions?

   • How blockchain can be utilized as a tool for both students and teachers

     • Examples of blockchain use in the education sector

   • Panelists: 3 experts in blockchain technology and education

   • Moderator: Shai Perednik, Web3 & Emerging Technology Leader

5. Break (5 minutes)
6. Session 3: Machine Learning and Education (30 minutes)

   • Panel discussion on the role of machine learning in interpreting underlying data and its applications in education

     Q1: How can machine learning help in identifying and addressing learning gaps among students with diverse learning needs?

     • Follow-up 1: How can machine learning help teachers in creating personalized learning paths for their students based on their abilities and learning styles?

     Q2 How can machine learning algorithms be employed to analyze student performance data and identify trends or patterns that can help improve instruction?

     • Follow-up 1: What types of data should educators prioritize when using machine learning for performance analysis?
     • Follow-up 2: Can you share examples of schools or institutions that have successfully used machine learning to analyze student performance data and improve instruction?

     Q3: How can machine learning be used to create intelligent tutoring systems that adapt to individual student needs and improve learning outcomes in real time?

     • Follow-up 1: What are the primary indicators that machine learning algorithms should focus on when identifying students with learning difficulties?

   • How machine learning can be utilized as a tool for both students and teachers

     • Exploration of the technology stack used in machine learning and how it makes sense of data. What portions are the stack are critical for educators to understand and why?

   • Panelists: 3 experts in machine learning and education

   • Moderator: Machine learning expert

7. Break (5 minutes)
8. Session 4: Generative AI and Education (30 minutes)

   • Panel discussion on the applications and benefits of generative AI, such as ChatGPT, other large language models, and multimodal models, in education

     Q1: How can generative AI help teachers in streamlining their workload and facilitating more effective student-teacher interactions?

     Q2: How can generative AI help teachers in automating content creation, such as generating quizzes, tests, or writing prompts, to save time and streamline their workload?

     • Follow-up 1: What are the potential limitations or pitfalls of using generative AI for automating content creation in education?
     • Follow-up 2: Can you share examples of schools or institutions that have successfully used generative AI to support teachers in content creation and saved time?

     Q3: How can generative AI be used to provide real-time feedback to students on their written work, helping them to improve their writing skills and understanding of course material?

     Q4: How can generative AI be integrated into the learning curriculum, such as using large language models to generate history or other topic content, and having students fact-check the AI as a learning exercise?

     • Follow-up 1: What are the potential benefits of integrating generative AI into the learning curriculum in this manner, both in terms of student engagement and skill development?
     • Follow-up 2: Can you provide examples of teachers or educational institutions that have successfully implemented generative AI in their curriculum in creative ways, such as the fact-checking exercise mentioned?

   • How generative AI can be utilized as a tool for both students and teachers with examples

     • Real-world examples of generative AI being used to accelerate education (Khanmigo @ Khan Academy)

   • Panelists: 3 experts in generative AI and education

   • Moderator: Generative AI expert

9. Conclusion (5 minutes)
   • Closing remarks by the session host
   • Summary of key takeaways
   • Q&A and final thoughts

Event Takeaways:

• Educator focused understanding of Web3 and its three layers: Blockchain, Machine Learning, and AI (Generative Models).
• Strategies for educators to leverage these tools as tools to accelerate their teaching and students' learning.
  • Practical understanding of these technologies' applications in education.
  • Real-world examples of current initiatives using these technologies in classrooms.