Overview
Explore how AI is transforming education with Derek Muller as he examines cognitive science principles, potential opportunities, and risks for learning in an AI-powered world, drawing from his expertise in physics education.
Syllabus
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- Introduction to AI in Education
-- Overview of AI technologies in educational settings
-- Historical context and evolution of AI in education
- Cognitive Science Principles in Learning
-- Key cognitive science concepts and their relevance to AI
-- How AI can enhance or hinder cognitive processes in learning
- Opportunities Offered by AI in Education
-- Personalized learning experiences through AI
-- Enhancing engagement and motivation via AI tools
-- Data-driven insights and adaptive learning platforms
- Risks and Challenges of AI in Education
-- Privacy concerns and data security in AI applications
-- Potential biases and inequalities introduced by AI systems
-- The risk of over-dependence on technology in learning
- Case Studies and Real-World Applications
-- Successful implementations of AI in classrooms
-- Lessons learned from AI deployment in different educational contexts
- Examining AI’s Impact on Physics Education
-- Specific examples from physics education enhanced by AI
-- Challenges and solutions unique to integrating AI in science education
- The Future of AI in Learning
-- Predictions and trends for AI development in education
-- Preparing educators and learners for AI-influenced futures
- Final Project
-- Analyze a current AI tool used in education
-- Propose improvements or new applications based on cognitive science principles
- Conclusion
-- Recap of the course learnings and critical reflections
-- Resources for further study and exploration in AI and education
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On-Demand
