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Course Outline
Introduction to Large Language Models (LLMs)
- Overview of LLMs
- Evolution of LLMs in educational technology
- Understanding the architecture of LLMs
Personalization in Education
- The need for personalized learning
- Current approaches to personalization
- Challenges and opportunities
LLMs and Content Adaptation
- LLMs in content creation and curation
- Adapting content to learning styles and levels
- Multitasking with LLMs for content adaptation
LLMs in Practice
- Case studies: Successful LLM applications in education
- Interactive session: LLMs at work
Designing Adaptive Learning Platforms
- Principles of adaptive learning platform design
- Incorporating LLMs into platform architecture
- User experience and interface considerations
Implementation and Testing
- Developing a prototype adaptive learning platform
- Testing and iteration
- Collecting and analyzing user feedback
Evaluating LLM Effectiveness
- Metrics for measuring LLM impact on learning
- Research methods for educational technology
- Case study analysis and discussion
Ethical Considerations and Future Directions
- Ethical implications of LLMs in education
- Ensuring inclusivity and fairness
- Predictions for the future of LLMs in personalized learning
Project and Assessment
- Designing and presenting a proposal for an LLM-based adaptive learning platform
- Peer reviews and group discussions
- Final assessment and feedback
Summary and Next Steps
Requirements
- An understanding of basic machine learning concepts
- Experience with programming in Python is recommended but not required
- Familiarity with educational technology is beneficial
Audience
- Educators
- EdTech developers
- Researchers in the field of educational technology
14 Hours
