AI+ Learning & Development (AILD) – Outline

Outline detalhado do curso

Module 1: Introduction to Artificial Intelligence (AI) in Education

  • 1.1 Overview of Artificial Intelligence
  • 1.2 AI’s Role in Education and Training
  • 1.3 Impact of AI on Educational Content Creation
  • 1.4 AI in Assessment and Feedback
  • 1.5 Ethical Considerations and Challenges

Module 2: Machine Learning Fundamentals

  • 2.1 Introduction to Machine Learning
  • 2.2 Supervised Learning
  • 2.3 Unsupervised Learning
  • 2.4 Reinforcement Learning
  • 2.5 Machine Learning in Practice

Module 3: Natural Language Processing (NLP) for Educational Content

  • 3.1 Fundamentals of NLP in Education
  • 3.2 Content Analysis and Enhancement
  • 3.3 Personalized Learning and Adaptive Content
  • 3.4 Assessment and Feedback Automation

Module 4: AI-Driven Content Creation and Curation

  • 4.1 AI in Generating Educational Content
  • 4.2 Adaptive Learning Materials Creation
  • 4.3 Dynamic Assessment Item Generation
  • 4.4 Curating Educational Resources
  • 4.5 Challenges and Ethical Considerations in AI-Driven Content

Module 5: Adaptive Learning Systems

  • 5.1 Foundations of Adaptive Learning
  • 5.2 Designing Adaptive Learning Systems
  • 5.3 Implementation Strategies
  • 5.4 Assessment and Evaluation in Adaptive Systems
  • 5.5 Ethical and Privacy Considerations

Module 6: Ethics and Bias in AI for L&D

  • 6.1 Understanding AI Ethics in L&D
  • 6.2 Privacy Concerns in AI-Driven L&D
  • 6.3 Bias and Fairness in AI Assessments
  • 6.4 Ethical AI Use and Learner Engagement
  • 6.5 Future Challenges and Opportunities

Module 7: Emerging Technologies and Future Trends

  • 7.1 Augmented Reality (AR) in Education
  • 7.2 Virtual Reality (VR) in Learning Environments
  • 7.3 AI-Driven Personalized Learning
  • 7.4 Blockchain in Education
  • 7.5 Emerging AI Technologies in Educational Research and Development

Module 8: Implementation and Best Practices

  • 8.1 Strategic Planning for AI Integration
  • 8.2 Selecting the Right AI Tools
  • 8.3 Implementing AI Solutions
  • 8.4 Monitoring and Evaluating Impact
  • 8.5 Ethical Use and Data Governance