Course Outline

Introduction to Small Language Models (SLMs) in Educational Technology

  • Overview of Small Language Models
  • The Evolution of Artificial Intelligence in Education
  • Benefits of SLMs for Personalized Learning

Designing Learning Experiences with SLMs

  • Understanding Learner Needs and Preferences
  • Creating Adaptive Learning Pathways
  • Integrating SLMs with Instructional Design Principles

Implementing SLMs in Educational Settings

  • Setting Up SLMs for Classroom and Online Learning
  • Developing Interactive Content with SLMs
  • Best Practices for Maintaining Student Engagement

Evaluating SLMs in Learning Outcomes

  • Assessment Strategies for AI-Driven Learning
  • Data Analysis and Learning Analytics
  • Continuous Improvement and Feedback Loops

Challenges and Ethical Considerations

  • Addressing Biases in AI
  • Ensuring Data Privacy and Security
  • Promoting Equitable Access to AI Resources for Government and Educational Institutions

Project Work and Case Studies

  • Designing a Mini-Project Using SLMs
  • Case Study Analysis of SLMs in Action
  • Group Presentations and Peer Feedback

Summary and Next Steps

Requirements

  • Basic understanding of machine learning concepts for government applications
  • Experience in educational technology or instructional design for government programs
  • Interest in AI-driven educational solutions for government initiatives

Audience

  • Educational technologists working in the public sector
  • Instructional designers focused on government projects
  • AI developers specializing in educational technology for government use
 14 Hours

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