1. Introduction to AI and Robotics
- Overview: Explore foundational AI concepts and applications across industries, along with the core principles of robotics.
- History and Evolution: Key milestones in AI and robotics, from early inventions to modern advancements in technology.
- Hands-On Component: Introductory activity where participants identify common AI applications in everyday life.
2. Programming Basics for AI
- Python Fundamentals: Introduction to Python syntax, basic data types, loops, and conditional statements.
- Coding Exercises: Simple exercises to write programs performing basic tasks, laying the foundation for AI applications.
- Data Handling: Brief introduction to data manipulation in Python, essential for developing AI applications.
3. Fundamentals of AI in Education
- Problem-Solving with AI: Understanding AI’s role in enhancing problem-solving and pattern recognition, with a focus on critical thinking.
- Case Studies: Examples of AI in education, such as adaptive learning platforms, feedback systems, and personalized learning experiences.
- Collaborative Activity: Group activity where participants brainstorm potential applications of AI in educational settings.
4. Integrating AI & Robotics with STEM
- Curriculum Alignment: Approaches for incorporating AI and robotics within the STEM curriculum.
- Workshop: Participants design a lesson plan that integrates basic AI or robotics concepts with STEM learning goals.
- Practical Examples: Review of educational tools and platforms that support AI and robotics learning in STEM.
5. Building a Simple Robot for Classroom Demonstration
- Introduction to Robotics Kits: Overview of popular educational robotics kits, including sensors, motors, and programmable parts.
- Hands-On Assembly: Guided assembly and programming of a basic robot, demonstrating functions like following instructions or responding to touch.
- Classroom Applications: Discussion on ways to engage students with robotics-based activities in a classroom setting.
6. Practical Coding for AI Tools
- Working with AI Models: Introduction to pre-built AI models, such as chatbots, basic image classifiers, and sentiment analysis tools.
- Training and Testing: Basic concepts in using training data, evaluating model accuracy, and interpreting AI outputs.
- Project: Set up a simple chatbot project to illustrate AI in action, allowing participants to customize and interact with AI responses.
7. Classroom Engagement Techniques
- Pedagogical Approaches: Strategies for teaching complex topics like AI and robotics effectively to various age groups.
- Interactive Learning: Techniques for fostering hands-on learning, promoting inquiry-based projects, and encouraging collaborative problem-solving.
- Student Engagement: Tailoring instructional approaches to different learning styles, emphasizing inclusivity and accessibility.
8. Assessment Strategies in AI Education
- Competency-Based Assessment: Approaches for evaluating practical AI and robotics skills, including problem-solving and critical thinking.
- Rubric Design: Crafting clear, objective rubrics for project-based assessments, quizzes, and hands-on activities.
- Feedback Mechanisms: Using AI-enabled tools for continuous formative assessment and constructive feedback.
9. AI Ethics and Responsible Use
- Ethics in AI: Exploration of key ethical considerations in AI, including bias, privacy, transparency, and accountability.
- Classroom Discussion: Facilitated discussion on ethical scenarios in AI, encouraging students to think critically about the social impact of AI technologies.
- Project: Students create a brief presentation on the ethical implications of a chosen AI technology, addressing potential benefits and risks.
10. Project-Based Learning
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- Final Project Design: Structuring a capstone group project where participants develop simple AI or robotics applications.
- Group Collaboration: Best practices for managing teamwork, assigning roles, and facilitating cooperative learning.
- Presentation and Review: Group presentations of projects followed by a class discussion, constructive feedback, and a reflection on project experiences.