Methodology:
Blended Learning: This course will combine interactive lectures, hands-on workshops, group discussions, and individual reflection.
Expert-led instruction: Trainers will be experienced educators with expertise in AI and educational technology.
Peer collaboration: Encouraging collaboration through breakout sessions, lesson plan development, and resource sharing will foster a supportive learning environment.
Active learning: Participants will actively engage with the material through hands-on activities, simulations, and prompt creation.
Technology integration: The course will utilize various AI tools and online platforms to provide a practical learning experience.
Assessment:
Formative assessment:
Pre-course survey: Gauges participants' prior knowledge and expectations.
Interactive activities and discussions: Trainers will observe participation and provide immediate feedback.
Breakout session reports: Encourages reflection and collaboration during AI tool exploration.
Peer feedback on lesson plans: Promotes critical thinking and refinement of AI integration.
Exit tickets: Allows trainers to assess knowledge retention and gather feedback on course effectiveness.
Summative assessment:
Final lesson plan presentation: Participants showcase their AI-integrated lesson plan, demonstrating their knowledge of AI, prompting, and application.
Post-course survey: Measures learning outcomes and gathers feedback on overall course experience.
Additional Considerations:
Differentiation: Trainers will be prepared to cater to participants with varying levels of technological experience.
Follow-up support: Participants will receive a list of resources and access to a dedicated online forum for continued learning and communication.
This methodology and assessment approach aims to create a dynamic and engaging learning experience.