Digital Skills for Teacher Training: Sustainable and Non-Formal Methods in Maths and Stats with Coding and AI
▶Summary
Integrate Coding & AI into Math & Stats: Develop lesson plans with R, Python, and AI tools. Support Teachers: Provide training, workshops, and AI-powered teaching materials (Modules for teachers)....
▶Objectives
Integrate Coding & AI into Math & Stats: Develop lesson plans with R, Python, and AI tools. Support Teachers: Provide training, workshops, and AI-powered teaching materials (Modules for teachers). Develop Open-Source Tools: Create an R/Python library and AI exercises. Evaluate Methods: Compare coding vs. traditional teaching and offer policy recommendations. Analyze Impact: Study AI’s effect on focus, cognitive load, and engagement.
▶Activities
Teacher Training: Hands-on sessions and webinars on AI and coding in math education. Resource Development: Create lesson plans, coding exercises, and an R/Python package. Classroom Testing: Test coding vs. traditional methods and assess performance and cognitive load. Research & Data: Gather feedback through surveys and eye-tracking for engagement analysis. Dissemination & Sustainability: Share results via Erasmus+ platforms, conferences, and work with policymakers for education integration.
▶Impact
15+ teachers trained in coding-based math education. 15+ students engaged in digital learning. A validated teaching framework for integrating coding & AI in schools. Development of open-access resources (lesson plans, coding libraries, AI tools). Comparative research findings on digital vs. traditional teaching effectiveness. Improved student engagement, motivation, and problem-solving skills. Long-term sustainability through continued teacher training and open resources.