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Action Simulator
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Welcome page
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Story Module
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Teacher Dashboard
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Explore Data
About the Project
Understanding, addressing, and taking action on climate change is becoming an increasingly difficult task for our planet. Many people find the problem to be remote, complicated, and challenging to turn into significant action. Our creation of CMA (Climate Mindset Academy), a deployable, interactive, AI-powered platform that makes climate education approachable, interesting, and useful, was motivated by this.
Inspiration
The need to close the climate literacy gap served as the impetus for the project. Many of the resources currently available are either overly technical or superficial, depriving learners—particularly students and young professionals—of an organized method to link knowledge to action. We aimed to develop an educational experience that enables individuals to not only comprehend the data but also take action based on it.
How We Built It
1.First, we seeded the platform with carefully selected climate datasets (CO₂ emissions, anomalies in global temperature, etc.). 2.For data exploration, story-based learning, and action simulation, we created interactive Streamlit modules. 3.Based on user preferences, a recommendation model was trained to tailor climate-friendly behaviors. 4.In order to provide contextual content from climate knowledge sources, we integrated RAG (Retrieval-Augmented Generation). 5.Docker was used to containerize the system for simple cross-platform deployment.
What We Learned
- Data accuracy and user engagement must be carefully balanced when developing educational AI tools.
- Using Streamlit, we discovered how to link interactive user interface flows with machine learning models.
- We learned how to organize unstructured data for powerful storytelling by putting RAG pipelines into practice.
- The key to success was teamwork and coordinating technical design with educational psychology.
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