A platform that integrates a predictive model using machine learning to flag students at risk of dropping out of high school. Based on significant evidence supported by research, the model uses isolated inputs recognized as predictive markers for students dropping out and thus assigning a percentage of probability at which they are likely to drop out. More importantly, the platform provides a user-friendly interface that allows for the data to be easily visualized allowing for the school to identify students at risk of dropping out. The feature enables schools and parents to intervene prematurely to prevent such actions to occur.
We recognized a need to reduce drop out rates in high schools as there was a recognizable correlation between the dropouts and there negative impact on society and their respective communities.
An early intervention platform for potential high school dropouts.
The main challenge we faced was the absence of a data set that is required to be run through our predictive model. Another issue was protocol design, specifically getting the backend and frontend to communicate.
There a couple of things we hope to work on! For one; retrieving the proper dataset by partnering with schools, adding messaging hubs, a better user interface and data visualization on our platform.
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