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DataKind's Student Success Tool (SST)

Customized and easily actionable insights for data-assisted advising, at no cost

Data-assisted advising helps advisors use their limited time to more efficiently identify and reach out to those most in need of help. Using the Student Success Tool to implement data-assisted advising, John Jay College has reported a 32% increase in senior graduation rates in two years via their CUSP program. Based on the success of this implementation, DataKind is supported by Google.org to develop this solution with additional postsecondary institutions, at no institutional cost. This repo is where the google.org fellows team will collaborate with DataKind to develop and ultimately share the open source components of the tool.

DataKind's Product Principles

  • Transparent: Our features and models will be openly shared with the institution, so you can know exactly what variables are leading to identifying those student most at risk of non graduation. Our end-to-end tool code will be openly shared in this github repo.
  • Dedicated to bias reduction: We use bias-reducing techniques and regularly review our implementations for fairness and equity.
  • Humans in the loop by design: Our interventions are designed to be additive to the student experience, and all algorithms are implemented through human actors (advisors).

Contributing

Please read the CONTRIBUTING to learn how to contribute to the tool development.

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