Student Dropout Risk Prediction

This is a proactive tool under design to identify and support at-risk students at Hogeschool Utrecht. Leveraging predictive analytics on enrollment data, the tool aims to detect potential dropouts early in their academic journey. This allows for timely interventions that are tailored to individual needs, enhancing student success and promoting equity in educational outcomes. Privacy and Data Access:

• Coordination with the privacy officers to ensure compliance with privacy regulations.
• Use of anonymized or aggregated data to protect student privacy.

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