Preventing Student Dropouts with IDA | No-Code Predictive Analytics for Higher Ed

The Problem

Student dropouts were on the rise. University administrators urgently needed a way to identify at-risk students quickly and accurately—before it was too late.

Roadblocks

While administrators had theories about why students were leaving, they lacked a scientific, timely method to confirm these insights. Despite having access to a wealth of student data—attendance, grades, employment status, tuition payment history, and more—they couldn’t act fast enough to intervene effectively.

Why IDA

IDA (Intuitive Data Analytics) turned this overwhelming data into actionable insight. With its human-driven, no-code analytics platform, IDA empowered administrators to harness advanced tools like correlation analysis, predictive modeling, and random forest algorithms—without needing a data scientist or IT specialist. By generating real-time risk scores, IDA made it possible to spot students in danger of dropping out—fast.

What Sets IDA Apart

The true innovation lies in how IDA puts control directly into the hands of decision-makers. Through its dynamic data playground, administrators could

IDA enabled them to visualize and interact with live data, adjust models on the fly, and develop tailored intervention strategies with confidence and clarity.

IDA eliminates dependency on external departments by making complex analysis accessible, intuitive, and immediate—bridging the gap between data and human insight.

The Results

With IDA, universities discovered the real reasons behind student attrition—often contrary to their original beliefs. More importantly, they were able to proactively identify and support at-risk students, enabling administrators and counselors to deliver personalized, timely interventions that made a measurable difference.

The Problem

Roadblocks

Why IDA

What Sets IDA Apart

The Results

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