

NDA
ABOUT
ROLE
Product Designer
PLATFORM
Mobile Application | Web Application
DURATION
16 Weeks
SCOPE
Product Design
PROJECT TIMELINE
Interviewing faculties revealed that students showed signs before they dropped off.
Faculties interacted with students to make them stop by dropping off
Priya - Senior Faculty Member
5 batches • 100+ students
Rahul — The Batch Admin
Manages 500+ students across batches
Drop outs are calculated by ratio of class attendance and test performances.
No Early Warning System
Attendance data lived in spreadsheets. There was no automated flag for declining engagement patterns. Teachers relied entirely on memory.
Reactive, Not Proactive
Follow-ups happened after the drop-out, not before. By the time admin noticed dipping ratings or batch absences, the student had already mentally checked out.
Desktop-Only Tools for Mobile Teachers
Follow-ups happened after the drop-out, not before. By the time admin noticed dipping ratings or batch absences, the student had already mentally checked out.
We sorted information in 3 categories according to prioritisation. This helped in creating the wireframe
Primary information
• Student test performance
Student attendance
Student left out probability
Student details
Engagement reports
Primary information
• Student test performance
Student attendance
Student left out probability
Student details
Engagement reports
Secondary information
• Student name | image
Class | batch
Basic details
Quick links
STRUCTURE
After closely examining the digital interactions and apps used by educators , we defined a structure and reading pattern for the product
KEY FEATURE 1
0 Layer Design,
The dashboard surfaces the right signal to the right person giving teachers a fast mobile view and admins a rich desktop overview, all anchored to the same live risk data.

KEY FEATURE 2
Real time student insights visible
at a glance
All faculties and admin have access to all of student attendance, mark sheets at a glance. faculties can look at LOP of students. The focus shifts from taking actions at the last moment to taking action at the begining.

KEY FEATURE 3
Leveraging AI
to reduce churn
AI scans through all student profile and suggests students with hight probability of churn to the faculties and admin. Faculties can furthermore consolidate student profiles and know exactly what issue the students are facing.

REFLECTION AND NEXT STEPS














