Ek Time
School timetable management looks like a static matrix optimization problem on paper. In reality, it is a high-stress, early-morning human crisis fueled by administrative oversight and unvoiced teacher burnout. Standard management tools try to automate the static weekly grid, completely missing the daily emotional and operational friction of sudden absences and manual substitution scrambling.
Before You Read
This project was developed as part of a 3-week Interaction Design course at IDC, IIT Bombay under Prof. Anirudha Joshi. Because of its research-first academic nature, this case study intentionally frontloads the field visits, contextual inquiry, and problem discovery over pure visual polish.
In a hurry? Jump straight to the built solution & system architecture - here.
Security features that prevent 200,000+ users from falling into crypto scams every month.
Shipped core trader features that increased Day 10 retention by 17%.
Design-led discovery features that increased usage frequency by 80%.
TL;DR
- Why Contextual Inquiry Saved Us: Preliminary surveys failed because teachers couldn’t criticize administration or voice operational breakdowns due to workplace caution. Sitting beside them at 7:30 AM revealed a hidden, accepted workload—teachers taking unfair proxy loads out of institutional obligation while coordinators panicked over 1-meter wall charts .
- The Core Pivot: We realized static timetable generation wasn’t the daily crisis—the 7:30 AM proxy scramble was. We pivoted from a complex grid generator to an emergency substitution engine.
- What We Built: A web app for coordinators, a teacher mobile app, and a zero-install WhatsApp bot for instant, 1-tap proxy acceptance.
Everything seemed to be running like a well-oiled machine.
Our brief began with a clear objective: automate the weekly timetable grid. We started with 4 preliminary call interviews across teaching and administrative staff. The responses were clean, procedural, and completely devoid of operational breakdowns.
The data was tidy and useless. Staff were understandably cautious about discussing internal friction or administrative strain with external researchers.
“The coordinator builds the master grid, updates are shared via WhatsApp, and teachers cover free periods as assigned. Everything is running pretty well” - a school teacher
To cut through this surface-level narrative, we shifted to Contextual Inquiry using a Master–Apprentice approach.
Contextual Inquiry is a very interesting Qualitative Research Methodology where researchers observe and interview users in their natural environment as they perform tasks. By watching them work in real time, you see full context, uncover hidden workarounds, and build genuine empathy.
We conducted interviews across 3 site visits, covering 18 total participants: 12 subject teachers, 3 coordinators, 2 principals, and 1 extra-curricular teacher. Sitting alongside them and positioning ourselves as newly joined staff learning their daily routine allowed staff to walk us through their morning naturally (Master-Apprentice).
Being on the ground changes everything
You can’t fix a broken system from a distance. By immersing ourselves in their actual workspace, we uncovered a web of invisible dependencies and daily workarounds that phone calls never revealed.
The Master Timetable
In the principal’s office, there was a one meter long timetable which had info on all the classes, periods and assigned faculties.
This is created during a meeting conducted at the start of every academic year by the principal, senior faculties and the timetable incharge.
Updating this timetable in the middle of an academic year, whenever there is a transfer, was a hassle.
Subjective Substitution Management
Each morning, the coordinator manually tracked teacher absences in a physical logbook to assign proxy coverage.
However, the system was prone to friction and bias, often derailed by pushback from resistant faculty or blatant favoritism in duty assignments.
The Crosscheck Bottleneck
Proxy allocation depended on a massive, one-meter-long physical master sheet laid out in the principal’s office.
Under intense morning time pressure, coordinators had to manually cross-reference absent teachers with available free periods to scramble for coverage.
Legacy Software Held Together by Fear
Despite computers being in staff rooms for over two decades, coordinators still relied on an ancient, legacy desktop scheduling software running on a single Windows 7 machine.
The school intentionally refused OS updates or system upgrades out of panic that modern software wouldn’t support the legacy tool..
We have retained the similar visual language of the legacy software in our final solution.
“I don’t care if the semester grid takes two hours to generate once a year. I care that I have 10 minutes at 7:30 AM to find someone to cover 7th-grade math so 40 kids aren’t left unsupervised.”
Strategic Pivots: Turning 18 Data Points Into Design Decisions
We compiled raw field observations into an Excel sheet, synthesizing 18 interpreted user data points into Flow, Physical, and Artifact models. This bottom-up affinity mapping forced us to kill early concepts.
Time table creation wasn't the main issue
Going through the data made us realize that in multiple schools, the issue is not in creating a timetable. As its a one time process. The main issue was in everyday proxy allocation, which is a manual 1 hour labour at 7 AM everyday.
We edited our research objective from “Creating a timetable” to “Solving the proxy allocation problem”.
Creating Our Two Different User Personas
From our contextual inquiries and research synthesis, we established two primary user archetypes representing the opposing sides of the proxy allocation dynamic:
- Senior Timetable Coordinator: Under extreme 10-minute morning time pressure to find available subs without creating chaos or missing class coverage.
- Subject Teacher: Absorbs unrecorded substitution duties during free periods, balancing daily lesson prep with sudden administrative assignments.
We Built Ek-Time: A Real-Time Workload-Aware Substitution Engine
Instead of forcing a single bloated desktop tool onto staff who are always on the move, we built a three-part ecosystem designed around how school staff actually communicate:
- Web App (For Coordinators): A desktop dashboard for setting up master timetable rules, reviewing leave requests, and dispatching proxy assignments .
- Mobile App (For Teachers): A daily schedule viewer where teachers track their timetable, view incoming substitution requests, and submit leave applications .
- WhatsApp Bot (Low-Barrier Interaction Edge): A secondary chatbot interface that routes proxy notifications directly to teachers’ WhatsApp, allowing 1-tap accept/reject responses without forcing them to open or download the app .
Master Grid Generation (Web App)
Before handling daily proxy allocations, coordinators need to establish the school's annual scheduling framework.
School Configuration
On first launch, coordinators define base parameters—number of periods, duration, and break times.
This determines the timetable structure the algorithm must respect for all subsequent operations.
Data Ingestion & Workload Mapping
Coordinators upload or scan class/subject data, assign teaching loads, and flag class teachers.
Workload mapping
Coordinators set custom logic (e.g., maximum subject periods per week, subject spacing).
Updating Teacher’s list and the classes they teach
Teachers teaching what subjects in which all classes are updated.
Adding special rules, constraints or preferences a school might have
Different schools have different styles of time table. Some focuses on STEM, where as some focuses on PT and extracurriculars.
Here, the coordinator could select from existing rules or add new rules.
Finally generating a Master Timetable, which is editable
Using all the previous data, a master time-table will be generated, which can be cross-checked by coordinators before sharing.
Human-in-the-Loop Proxy Allocation
Machine lacks accountability. We do need a human in the loop, especially when dealing with problems like this.
Leave Requests
When a teacher applies for leave via the app, it appears on the coordinator’s web dashboard.
We intentionally chose not to auto-approve leave requests. Leave decisions depend on interpersonal nuances and school context, so the algorithm only triggers after a coordinator manually approves the leave.
Equity-Based Candidate Scoring
Once approved, the routing engine scans free periods and prioritizes teachers who have taken fewer recent substitutions, capping proxy stacking on the same individuals.
Coordinators review algorithmic recommendations, make tweaks if necessary, and dispatch the assignment.
Zero-Friction Acceptance & Accountability
Dual Dispatch
The assigned proxy request hits the teacher’s mobile app and WhatsApp bot simultaneously.
Teachers accept or reject the duty directly from WhatsApp or the app.
Reasoning Requirement
When a teacher rejects a proxy assignment, they must select a reason (e.g., clashing duty, medical, personal).
The system logs this for reporting and uses it to refine future candidate scoring.
What Field Testing Taught Us About Software Assumptions
We conducted user testing using a think-aloud protocol with teaching and administrative staff. Navigating prototype scenarios exposed key edge cases:
- Half-Day & Floating Periods: Updated schedule matrix from full-day toggles to period-level availability slots.
- Administrative Oversight: Kept human-in-the-loop candidate recommendations rather than auto-assigning leave.
- Notification Fatigue: Separated emergency proxy alerts to high-priority WhatsApp messages while keeping routine schedule updates in app.
Key Impact Takeaways
- Contextual Inquiry Over Surveys: Direct observation in the user’s actual environment revealed unvoiced operational panic and informal workarounds that standard surveys missed completely.
- Meet Users in Their Existing Ecosystem: Leveraging WhatsApp as an interaction edge allowed non-tech-savvy staff to accept proxy requests instantly without forcing mandatory app adoption.
- Design for Equity, Not Just Optimization: Operational efficiency must be balanced with workload fairness to reduce stress and prevent unvoiced teacher burnout.
This project was part of a 3-week course led by Prof. Anirudha Joshi at IDC, IIT Bombay, alongside teammates Tanushree Pillai, Puru Vats, Kshitij Ghag, and Vipin Surendran. Case study structure based on research documentation by Puru Vats and Kshitij Ghag.