Building the AWS-Based Remote Research Platform that Kept the University of Chicago's Child Development Studies Running Through COVID
The TMW Center's in-person research programs for early childhood development could not run during COVID. Ideas2IT built a cloud-native AWS platform so researchers could schedule, deliver, and track remote parent sessions with the same fidelity as an on-site lab, with video conferencing, real-time content sync, attendance logging, and goal tracking built in.
Client
TMW Center for Early Learning
Industry
Education
Service
Cloud
Engagement
Complete
01 Challenge
The TMW Center's New Born, Well Baby, and Let's Talk programs ran in-person. Researchers observed sessions, collected attendance, and administered surveys from a lab. When COVID suspended in-person access, the data collection model it depended on stopped entirely.
02 Solution
Ideas2IT built a cloud-native research platform on AWS where hosts schedule and run sessions remotely, slides sync in real time through a Contentful integration, video and chat run through Twilio, attendance is logged automatically on participant join, and goals and surveys are collected mid-session without breaking the session flow.
03 Outcome
The TMW Center's three research programs moved to fully remote delivery. Researchers retained attendance logging, goal tracking, and survey collection with no degradation to session fidelity.
Phase 01
Remote session delivery: real-time slide sync, Twilio video, and role-based host controls
The first constraint the platform had to satisfy was parity with in-person delivery. A remote research session is not equivalent to an in-person one unless slides advance in real time, host controls are precise, and attendance is captured automatically.
Ideas2IT built the session layer on that requirement. Contentful powers content delivery, pulling slides into the platform and synchronising them so every participant sees exactly what the host is presenting.
Twilio provisions video and chat, with host-level controls to mute or remove participants and a co-host handoff for multi-facilitator sessions. Attendance is logged automatically on participant join. Goals from prior sessions surface mid-session alongside current surveys, keeping longitudinal tracking intact across the program.
This Phase Produced
Remote session delivery platform AWS-hosted, built for research-grade fidelity Contentful CMS integration Real-time slide sync across host and participant views Twilio video + chat integration In-session video conferencing with host moderation controls Role-based session controls Host and co-host ownership, participant mute and removal Automated attendance logging Triggered on participant join, without researcher manual entry Mid-session goal and survey collection Longitudinal data capture within the active session flow
Phase 02
AWS infrastructure and compliance layer: secure data handling, IRB-aligned logging, and scalable cloud architecture
The infrastructure layer ran on AWS EKS, with PostgreSQL as the primary data store and S3 handling media and recording storage.
Logstash captured platform events for monitoring and audit purposes. The architecture served both mobile and web clients over HTTPS, with IoT device support built into the connection model for research contexts where participants join from non-standard endpoints.
EKS Monitor handled container-level observability across the deployment.
This Phase Produced
AWS EKS deployment Container orchestration for the session and API services PostgreSQL data store Primary relational store for session, participant, and program data S3 storage layer Media, recording, and content asset storage Logstash event pipeline Platform monitoring and audit event capture EKS Monitor observability Container-level health and performance monitoring Multi-client architecture Web and mobile clients, HTTPS transport, IoT endpoint support
The Outcome
What the University of Chicago's research team gained when in-person access closed and the platform held
The TMW Center's three research programs continued without discontinuity because the platform matched in-person session fidelity: real-time content sync, automated attendance, and mid-session survey capture preserved the longitudinal data structure the research depended on. The AWS architecture gave the research team a cloud-native infrastructure that scales with program enrollment rather than with lab availability.