WhatsApp-Based Language Data Collection for the SA-CDI
BScHons Computer Science · Stellenbosch University · Child Language Development Node
My Honours research project: replacing a mobile app with an accessible WhatsApp questionnaire so users can contribute without installing anything.
The SA-CDI project is gathering Communicative Development Inventory responses from caregivers across South Africa to establish early-language development norms in the country's official languages, with a target of roughly 20,000 responses. An earlier pilot used a Flutter app, but asking caregivers to install software created real barriers around data cost, device storage, and digital literacy. My project delivers the same questionnaire through WhatsApp, a platform most caregivers already use, with no installation at all.
I'm building the system in Python and Flask, using Twilio for WhatsApp messaging, Firebase for storage, and soon Azure neural text-to-speech wil be used so caregivers with lower literacy can hear each question read aloud. It runs in English, Afrikaans, and isiXhosa, persists session state server-side so a questionnaire can be paused and resumed across conversations, and pseudonymises participant data to stay POPIA-compliant. Alongside the engineering, the work is structured around three research questions: how the WhatsApp interface compares to the original app, which text-to-speech system serves each language best, and how the interface holds up under usability evaluation.
- Working button-based prototype in the Twilio sandbox, with a WhatsApp Flows version prepared for migration once a Business Account is approved.
- AgileUX co-design with linguists, fieldworkers, and caregivers throughout.
- Schema-compatible with the research team's existing Firebase pipeline, so responses drop straight into their analysis tools.