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Teach Assist.

Focus Area

Quality Preschool Programmes

Innovation Lever

Existing product or service

Stage

Feasibility

Status

Open

Executive Summary.

Teach Assist uses existing smartphone technology and leverages established ‘selfie culture’ behaviour to make preschool attendance tracking easy and fun. Simply using photos to track class attendance, dates and location.

The Problem.

Accurately tracking class attendance in South Africa is notoriously difficult- largely due to the paper-based systems being time-consuming, challenging to consistently track and unreliable. The data from the paper forms become largely inaccessible and near impossible to share, analyse and audit at scale. 

With close to 2.5 million children between the ages of 3 and 5 signed up for a form of group-based early care and education programmes, it’s imperative that we receive accurate attendance data to inform decision making around funding, attendance incentives and programme changes.

The Innovation.

Teach Assist is a mobile app that leverages both ‘selfie culture’ behaviour and AI facial recognition technology to provide instant, transparent and reliable attendance data of the number of children attending classes of early learning programmes across South Africa. 

The class data is synced to a live dashboard allowing for simple mass monitoring and auditing that’s accurate and trustworthy. This data can then be used to determine what factors need to be changed to ensure better educational and developmental outcomes for children. 

For example, if programme attendance is high but the children are still not developmentally on track we know the programme needs improvement. If attendance is low the reason why will need to be investigated and potential funding solutions or attendance incentives will need to be implemented.   

The app has been developed and piloted in partnership with SnapChat and teachers in under-resourced communities to create a robust minimal viable product. 

How it works
  1. At the start of the year, the teacher enters the number of children who are registered to attend their class into the app via their mobile phone.
  2. Each day, teachers take group photos of their class and indicates the number of children in attendance.
  3. The class location, duration and number of children in attendance are stored by the app until the teacher has access to data or an open wifi network. From there the data is stored on the live system. 
  4. Facial recognition software verifies the attendance information provided by the teacher by identifying the number of faces in the image and confirming the total amount of children in attendance. This ensures reliable, transparent and honest attendance data that can’t be altered. 

Testing is currently underway to develop facial recognition software that can verify and tag each individual child based on recognising their face in the class photograph to track specific attendance data per child. 

The live dashboard provides a digital record of class attendance and location with photo-based evidence. Backend managers can easily track and sort class data from any location to further improve accuracy and transparency.

Why we invested.

Transparent, accessible, longitudinal attendance data will be hugely valuable for multiple stakeholders from government and funders to the development sector.  It will enable assessing programme quality, monitoring and evaluation and allocating any funding or incentives for attendance (e.g. a subsidy, a meal voucher).

Teachers will also now have the longitudinal data to pick up patterns of attendance and drop off and be able to implement changes and incentives to avoid this. It will also enable accurate attendance data for teachers to feedback to parents consistently which has been proven to increase attendance over time. 

The Project Team

Tim Conibear is an Ashoka Fellow and founder of the award-winning organisation Waves for Change, as well as the International Surf Therapy Organisation and the Action Impact Network. Al organisations are focused on improving the evidence base for the use of physical activity to improve mental health outcomes.

Matthew Mattila has over a decade working in business strategy and innovation, having spent time working for some of the world’s largest NGO’s, business consulting firms and brands. He is currently the COO of Waves for Change and Chairman of the International Surf Therapy Organization.

Kavan Seggie is the founder of SnapChat and has over two decades of business experience from grassroots startups to global brands. He acts as a mentor and tech advisor to the Teach Assist team as they further develop their tech solution and plan for scale worldwide.