Develop Automated Child Reading Assessment & Intervention Tool
| Project Title | Development of Automated Child Reading Assessment and Intervention Tool |
|---|---|
| Project Timeline | 2020 - Ongoing |
| Researchers | Dr Saeed Afshar, Dr Ying Xu, Associate Professor Mark Antoniou, Professor André van Schaik |
| Partners/Collaborators | Neurabuild, Stellenbosch University |
Project Synopsis
This project seeks to use machine learning to create automated systems that assess children's reading skills and provide personalised intervention strategies in real-time. The goal is to develop a free system that accurately evaluates reading abilities, offers tailored feedback, and improves reading skills for children with different accents, dialects, and non-English languages, including those facing unique challenges in speech patterns. By sharing this advanced technology with partners in developing nations, particularly in Asia and Africa, the project aims to empower vulnerable children and help them achieve their full potential.
Project Details
The ability to read is the cornerstone of self-sufficiency and progress in life. Poor literacy is a silent affliction that limits job options, results in poorer health, increased risk of imprisonment, and a shorter, harsher life.
The project aims to leverage machine learning for the development of automated systems that assess children's reading skills and provide tailored intervention strategies in real-time. Together with researchers across Australia we are developing a free system that can accurately assess reading abilities, offer personalised feedback, and enhance reading skills of children across different accents, dialects, and non-English languages, even in the face of unique challenges presented by the speech patterns of young learners.
By making our state of the art machine learning systems freely available to partners in developing nations in Asia and Africa we are leveraging leading edge technology to assist the most vulnerable children realise their full potential.
