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Objective

To detect risk of Learning disabilities and related mental health issues in school children.

Approach

Machine Learning(ML) and Computer Vision(CV) based analysis of a 2 minute video of the child interacting with the teacher.

https://youtube.com/shorts/xgOV5ISa9Po?feature=share

Scope of Impact

The Indian Journal of Psychological Medicine estimates that Specific Learning Disorders (SLD) affect about 8% of Indian children, impacting nearly 14 million students.

Many such children are misunderstood as lazy, disobedient or careless.

This further leads to stigma, emotional distress and academic struggles.

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Current Assessment Efforts

Organization Tool Assessment Method Administered By
National Institute of Mental Health and Neurosciences (NIMHANS) Specific Learning Disability (SLD) Battery Clinical Assessment Clinical Psychologists, Special Educators
National Institute for the Empowerment of Persons with Intellectual Disabilities (NIEPID) 1. Grade Level Assessment Device (GLAD)
  1. Indian Test of Intelligence | Paper-based | Special Educators, Teachers | | National Brain Research Centre (NBRC) | Dyslexia Assessment for Languages of India (DALI) | Paper-based | Special Educators, Teachers | | Central Institute of Educational Technology (CIET-NCERT) | PRASHAST (Pre-Assessment Holistic Screening Tool) | Digital | Teachers (Phase 1), Special Educators (Phase 2) | | Department of Empowerment of Persons with Disabilities (DEPwD) | Screening tool for SLD

Limitations

Clinical assessments have scalability challenges in rural areas, while paper-based tests may not fully capture learning disabilities. Digital platforms offer broader reach but require infrastructure and technical training for effective implementation.

Overcoming Limitations

  1. The proposed ML-CV solution is a non-invasive method, it minimizes stress for both students and teachers, making the screening process more comfortable and natural.