Developing ai assistive technology in african eanguages for neurodivergent children: enhancing learning and social engagement in rwanda
1
Children digital mental health, Evidence matter, kigali, Rwanda
Popul. Med. 2026;8(Supplement Supplement 1):
ABSTRACT
ABSTRACT:
Title: Developing AI Assistive Technology in African Languages for Neurodivergent Children: Enhancing Learning and Social Engagement in Rwanda
BACKGROUND:
Neurodivergent children, including those with autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD), face challenges in communication, learning, and social interaction. In low- and middle-income countries (LMICs) like Rwanda, access to interventions is limited, and most existing assistive technologies are not available in African languages, creating barriers to effective use. AI-driven tools adapted to local languages have the potential to provide personalized, culturally relevant support and improve developmental outcomes.
OBJECTIVE:
This project aims to design and pilot an AI-based assistive technology operating in African languages that supports learning, communication, and social engagement for neurodivergent children, focusing on usability, acceptability, and scalability in LMIC educational settings.
METHODS:
A prototype AI application was developed integrating machine learning-based adaptive learning modules, speech recognition, and gamified social exercises in local African languages. A pilot study involved 20 neurodivergent children aged 6–12 years in Rwanda. Outcomes included engagement metrics, task completion rates, and structured feedback from caregivers and educators. Ethical approval and informed consent were obtained.
RESULTS:
Preliminary findings show that children using the AI tool in African languages demonstrated improved engagement, task completion, and social interaction compared to baseline measures. Caregivers and educators reported increased attention, responsiveness, and motivation. The technology was well-received and is considered potentially scalable for school and home use across African settings.
CONCLUSIONS:
AI assistive technology in African languages offers a feasible, impactful, and culturally relevant solution for neurodivergent children in LMICs. This project highlights the importance of locally adapted innovations in global mental health and education, and underscores the potential for international collaboration to expand access to effective, language-appropriate interventions. Keywords: AI assistive technology, African languages, neurodivergent children, autism, ADHD, low- and middle-income countries, personalized learning, social engagement
Title: Developing AI Assistive Technology in African Languages for Neurodivergent Children: Enhancing Learning and Social Engagement in Rwanda
BACKGROUND:
Neurodivergent children, including those with autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD), face challenges in communication, learning, and social interaction. In low- and middle-income countries (LMICs) like Rwanda, access to interventions is limited, and most existing assistive technologies are not available in African languages, creating barriers to effective use. AI-driven tools adapted to local languages have the potential to provide personalized, culturally relevant support and improve developmental outcomes.
OBJECTIVE:
This project aims to design and pilot an AI-based assistive technology operating in African languages that supports learning, communication, and social engagement for neurodivergent children, focusing on usability, acceptability, and scalability in LMIC educational settings.
METHODS:
A prototype AI application was developed integrating machine learning-based adaptive learning modules, speech recognition, and gamified social exercises in local African languages. A pilot study involved 20 neurodivergent children aged 6–12 years in Rwanda. Outcomes included engagement metrics, task completion rates, and structured feedback from caregivers and educators. Ethical approval and informed consent were obtained.
RESULTS:
Preliminary findings show that children using the AI tool in African languages demonstrated improved engagement, task completion, and social interaction compared to baseline measures. Caregivers and educators reported increased attention, responsiveness, and motivation. The technology was well-received and is considered potentially scalable for school and home use across African settings.
CONCLUSIONS:
AI assistive technology in African languages offers a feasible, impactful, and culturally relevant solution for neurodivergent children in LMICs. This project highlights the importance of locally adapted innovations in global mental health and education, and underscores the potential for international collaboration to expand access to effective, language-appropriate interventions. Keywords: AI assistive technology, African languages, neurodivergent children, autism, ADHD, low- and middle-income countries, personalized learning, social engagement
| eISSN: | 2654-1459 |
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