Page 648 - AI for Good Innovate for Impact

AI for Good Innovate for Impact

support. This AI solution helps level the playing field by offering dynamic assistance and equal
access to digital education tools.

Furthermore, it monitors cognitive overload, emotional fatigue, and stress. The system
recommends supportive interventions such as mindfulness breaks or slower pacing to prevent
burnout, anxiety, or learning fatigue. By focusing not only on academic progress but also on
mental health, the project promotes a holistic approach to student development.

2�3 Future Work

1. Data Collection & Expansion

The project will involve collecting diverse, ethically sourced multimodal data from neurodivergent
learners. This includes facial expression cues, eye movement patterns, engagement signals,
and behavioral interactions across various educational settings. All data collection efforts will
prioritize informed consent, privacy, and student well-being.

2. Proof of Concept Development

A minimum viable prototype will be developed to demonstrate real-time emotional assessment
and dynamic content adaptation. Initial deployments will take place in collaboration with
special education institutions to validate responsiveness and accuracy in real-world classroom
environments.

3. Model Development

Pre-trained AI models for sentiment analysis, attention tracking, and adaptive content generation
will be fine-tuned using neurodivergent-focused datasets. Retrieval-Augmented Generation
(RAG) will be incorporated to align content with curriculum standards and personalized learning
contexts.

4. Variations and Extensions

Planned future extensions of the system include:

• Dashboards for educators to track collective emotional and cognitive trends
• Integration with assistive or wearable technologies
• Embedded mindfulness tools (e.g., breathing cues, calming visuals, adaptive audio)
tailored for sensory-sensitive learners

5. Standards Development

Efforts will be made to contribute to emerging global standards on AI in neurodivergent
education. This includes aligning with ITU’s architectural frameworks (such as Y.3172), and
promoting fairness, transparency, and responsible emotional data usage.

6. Reference Tools and Simulation Environments

Interactive simulation environments will be developed to allow researchers, educators, and
developers to test adaptive learning flows, emotional response models, and feedback loops
under controlled experimental conditions. These tools will be open source to encourage
community collaboration and iterative improvement.

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