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Towards a Supporting Framework for Neuro-Developmental Disorder: Considering Artificial Intelligence, Serious Games and Eye Tracking

Project Overview

The document outlines a framework that integrates generative AI, serious games, and eye-tracking technology to enhance educational outcomes for children with neurodevelopmental disorders (NDDs). By leveraging data analysis, the framework aims to provide teachers with valuable insights into student performance, facilitating personalized interventions tailored to individual needs. This approach not only improves teacher-student communication but also prioritizes data privacy, ensuring that sensitive information is protected. Key applications of this framework include the use of generative AI to create adaptive learning experiences that respond to the unique challenges faced by students with NDDs. The findings suggest that such technological advancements can significantly enhance engagement and learning effectiveness, ultimately leading to better educational outcomes for these students. The document underscores the potential of generative AI in education, particularly in supporting vulnerable populations through innovative, data-driven strategies that foster a more inclusive and effective learning environment.

Key Applications

Framework for using AI and eye-tracking in serious games to assess NDD children’s performance.

Context: Educational support for teachers working with children diagnosed with neurodevelopmental disorders.

Implementation: Data is collected through eye-tracking while children play serious games. Insights are generated for teachers to adapt educational strategies.

Outcomes: Improved understanding of student performance, enhanced personalized interventions, and better communication between teachers and psychologists.

Challenges: Ensuring data privacy and explainability of AI decisions.

Implementation Barriers

Technical

Challenges in processing and analyzing eye-tracking data effectively.

Proposed Solutions: Develop federated explainable AI models to enhance data handling and transparency.

Privacy

Concerns about the privacy of children's data during the learning process.

Proposed Solutions: Implement mechanisms for data privacy preservation in the learning framework.

Project Team

Abdul Rehman

Researcher

Ilona Heldal

Researcher

Diana Stilwell

Researcher

Jerry Chun-Wei Lin

Researcher

Contact Information

For information about the paper, please contact the authors.

Authors: Abdul Rehman, Ilona Heldal, Diana Stilwell, Jerry Chun-Wei Lin

Source Publication: View Original PaperLink opens in a new window

Project Contact: Dr. Jianhua Yang

LLM Model Version: gpt-4o-mini-2024-07-18

Analysis Provider: Openai

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