Objectif
Eye-tracking and AI for Enhanced Teaching (EYE-TEACH)
Recent education assessments (PIRLS, PISA) show a significant decline in reading comprehension amongst students in many European countries. The EYE-TEACH project is an initiative integrating artificial intelligence (AI) and eye-tracking (ET) that aims to transform educational practices and empower European teachers with new pedagogical skills for assessing and supporting their students' reading comprehension. The project addresses issues such as the post-COVID-19 educational challenges, mounting teacher workload and teacher shortages across Europe.
Eye tracking, although not without limitations, has proven its worth in educational research, offering insights into students' reading behaviours, cognitive load, and emotional engagement. It differentiates between various levels of reader comprehension, making it a valuable tool for personalised education. Complex eye-tracking data translated into intelligible output by AI and supported by a robust ethical and data privacy framework can provide teachers with actionable insights, aiding the selection of effective pedagogical strategies.
EYE-TEACH reaches beyond the state of the art by involving teachers and education practitioners early in the development process. By mapping educators' acceptance and readiness to adopt such novel technologies and highlighting the role of perceived ease of use and usefulness, the project has real potential to transform educational practices. The final joint result of the project will be a comprehensive resource of training materials and guidelines for using and implementing this technology in education, including benefit and risk assessments, and considerations of privacy and ethics issues.
By empowering teachers with an AI-assisted ET-analytics tool and training materials, the project aims to contribute positively to the future of education in Europe.
Champ scientifique (EuroSciVoc)
CORDIS classe les projets avec EuroSciVoc, une taxonomie multilingue des domaines scientifiques, grâce à un processus semi-automatique basé sur des techniques TLN.
CORDIS classe les projets avec EuroSciVoc, une taxonomie multilingue des domaines scientifiques, grâce à un processus semi-automatique basé sur des techniques TLN.
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HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinateur
20014 Turku
Finlande