Imagine a smart filter for reading materials that automatically adjusts the difficulty of a text to match the reader's actual skill level. It works like a personalized tutor that ensures a worker isn't overwhelmed by complex manuals or bored by too-simple texts. This helps people who struggle with reading to learn new technical skills and feel more confident at work.
Low literacy adults struggle to acquire technical and scientific knowledge, making it hard for them to adapt to the evolving job market. This creates a gap in transversal skills and reduces overall employee productivity and well-being.
An intelligent reading system that evaluates text complexity and suggests materials based on the user's literacy level. It also includes tools for trainers to adapt texts for their students.
If you are an industrial plant operator dealing with workers who struggle to follow complex written safety manuals — this project developed an intelligent reading system that adapts text complexity to the user's level. This ensures instructions are understood, reducing errors and improving workplace safety.
If you are a vocational training provider dealing with adult learners who lack the reading skills to pass technical certifications — this project developed a tool for trainers to create or adapt texts with the appropriate complexity. This allows for faster skill acquisition and higher graduation rates.
If you are a recruitment agency dealing with candidates who have high technical potential but low literacy gaps — this project developed a system to monitor the link between literacy improvement and transversal skills. This helps in designing better onboarding paths to make workers more employable.
Based on available project data, the system is intended to be an open access system, though specific commercial pricing is not mentioned.
Yes, the project already involves partners from 4 countries (BE, ES, LU, PT) and focuses on Adult Learning and Vocational Educational Training contexts.
Based on available project data, the project aims to provide an open access system, but specific licensing agreements are not detailed.
The project uses ICT tools to evaluate text complexity and suggest materials, though specific API or integration protocols are not listed in the summary.
The project period runs from 2023-03-01 to 2026-02-28, indicating it is currently in the development and testing phase.
The consortium is heavily academic, with 4 universities and 2 research centers, but it maintains a practical edge with 1 industry partner and 2 SMEs. With a 12% industry ratio, the project is primarily research-driven but includes the necessary corporate and public administration perspectives to ensure the tool meets real-world vocational training needs.
Contact the Universidade Nova de Lisboa regarding the intelligent reading system's open access availability.
Contact SciTransfer to explore how to integrate this text-complexity AI into your corporate training pipeline.
