AI Technology: Natural Language Processing; Generative Language Modeling.
This project proposes a new methodology to develop Automatic Essay Scoring (AES) systems for the Basque low-resource language.
The methodology relies on a pair of interacting components: an 'expert model' that generates detailed essay evaluations, and a 'judge model' that filters these assessments to retain only pedagogically valuable feedback.
The approach leverages the self-taught paradigm, requiring minimal pedagogical annotations, and aims to address the unequal treatment of languages in existing AES systems through transferable methodologies.
The study's performance analysis will be grounded in a series of four experiments, each looking at different aspects of the proposed system.
The intended outcomes include robust, pedagogically aligned AES models, as well as a sound methodology that can be transferred to other low-resource languages in Europe.
Principal Investigator, Institution and Country
Aitor Soroa, University of the Basque Country - EHU, Spain