ReaderBench Learns Dutch: Building a Comprehensive Automated Essay Scoring System for Dutch Language

Automated Essay Scoring has gained a wider applicability and usage with the integration of advanced Natural Language Processing techniques which enabled in-depth analyses of discourse in order capture the specificities of written texts. In this paper, we introduce a novel Automatic Essay Scoring method for Dutch language, built within the Readerbench framework, which encompasses a wide range of textual complexity indices, as well as an automated segmentation approach. Our method was evaluated on a corpus of 173 technical reports automatically split into sections and subsections, thus forming a hierarchical structure on which textual complexity indices were subsequently applied. The stepwise regression model explained 30.5% of the variance in students’ scores, while a Discriminant Function Analysis predicted with substantial accuracy (75.1%) whether they are high or low performance students.