@article{machhout2024enhanced,
  title = {Enhanced BERT Approach to Score Arabic Essay’s Relevance to the Prompt},
  author = {Rim Aroua Machhout and Chiraz Ben Othmane Zribi},
  year = 2024,
  url = {https://ibimapublishing.com/articles/CIBIMA/2024/176992/},
  journal = {Communications of the IBIMA},
  volume = 2024,
  pages = 14,
  doi = 10.5171/2024.176992,
  abstract = {In recent years, automated essay scoring systems have seen significant progress, particularly with the integration of deep learning algorithms. This shift marks a move away from the traditional focus on style and grammar to a more in-depth analysis of text content. Despite these advancements, there remains a limited exploration of the essay's relevance to the prompts, especially in the context of the Arabic language. In response to this lack, we propose a novel approach for scoring the relevance between essays and prompts. Specifically, our aim is to assign a score reflecting the degree of adequacy of the student's long answer to the open-ended question. Our Arabic-language proposal builds upon AraBERT, the Arabic version of BERT, and enhanced with specially developed handcrafted features. On a positive note, our approach yielded promising results, showing a correlation rate of 0.88 with human scores.},
  keywords = {Automated Essay Scoring systems, Enhanced BERT with handcrafted features, Relevance to the prompt, Arabic language.},
  note = Article ID: 176992
}