Request Correction
Use this form to request corrections to the paper metadata. Select the fields that need correction and provide the correct information.
Correction Guidelines
- Click the edit button next to a field to report a correction.
- Fill in the suggested correction value for each field you want to correct.
- Provide your name and email so we can contact you if needed.
Paper Information
DARES: Dataset for Arabic Readability Estimation of School Materials
Paper Fields
Click the edit button next to a field to report a correction.
DARES: Dataset for Arabic Readability Estimation of School Materials
This research introduces DARES, a dataset for assessing the readability of Arabic text in Saudi school materials. DARES compromise of 13335 instances from textbooks used in 2021 and contains two subtasks; (a) Coarse-grained readability assessment where the text is classified into different educational levels such as primary and secondary. (b) Fine-grained readability assessment where the text is classified into individual grades.. We fine-tuned five transformer models that support Arabic and found that CAMeLBERTmix performed the best in all input settings. Evaluation results showed high performance for the coarse-grained readability assessment task, achieving a weighted F1 score of 0.91 and a macro F1 score of 0.79. The fine-grained task achieved a weighted F1 score of 0.68 and a macro F1 score of 0.55. These findings demonstrate the potential of our approach for advancing Arabic text readability assessment in education, with implications for future innovations in the field.
Authors
Expand an author to correct their information. Use the remove button to request author removal, or add a new author.
PDF Attachment
You may attach a PDF as a corrected version of the paper. Max file size: 10MB. Only PDF files are accepted.
Your Information
Author Declaration *
Select at least one field to correct using the edit buttons above.