Designing Annotation Guidelines for Trait-Based Arabic Automated Essay Scoring: A Systematic Methodology

Automated Essay Scoring (AES) fundamentally depends on high-quality annotated data, yet systematic approaches to developing annotation guidelines remain largely undocumented, especially for Arabic. We present a comprehensive methodology for trait-based Arabic AES annotation, applied to build a dataset of 7,859 essays by high school students annotated across seven writing traits, achieving substantial inter-annotator agreement (QWK: 0.66--0.75). Our methodology encompasses: (1) a seven-dimensional scoring framework grounded in Arabic linguistic and rhetorical conventions; (2) over 25 pages of Arabic-language guidelines with terminology unification, text-type-specific scoring descriptors, and annotated student examples; (3) a multi-stage training protocol that raised annotator agreement (QWK) from 0.58 to 0.71 before production began; and (4) quality assurance mechanisms, including dual annotation and supervisor adjudication. We release all materials publicly, providing both a validated foundation for Arabic AES research and a replicable template for annotation guideline development in other morphologically complex, under-resourced languages.