Developing Frequency-Based and Thematically Aligned Arabic Learner Vocabulary Resources - Adam Gargani

This project focuses on enhancing Arabic language learning through the development of data-driven vocabulary and grammar resources.

The initial phase involves generating frequency counts for a manually curated list of around 62 000 Arabic words and phrases using a comprehensive corpus, such as arWaC. The list will be analysed to identify any missing lemmas, and the resulting data will be organized by frequency and aligned using the SketchEngine "wordlist" tool.

Subsequent stages will involve aligning the vocabulary list with existing thematic vocabularies, particularly those structured according to CEFR levels in Arabic and other languages. In parallel, the project includes the comprehensive morphological glossing of vocabulary to support the creation of learner-oriented materials.

The project also involves collaboration with departmental colleagues on the development and publication of learner vocabulary lists and grammar learning tools, especially focused on morphology. Discussions are underway with the AIMES group to explore co-authored reference materials tailored to specific subject domains such as religion, education, and law.