Design of an Arabic Learner Text Corpus for STAI Ma’arif Kendal Ngawi Students to Support Data Driven Learning Material Development

Desain Pengembangan Korpus Teks Pembelajar Bahasa Arab Mahasiswa STAI Ma’arif Kendal Ngawi dalam Mendukung Penyusunan Materi Pembelajaran Berbasis Data?Driven Learning

Abstract

This study discusses the design of an Arabic learner text corpus compiled from texts produced by students of STAI Ma’arif Kendal Ngawi, and its utilization in developing Data-Driven Learning (DDL) based teaching materials. The background of the research lies in the need for authentic teaching materials that address the actual difficulties faced by students in learning Arabic. The corpus was constructed from Arabic texts written by students (e.g., essays from the I’dadul Maw?d course) in a systematic way and enriched with metadata (author, topic, proficiency level, etc.). A qualitative-descriptive approach was employed. The results include the design of the learner corpus featuring concordance and word frequency analysis, as well as sample DDL concordance analyses to identify language patterns and common errors. The study also presents examples of DDL-based teaching materials derived from the corpus data, for instance tasks prompting students to analyze the usage of certain words or structures in authentic sentences. These corpus-based materials encourage learners to discover patterns independently (discovery learning) and improve their grasp of grammar and vocabulary. In conclusion, the developed learner corpus is beneficial in providing representative authentic Arabic language data, thus bridging the gap between teaching materials and students’ real needs, and strengthening the DDL-based learning approach.