Natural Language Processing in Teaching Arabic Syntactic Analysis: A Systematic Literature Review of Its Strengths and Weaknesses in Indonesian

Abstract

This study is motivated by the increasing integration of Artificial Intelligence (AI), particularly Natural Language Processing (NLP), in Arabic language education, which has shifted traditional manual approaches to Arabic syntactic analysis (nahwu) and increased learners’ reliance on automated grammatical processing. The study aims to analyze the strengths and weaknesses of NLP in teaching Arabic syntactic analysis through a Systematic Literature Review (SLR) approach. A qualitative design was employed using the PRISMA 2020 framework, with data collected from scholarly articles published in SINTA-accredited journals between 2024 and 2026 related to NLP, Arabic syntax analysis, and grammar instruction. Data were analyzed using thematic analysis to identify patterns of strengths and limitations. The findings indicate that NLP provides significant advantages in enhancing syntactic analysis efficiency, accelerating grammatical structure identification, and delivering automated feedback in Arabic language learning. However, it also presents limitations, including reduced independent grammatical reasoning, increased dependency on AI systems, and weakened analytical thinking processes in nahwu learning. The study concludes that NLP should be positioned as a cognitive partner rather than a replacement for manual grammatical analysis, ensuring a balance between technological efficiency and the development of learners’ grammatical reasoning skills