AI Concepts Integration in Developing E-Muhadathat Kits For Non-Arabic Speakers

Abstract

Recent educational reforms focus on strategically integrating technology into teaching, aligning with the principles of the fourth industrial revolution (IR 4.0). Among the swiftly evolving technologies in language learning is Artificial Intelligence (AI), particularly in the form of Natural Language Processing (NLP). This technology has been applied to create the E-Muhadathat kit, an interactive Arabic conversation simulation tool designed to enhance communication skills for non-Arabic speaking students in Malaysian public universities. This study aims to investigate the role of AI in education, address the challenges in developing AI-based Arabic language learning software, and propose a model for the E-Muhadathat kit tailored for non-Arabic speakers. This literature review uses documentary methods to gather information from journals, conference proceedings, articles, dissertations, and digital books from databases such as Google Scholar, Springer Link, Science Direct, and Research Gate. The collected data undergoes descriptive analysis based on thematic categorization. The findings indicate that the concept of AI consists of three core components: machine learning, deep learning, and neural networks. Arabic linguists have recognized several challenges in developing AI-based software, such as orthographic, morphological, syntactic, anaphoric, and semantic ambiguities. Moreover, the E-Muhadathat kit's design integrates machine learning and deep learning techniques, featuring applications for both spoken and written language. The study's findings support educators and researchers aiming to create Arabic language software tailored for non-native speakers in Malaysian higher education institutions. As a result, the study advocates for further investigation into the use of AI in Arabic language education to enhance the communication abilities of non-native speakers in Malaysia.