The Transformation of Arabic Language Assessment: A Systematic Literature Review of Technology-Enhanced Assessment (2021–2026)

Abstract

This study aims to analyze the development of Technology-Enhanced Assessment (TEA) in Arabic language learning from 2021 to 2026, particularly the shift from conventional evaluation to digital and AI-based assessment. This study employed a qualitative research approach using the Systematic Literature Review (SLR). A Systematic Literature Review (SLR) approach using the PRISMA framework to identify, screen, evaluate, and synthesize relevant studies obtained from Google Scholar, Garuda, and DOAJ databases. From 75 records identified through database searches, 11 studies satisfied the inclusion criteria and were thematically analyzed to examine trends, challenges, and implications of technology-enhanced assessment in Arabic language learning. The findings indicate that Arabic language assessment has undergone a significant shift toward more interactive, adaptive, and student-centered evaluation through the implementation of gamified, web-based, multimedia, authentic, and AI-supported assessment. Gamified assessment emerged as the dominant trend due to its effectiveness in increasing students’ motivation and participation. In contrast, AI-based assessment reflects the growing integration of intelligent technologies in educational evaluation. However, TEA implementation still faces challenges related to digital literacy, technological infrastructure, technical limitations, and the validity of AI-supported assessment systems. Therefore, integrating technology into Arabic language assessment requires pedagogical readiness, digital competence, and assessment literacy to support more meaningful, competency-oriented learning practices.