Evaluation Models and Digital Assessment Innovation in Arabic Language Learning: Towards Authentic and Competency-Based Evaluation

Abstract

This article explores contemporary approaches to evaluation in Arabic language learning, emphasizing authentic, digital, and competency-based assessment models. As language pedagogy evolves in the era of AI and hybrid education, the need for multidimensional evaluation that captures linguistic proficiency, communicative competence, and intercultural understanding becomes urgent. The study adopts a qualitative-descriptive method to analyze various evaluation models used in Arabic learning—diagnostic, formative, summative, and performance-based—while integrating digital innovations such as Moodle quizzes, e-portfolios, and AI-powered assessment tools. Data were gathered through observation, interviews with Arabic teachers, and analysis of institutional assessment frameworks at Universitas Negeri Malang. Findings indicate that digital-based authentic evaluation improves learner engagement and motivation, providing real-time feedback that supports individualized learning trajectories. However, the transition from traditional exams to competency-oriented assessment faces challenges in teacher digital literacy, rubric consistency, and linguistic standardization. The paper concludes by proposing a comprehensive framework of “Integrated Arabic Evaluation” (IAE) that combines digital, affective, and communicative dimensions aligned with the CEFR-Arabic proficiency standards.