AI ASSISTED RUBRIC ASSESSMENT FOR BASIC ARABIC LINGUISTICS LEARNING
Keywords:
Artificial Intelligence, Rubric Assessment, Arabic Linguistics, Muqaddimah Ilm Al-Lughah, EvaluationAbstract
This article discusses AI-assisted rubric assessment in Muqaddimah Ilm al-Lughah learning as a strategy to improve the objectivity, transparency, and depth of evaluation in introductory Arabic linguistics. The study is motivated by the frequent use of conventional evaluation that assesses final answers without providing sufficient criteria for linguistic reasoning. Using a qualitative descriptive method based on literature review and conceptual analysis, this study examines how artificial intelligence can support rubric-based assessment for tasks related to phonological classification, morphological analysis, syntactic description, and semantic interpretation. The findings show that AI-assisted rubrics can help lecturers formulate clearer performance indicators, provide structured feedback, and identify patterns of student errors. AI can also support the analysis of student responses by highlighting incomplete explanations, inconsistent terminology, and weak argumentation. Nevertheless, the role of lecturers remains essential in validating AI-generated feedback and ensuring that assessment reflects pedagogical and ethical considerations. The study concludes that AI-assisted rubric assessment can strengthen evaluation practices in Muqaddimah Ilm al-Lughah when it is used as an academic assistant rather than as an autonomous judge.
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Copyright (c) 2026 Feby Angelina Putri, Ainur Rofiq Sofa, Muhammad Ichsan (Author)

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