aspg-27-4383-1792228713 20261017091833 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group International Journal of Artificial Intelligence and Education Technology IJAIET 2835-2432 2026 5 1 Sanjar Raximjonov Department of Computer Science, Central Asian University, Tashkent, Uzbekistan Eugene Q. Castro Department of Computer Science, Central Asian University, Tashkent, Uzbekistan This paper presents a Systematic Literature Review (SLR) of AI-powered automated short-answer grading, with a particular focus on low-resource languages such as Uzbek. The review follows the PRISMA 2020 guidelines to ensure transparency and methodological rigor. Relevant peer-reviewed studies published between 2018 and 2025 were systematically identified, screened, and analyzed across multiple academic databases. In total, 33 studies were included in the final synthesis. The reviewed literature indicates that transformer-based models, including mBERT and XLM-R, generally achieve stronger performance than traditional machine learning approaches, while recent large language models show potential in few-shot and zero-shot grading scenarios. The findings also highlight that the limited availability of teacher-annotated datasets remains a major challenge for developing reliable automated grading systems in low-resource educational contexts. 2026 37 42 4383 https://creativecommons.org/licenses/by/4.0/ 10.54216/IJAIET.050104 https://americaspg.com/journal/27/article/4383 https://americaspg.com/storage/articles/manuscripts/01KT7X63NY1Y52R8NMCG86PN73.pdf