Firda Hariyanti, I. Ketut Budayasa, Rini Setianingsih
Statistical literacy has become a crucial skill in the data-driven digital era. However, significant challenges remain in enhancing a deep understanding of statistical concepts. This study systematically reviews the role of Artificial Intelligence (AI) in improving statistical literacy in statistics education. Employing a Systematic Literature Review (SLR) approach, the study follows three stages: planning, implementation, and reporting. A total of 11 main articles were selected from 173 relevant articles retrieved from the Scopus database. The analysis categorizes the AI tools used, the aspects of statistical literacy enhanced, the research methods employed, the instruments utilized, and the impact on statistics learning. The findings reveal that AI contributes to three key aspects of statistical literacy: (1) conceptual understanding, facilitated by generative language models (ChatGPT) and machine learning-based simulation tools; (2) data analysis and computational skills, enhanced through platforms such as Jupyter Notebook, CODAP, and AI-based statistical visualization applications; and (3) critical thinking and problem-solving, developed through predictive model evaluation and AI-driven data interpretation. Additionally, AI positively influences engagement and collaborative learning, particularly through interactive learning analytics-based instruction. From a methodological perspective, most studies adopt a qualitative approach (55%), followed by quantitative methods (45%), employing research instruments such as eye tracking, learning analytics analysis, and pre-post surveys. The primary respondents include university students, high school students, educators, and statistics professionals. While AI demonstrates significant potential in improving statistical literacy, challenges such as algorithmic bias, curriculum integration limitations, and ethical concerns in AI implementation require further investigation. Therefore, this study recommends developing more adaptive, moral, and effective AI-based learning strategies to strengthen statistical literacy across various educational levels and professional environments. © 2025, Malque Publishing. All rights reserved.
Universitas Negeri Surabaya, Faculty of Mathematics and Natural Sciences, Indonesia; Universitas Nahdlatul Ulama Pasuruan, Department of Mathematics Education, Indonesia
