IMPROVING STUDENT LEARNING THROUGH AI: A CASE STUDY ON DIGITAL LEARNING PLATFORMS

Students are greatly affected by the latest technological advances. Artificial intelligence, also called AI, is one of the most popular modern innovations. The purpose of this study is to use statistics to examine how Artificial Intelligence (AI) affects student learning. A total of 29 participants who were all Uinsu students participated in the quantitative analysis. Regression modeling, correlation analysis, and descriptive statistics were used to investigate the relationship between AI and student learning. The results obtained were with a significance level of 0.000, the simultaneous test results showed a calculated F value of 1.325. This indicates a fairly large simultaneous influence between the Artificial Intelligence variable (X) and the student learning variable (Y). If the partial test results show a calculated t value (4.738) greater than the t table (2.052), then Ha is accepted and H0 is rejected. Student learning (Y) is significantly influenced by Artificial Intelligence (X) and the R-Square test, which produces an R2 value of 0.811, Artificial Intelligence (X) has an influence of 81.1% on Student Learning (Y), while other elements not covered in this study have an influence of 19.9%. Regardless of the research findings, it is important to understand the benefits and drawbacks of artificial intelligence. If implemented correctly, artificial intelligence (AI) has the potential to be a useful tool to improve student learning outcomes and quality.