The Effect of Artificial Intelligence Knowledge on the GPA of Statistics Students in Ankara - Muhammad Tegar Yudhoyono; Fatemeh Ali Hoseini; Zahid Zufar At Thaariq (International Journal of Learning and Education, 2026)
This study aims to analyze the effect of Artificial Intelligence (AI) and automation knowledge levels on the academic performance of statistics students in Ankara. This study employed a quantitative approach using secondary data from the dataset “AI Impact on Statistics Students in Ankara”, involving undergraduate statistics students from Ankara University, Gazi University, Middle East Technical University, and Hacettepe University. The independent variable in this study was AI and Automation Knowledge Level, while GPA Midpoint was used as the dependent variable. Data analysis was conducted using descriptive statistics and simple linear regression, followed by Spearman correlation and Kruskal-Wallis tests to strengthen the validity of the findings. The regression analysis produced the equation Ŷ = 2.715 − 0.042X with an R² value of 0.006 and a p-value of 0.285, indicating that AI knowledge level did not significantly affect students’ GPA. Additional statistical tests also showed consistent results that there was no significant relationship between AI knowledge and academic performance. The findings indicate that AI literacy alone is insufficient to predict academic achievement among statistics students. Nevertheless, AI literacy remains important in preparing students to adapt to technological transformation and future workforce demands. Therefore, higher education institutions are encouraged to integrate AI literacy, critical thinking, and ethical AI usage into learning systems and curriculum development.