Artificial intelligence and autonomous learning among Secondary School students

Abstract

The incorporation of artificial intelligence tools into school environments has changed how students search for information, solve questions, complete academic activities, and organize study processes. This study aimed to determine the relationship between artificial intelligence use and autonomous learning among secondary school students at an educational institution in 2026. The study followed a basic quantitative approach with a correlational scope, non-experimental design, and cross-sectional data collection. The accessible population consisted of 87 students in the fourth and fifth years of secondary education, aged 15, 16, and 17 years, all of whom were included through a census. Data were collected using two structured five-point Likert questionnaires. The questionnaires underwent content validation by three experts and were piloted with 20 similar students; Cronbach’s alpha was 0.820 for artificial intelligence use and 0.960 for autonomous learning. Spearman’s rho was used for inferential analysis at a 0.05 significance level. The results showed a predominance of high levels of artificial intelligence use (57.5%) and autonomous learning (59.8%). A positive and statistically significant correlation was identified between the variables (rho = 0.731; p < 0.001). Significant associations were also observed with learning planning (rho = 0.642), learning strategies (rho = 0.708), and self-regulation and self-evaluation (rho = 0.681). Higher scores in academic AI use, learning support, and critical and responsible use were associated with higher autonomous learning scores. Given the correlational and non-experimental design, these findings do not establish causality.