Artificial intelligence and academic performance in early childhood education: A correlational study in a technological institute in Ecuador.

Abstract

The expansion of artificial intelligence (AI) tools is modifying study and assessment, but their relationship with academic performance depends on the context and teacher mediation. This study aimed to determine the relationship between the frequency of AI use and academic performance in fifth-semester Early Childhood Education students at a technological institute in Ecuador. A quantitative, correlational, and cross-sectional approach was applied. The population consisted of 70 students, and the analysis was conducted with 60 due to absences and incomplete forms. AI use was measured using a Likert scale, and performance was estimated using the recoded grade point average; Pearson's correlation was used. The results showed moderate adoption (73.3% use 1–5 applications; 50% use it 3–5 times per week), 95% attendance, and a predominance of "good" performance (65%). A high and positive correlation was found between AI use and performance (r = 0.81). It is concluded that when AI is integrated as support and accompanied by academic guidance, it can be associated with better performance indicators; therefore, guidelines for ethical use, AI literacy, and evaluative monitoring are recommended.