Artificial Intelligence in English Language Learning: Student Perspectives on AI Literacy, Academic Integrity, and Dependency at Universidad Tecnológica de Tijuana

Resumen

The increasing use of generative artificial intelligence (GenAI) in higher education has created new opportunities for English language learning while also raising concerns regarding academic integrity, student dependency, AI literacy, and institutional regulation. This study aims to analyze university students’ perceptions of these four dimensions in the context of English language learning at a technological university in Mexico. A quantitative, non-experimental, cross-sectional, and correlational research design was employed. Data were collected from 214 university students through a 16-item questionnaire organized into four constructs: Academic Integrity, AI Literacy, AI Dependency, and Institutional Regulation. Descriptive statistics, Cronbach’s alpha, Pearson’s correlation coefficient, and Kruskal–Wallis tests were used to analyze the data. The results showed relatively high levels of AI Literacy (M = 3.77, SD = 0.88) and Academic Integrity (M = 3.61, SD = 0.86), whereas AI Dependency obtained a lower mean (M = 2.61, SD = 0.78). AI Literacy was positively correlated with Academic Integrity (r = .684, p < .001), while Academic Integrity and AI Literacy were also positively associated with Institutional Regulation. AI Dependency showed weak negative correlations with Academic Integrity and AI Literacy. Significant differences according to frequency of AI use were found for AI Dependency and Institutional Regulation, but not for Academic Integrity or AI Literacy. The findings suggest that responsible AI integration in English language education requires more than regulating access to technology; it also requires developing students’ AI literacy, maintaining academic integrity, and promoting learner autonomy through clear institutional guidance.