The Role of Attitudes, Skills, and Demographic Factors in Using Generative Artificial Intelligence for English Learning

Abstract

This study explores the role of attitudes, skills, and demographic factors in the use of Generative Artificial Intelligence (AI) for English language learning among students at MAN 3 Pekanbaru. Employing a quantitative survey design, data were collected through a structured questionnaire distributed to 417 students. The instrument consisted of 53 items measuring attitudes, skills, frequency of use, and demographic characteristics. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 4 to test measurement validity and structural relationships among variables. The findings revealed that both attitudes toward AI (β = 0.347, p < 0.001) and skills in using AI (β = 0.232, p < 0.001) had a significant positive effect on the frequency of AI use. Gender also significantly influenced frequency (β = -0.205, p < 0.001) and skills (β = -0.167, p = 0.001), indicating disparities between male and female students. Additionally, training experience had a significant impact on AI skills (β = 0.168, p < 0.001), and indirectly influenced frequency of use through skills (β = 0.039, p = 0.014). In contrast, age and grade did not show significant effects on the main constructs. Measurement results demonstrated good reliability and validity: all constructs showed Composite Reliability > 0.90 and Average Variance Extracted (AVE) > 0.60, with outer loadings > 0.70 for retained items. These findings suggest that fostering positive attitudes and improving students’ technical skills are key to enhancing the effective use of Generative AI in language learning. The study concludes that demographic factors like training and gender have notable influence, while age and grade play less significant role.