Artificial intelligence dependence in academic tasks: Design and validation of the SAID questionnaire

Abstract

Artificial intelligence (AI) is transforming the educational system by providing new learning opportunities; however, it also presents challenges such as teacher adaptation, the digital divide, data ethics, depersonalization, and technological dependence. This study addresses the need to assess AI dependence among secondary education students through the construction and validation of the SAID questionnaire. A mixed-methods approach with a sequential design was employed, applying the instrument to 370 students across eight educational institutions in Tacna, Peru. In the qualitative phase, the components of the construct were identified, while in the quantitative phase, the psychometric properties of the questionnaire were evaluated. Exploratory factor analysis and confirmatory factor analysis, along with reliability testing, demonstrated that the SAID questionnaire is a valid and reliable tool. It captured three key dimensions: “informative exclusivity with AI,” “trust in AI,” and “AI literacy.” The questionnaire provides robust empirical evidence of an emerging construct that, based on students’ perceptions, enables the assessment of AI dependence in academic settings. It serves as a valuable resource for exploring long-term implications and developing educational strategies to mitigate the negative effects of AI. The conscious and critical integration of AI in education is essential to ensure that these technologies function as supportive tools rather than substitutes for independent learning.