Cargando...
Influence of Self-Efficacy in the Use of Artificial Intelligence (AI) and Anxiety Toward AI Use on AI Dependence Among Peruvian University Students
Author(s)
Flores-Paredes, Alcides
Universidad Nacional del Altiplano
Pascual-Mariño, Jai
Date Issued
12 de enero de 2025
Type
Article
Volume
4
Series/Report No.
Data & Metadata
Start Page
210
End Page
210
ISSN
2953-4917
Abstract
Background: The advancement of artificial intelligence (AI) in education has transformed the way students interact with technological tools, creating new challenges related to self-efficacy, anxiety, and AI dependence. Self-efficacy refers to one's confidence in their ability to use AI, while AI-related anxiety pertains to the fear or concern when interacting with these systems. These variables can influence technological dependence, affecting academic performance and emotional well-being. Objective: This study aims to examine the influence of self-efficacy in AI use and anxiety toward AI on AI dependence among Peruvian university students. Methods: A descriptive cross-sectional study was conducted with 528 Peruvian university students aged 18 to 37 years (M = 19.00, SD = 3.84). Scales were used to measure AI self-efficacy, anxiety toward AI, and AI dependence. Correlation and multiple regression analyses were applied to identify predictors of technological dependence. Results: The results showed that AI self-efficacy was positively correlated with AI anxiety (r = 0.43, p < .01) and AI dependence (r = 0.61, p < .01). Anxiety also significantly correlated with AI dependence (r = 0.71, p < .01). Multiple regression analysis revealed that both AI anxiety (β = 1.131, p < .001) and AI self-efficacy (β = 0.610, p < .001) predicted AI dependence. Additionally, business administration students exhibited greater dependence compared to students from other fields (β = 1.025, p < .05). Conclusions: Students with higher self-efficacy in AI use tend to utilize AI more frequently but also experience greater anxiety and dependence on AI. Educational interventions should focus on reducing AI-related anxiety to prevent excessive dependence, especially among students.