Work

Psychological mechanisms of perceived technological dependence on generative artificial intelligence tools: perceived knowledge, trust, anxiety, and self-efficacy

Year: 2026

Type: article

Abstract: Generative AI tools are increasingly used in design education, yet the relationship between students' perceptions of these tools and their reported reliance on them remains unclear. This study analyzed cross-sectional survey responses from 526 undergraduate students in design-related disciplines using partial least squares structural equation modeling. In the specified model, perceived reliability, perceived usefulness, and perceived intelligence were positively associated with perceived AIGC knowledge, whereas perceived ease of use was not significantly associated with it. Perceived AIGC knowledge was positively associated with trust, self-efficacy, and usage intention and negatively associated with AIGC-related anxiety. Trust, AIGC-related anxiety, and self-efficacy each showed a significant indirect effect in the modeled relationship between perceived AIGC knowledge and usage intention. Usage intention was strongly associated with perceived technological dependence. These findings are consistent with the proposed framework, but the cross-sectional data do not establish the temporal sequence of the constructs or show that reported dependence reflects harmful overuse. The study extends technology acceptance research by examining perceived reliance in AIGC-supported creative work.

Source: Frontiers in Psychology

DOI: 10.3389/fpsyg.2026.1928967

Authors: Le Wei, Shu Zhang, Junghyun Heo

Institutions: Kookmin University, Anhui Institute of International Business, Anhui Vocational College of Press and Publishing

Language: English

Topic: Technology Adoption and User Behaviour

Subfield: Information Systems and Management

Field: Decision Sciences

Domain: Social Sciences

SDG: Quality education

Open Access status: gold

Estimated APC paid: $3,801