Beyond Utility: Ai Competence as a Professional Signal in Digital Education
Year: 2026
Type: article
Abstract: Most educational technology research explains AI adoption through utilitarian variables such as performance expectancy and effort expectancy. However, this study explores an overlooked dimension: the symbolic and signaling value of AI competence. Through qualitative interviews with 12 educators in Uzbekistan, we investigate how teachers perceive AI use as a signal of professional modernity, competence, and institutional quality. Drawing on Signaling Theory (Spence, 1973), we find that teachers adopt AI tools not only for pedagogical efficiency but also to signal their readiness for digital transformation to students, peers, and administrators. This signaling effect enhances teacher credibility and student engagement, but it also introduces risks of "signal noise"—superficial adoption in which tools are displayed but not meaningfully integrated. The findings suggest that perceived usefulness and ease of use are supplemented by a third mechanism: "perceived signaling value." We propose the Signaling-Adoption Model (SAM), in which AI competence generates performance outcomes indirectly through both utilitarian utility and professional signaling, provided the signal is authentic and observable. The study contributes to TAM literature by introducing a sociocultural layer to technology adoption and offers practical insights into how teachers can strategically leverage AI to enhance their professional identity without falling into performative usage.
Author: Norbaeva, Shakhnoza
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W7212245891
FWCI:
Cites:
Cited by:
Related to: