Work

Research on University Teachers’ Perceptions of Gen‐AI From the Perspective of Actor‐Network Theory

Year: 2025

Type: article

Abstract: Employing the lens of Actor‐Network Theory (ANT), this paper explores university educators’ perceptions of Gen‐AI and its potential impact on education through a qualitative research approach. It focuses on how educators perceive generative AI technologies and how these technologies influence their teaching practices and role identification. The study reveals that multiple factors shape teachers’ acceptance and utilization of AI, encompassing personal attitudes, student responses, teaching environments, and institutional policies. The interaction between teachers and AI is conceptualized as part of a human‐machine interaction network, where AI transcends being merely a teaching tool and is attributed human‐like qualities such as a wise mentor and learning companion. This research underscores that the realization of human‐AI integration necessitates a synergistic development between educators and technology, coupled with the concerted efforts of other actors within the educational ecosystem. The paper concludes by discussing the implications and challenges of human‐AI integration for educational reform.

Source: Complexity

DOI: 10.1155/cplx/8885265

Authors: Yunlai Liu, Yuwei Zhang

Institution: Anqing Normal University

Language: English

Topic: Artificial Intelligence in Education

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: gold

Estimated APC paid: $2,760