From Technical Enablement to Deep Learning: The Paradigm Shift and Mechanism Examination of University Faculty Professional Development in the Digital-AI Era

Abstract

The deep integration of digital-AI technologies is reshaping the forms and logic of higher education teaching. However, university faculty professional development faces the limitations of the “technical enablement” paradigm, leading to a cycle of “technological anxiety–performative innovation–meaning depletion.” Based on sociocultural theory, expansive learning theory, and teacher identity theory, this paper constructs a “technology-cognition-identity” co-evolution theoretical framework. It proposes a new paradigm centered on “teacher deep learning,” operationalized into three dimensions: critical technological cognition, reflective practice iteration, and identity reconstruction. Accordingly, the article puts forward strategic recommendations targeting multiple stakeholders, including the state, universities, faculty development centers, and enterprises, aiming to propel teachers from “being empowered” to “self-empowerment,” and to achieve the synergistic development of educational wisdom and professional autonomy in the digital-AI era.