An epistemic-institutional artificial intelligence literacy framework for university educators
TL;DR
A five-dimensional AI literacy framework -including instrumental, algorithmic, ethical, epistemological, and institutional dimensions- is proposed herein, which suggests that university educators must be capable of critically reviewing AI results, defending academic integrity, and working within a clear governance structure.
Abstract
The rapid introduction of artificial intelligence (AI) into higher education is transforming the nature and shape of academic knowledge production. This theoretical paper proposes an AI literacy framework for university educators that extends beyond instrumental skills, incorporating epistemic, ethical and institutional facets. A narrative and selective literature review approach was conducted based on peer-review and policy-oriented literature between 2017 and 2025 in indexed academic repositories. The analysis process was based on an epistemic deconstruction of the existing efforts to frame AI literacy, complemented by thematic, gap, and theoretical reconstruction. The review found that existing frameworks focus on technical use and, to a lesser extent, ethical considerations; they rarely discuss the epistemic status of AI-generated outputs or the need for institutions governance. In response, a five-dimensional AI literacy framework -including instrumental, algorithmic, ethical, epistemological, and institutional dimensions- is proposed herein. This framework is founded on three areas of knowledge: technological, philosophical, and institutional. The framework suggests that university educators must be capable of critically reviewing AI results, defending academic integrity, and working within a clear governance structure. This work opens avenues for future empirical and longitudinal studies.