AI for education: The digital transformation of a liberal arts institution – implementation at Lingnan University

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Authors: S. Joe Qin
Cited by: 2
References: 19

Abstract

The global landscape of higher education is undergoing a profound transformation driven by Generative Artificial Intelligence (GenAI) and pervasive digital technologies, particularly posing fundamental challenges to the traditional liberal arts education model grounded in holistic human development, broad intellectual inquiry, and student engagement. This position paper examines Lingnan University (Lingnan), Hong Kong’s longest-established institution of higher education, as a critical case of how a liberal arts university can strategically transform itself in the digital era without relinquishing its humanistic foundations. It analyzes Lingnan’s institutional transformation towards a “Research-Intensive Liberal Arts Institution in the Digital Era” across four interrelated dimensions: the upgrade of instructional practices through AI technology, the prioritization of irreplaceable human competencies, the systematic renewal of curricula, and the retention of ethical and cultural value systems. The analysis argues that AI for education revolution constitutes an intellectual transformation rather than a technocentric augmentation, positioning digital fluency as a core liberal arts competency through the democratization of GenAI access and the embedding of digital literacy across the Common Core. Simultaneously, a human-in-the-loop educational model is developed that foregrounds ethical reasoning, critical judgment, and social responsibility, offering a viable blueprint for harmonizing technological innovation with the enduring moral and intellectual aims of liberal arts education.

Fields of Study & Subjects

Digital Education and Society Innovative Teaching Methodologies in Social Sciences Artificial Intelligence Applications

Publication details

Journal / source
Computers and Education Artificial Intelligence
Publisher
Elsevier BV
Volume
10
Pages
100592–100592
Publication date
8 April 2026
Language
EN