Get started
Work

AI knowledge readiness among university students: A cross-sectional quantitative study

Year: 2025
Type: article
Study design: Observational Study
Abstract: Artificial intelligence is now part of many ordinary routines, often in ways that people barely notice, and it has started to find its way into university work as well. For students, this means that some familiarity with AI is becoming less of an advantage and more of an expectation. Much of this comes down to knowing enough about AI to use it sensibly in their studies, or at least not feeling lost when it appears in academic tasks. In this study, that basic level of knowledge – enough to work with AI without relying on it blindly – is taken as the starting point for the study of AI readiness. The investigation centres on students in the English for Professionals programme, which is an applied-linguistics degree. The study looks at how prepared these students feel to handle AI in the course of their academic work. Using a cross-sectional design, 291 students from different academic years completed a structured questionnaire measuring four dimensions of AI readiness: cognition, ability, vision, and ethics. The results show that AI readiness generally increases with academic progression, with second- and third-year students reporting higher levels of ability, cognition, and vision. The ethics dimension, however, remains low across all groups. Gender differences were minimal. The findings indicate a need for earlier inclusion of AI-related material and a more sustained focus on AI ethics in the applied linguistics curriculum. More broadly, the programme requires considerable revision to incorporate computational linguistics and AI-related topics, ensuring that applied linguistics students leave with the level of preparation now expected in professional contexts where AI routinely plays a role.
DOI: 10.22363/2521-442x-2025-9-4-112-129
Authors: Luke Teoh, Manjet Kaur Mehar Singh, Jayanthi Muniandy
Language: English
Open Access status: diamond
OpenAlex ID: W7115064324
FWCI:
Cites:
Cited by:
Related to: