Bridging the Gap: Investigating Students' Self-Reported AI-Literacy and Perceived Employability Competencies for an AI-Enabled Workforce

Document Type

Article

Source of Publication

Journal of Computer Assisted Learning

Publication Date

10-1-2026

Abstract

Background: The integration of artificial intelligence (AI) into the global economy requires higher education institutions to equip graduates with AI literacy. However, there is limited empirical research on the relationship between AI literacy and employability, particularly within the rapidly transforming context of the Middle East and Gulf regions. Objectives: This study aimed to: (1) assess the self-reported AI literacy and perceived employability competencies of university students in the Middle East and Gulf regions; (2) examine the associations between specific dimensions of self-reported AI literacy and perceived employability; and (3) investigate whether students' attitudes and mindsets were statistically involved in theoretically ordered indirect associations between their self-reported AI literacy and perceived employability outcomes. Methods: A quantitative, cross-sectional survey was conducted with 380 university students recruited via the Prolific platform. In the final analytic file, country of residence was retained only as two pooled codes: the Middle East (n = 284; 74.7%) and the Gulf regions (n = 96; 25.3%). Following within-sample refinement, the instrument retained four dimensions of self-reported AI literacy and eight composites of perceived employability competencies. Data were analysed using hierarchical multiple regression and Partial Least Squares Structural Equation Modelling (PLS-SEM). Results: Mean levels of self-reported AI literacy and perceived employability competencies were high. The full regression model, including five background controls, accounted for 60.8% of the variance in overall perceived employability readiness (the four self-reported AI-literacy dimensions contributed an increment of 55.4 percentage points; ΔR2 = 0.554), with the ‘Analyze & Evaluate’ dimension showing the strongest standardised association. Attitudes & Mindsets composite was statistically involved in significant, theoretically ordered indirect associations between two self-reported AI-literacy dimensions (Understand & Knowledge; Use & Application/Create & Innovate) and all eight perceived employability outcomes. In the regression models, ‘Analyse & Evaluate’ was associated with both outcomes, overall perceived employability readiness and perceived career readiness. All reported outcomes are students' self-assessments; they do not represent objectively demonstrated AI competence, employer-rated competencies, actual employment outcomes, or temporal and causal order. Conclusions: In this cross-sectional sample, all four self-reported AI-related dimensions were positively associated with perceived employability readiness; attitudes and mindsets were statistically involved in indirect association patterns for two of the three antecedent dimensions. However, the observed association between critical thinking and the analytical and evaluative dimensions of AI literacy does not demonstrate that a direct pedagogical focus develops critical thinking. The findings provide a bounded rationale for further evaluating how AI-literacy learning opportunities may be designed and assessed in comparable settings.

ISSN

0266-4909

Publisher

Wiley

Volume

42

Issue

5

Disciplines

Education

Keywords

AI attitudes, AI-enabled workforce, career readiness, perceived employability competencies, self-reported AI literacy

Scopus ID

105049639806

Indexed in Scopus

yes

Open Access

yes

Open Access Type

Bronze: This publication is openly available on the publisher’s website but without an open license

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