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Perceived Contribution of General Education Curricula to the Sustainable Development Goals: A Four-Domain, Dual-Stakeholder Survey at the University of Ha’il

Sep 2026 · Sustainability · 0 citations

Abstract

This paper aimed to measure the perceived contribution of general education curricula to the Sustainable Development Goals at the University of Ha’il, Saudi Arabia, across four content-based domains: educational, social, environmental, and economic. Although higher education is increasingly recognized as a key setting for advancing Education for Sustainable Development, limited empirical evidence has examined how general education curricula contribute to sustainability across multiple content-based domains while simultaneously considering faculty and student perspectives. A cross-sectional, descriptive-analytical design was applied through a 40-item instrument, validated by an expert panel and administered to a stratified sample of 900 respondents (470 students and 430 faculty members) across eight colleges; overall reliability was high (Cronbach’s α = 0.968). Analyses comprised descriptive statistics, one-sample tests against the high-contribution benchmark, 95% confidence intervals, and a two-way analysis of variance with η2 effect sizes. Perceived contribution was high overall (M = 4.07), highest in the educational domain (M = 4.28, 95% CI [4.24, 4.32]) and lowest in the economic domain, the only domain within the moderate band (M = 3.49, 95% CI [3.45, 3.53]; t = −10.44, p < 0.001). Neither respondent type (η2 = 0.0002) nor college affiliation (η2 = 0.0046) produced significant differences. The findings support the value of a multi-domain and dual-stakeholder approach to evaluating sustainability contributions within general education curricula and identify the applied economic domain as a priority for curricular reinforcement in alignment with Saudi Vision 2030. The four domains represent a content-based classification of the sustainability areas examined and are not empirically confirmed as independent latent factors; confirmatory validation on an independent sample is the recommended next step.

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