Associations of metacognition, self-directed learning ability, and AI literacy with academic achievement among university students predominantly enrolled in health-related majors: a cross-sectional study
Abstract
The expanding integration of digital technologies and artificial intelligence (AI) in higher education has heightened the need to identify learner competencies associated with academic achievement. This study examined the associations of metacognition, self-directed learning ability, and AI literacy with self-reported academic achievement among university students in the Republic of Korea. A descriptive cross-sectional survey was conducted with 175 undergraduates from 11 universities between September 30 and November 1, 2025; 78.3% were enrolled in health-related majors. Metacognition, self-directed learning ability, and AI literacy were measured using the SMI, SDLI, and MAILS, respectively; academic achievement was measured as self-reported cumulative GPA on a 4.5-point scale. Data were analyzed using descriptive statistics, group comparisons, Pearson correlations, and hierarchical multiple regression with HC3 heteroscedasticity-robust standard errors. GPA differed by age, school life satisfaction, and AI-related course experience in unadjusted comparisons. Metacognition (r = .348, p < .001) and self-directed learning ability (r = .377, p < .001) were positively correlated with GPA, whereas AI literacy was not (r = .105, p = .167). In the adjusted six-predictor model, age ( β = .151, p = .023), AI-related course experience ( β = .145, p = .040), and self-directed learning ability ( β = .329, p = .023) were independently associated with GPA; metacognition and AI literacy were not. The model explained 20.0% of the variance (adjusted R 2 = .171). These findings identify self-directed learning ability as the only examined learner competency that remained significantly associated with GPA after adjustment. Longitudinal and intervention studies are needed before causal or mediational conclusions can be drawn.
