Pixel International ConferencesPixel International ConferencesThis study investigates the structural validity of students’ digital skills by comparing eight competing measurement models, including Confirmatory Factor Analysis (CFA), Exploratory Structural Equation Modeling (ESEM), and bifactor-ESEM variants, using data from a sample of 603 university students. All models aimed to assess both critical and functional digital skills, providing a comprehensive evaluation of the multidimensional structure of digital competence. Model performance was evaluated using robust fit indices: χ², RMSEA, CFI, TLI, and SRMR. The Set bifactor-ESEM model demonstrated superior fit (χ² (368) = 729.47, RMSEA = .040 [90% CI: .036–.045], CFI = .994, TLI = .992, SRMR = .022), outperforming both traditional CFA and Full bifactor-ESEM models. Structural analysis revealed distinct behavioral patterns between the two skill domains: critical digital skills followed a unidimensional structure, dominated by the general factor, whereas functional digital skills exhibited a multidimensional configuration, with meaningful contributions from specific subdomains. Moreover, factor correlations from the Full ESEM model showed that most relationships between critical and functional skill factors were statistically non-significant (e.g., CIC–TO: r = .025, p = .894; CIC–INP: r = .067, p = .606), reinforcing their empirical distinctiveness. These findings suggest that digital skills are best conceptualized as a layered construct, comprising interrelated but structurally distinct domains. Implications for assessment design, educational interventions, and theoretical modeling are discussed.
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Keywords |
digital competence; yDSI; critical digital literacy; Set bifactor-ESEM; WLSMV; higher education |
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