Developing a Critical Inquiry-Based E-Educational Model (CIEM) to Enhance Critical Thinking Skills among High School Students: A Mixed-Methods Study in the Libyan Context (Al-Farooq Journal of Sciences, 2026)
Background: Despite institutional drives toward digitalization, a persistent gap separates the availability of technological resources from their pedagogically purposeful deployment in Libyan secondary schools. Didactic transmission methods continue to dominate instruction, compounded by intermittent infrastructural instability.Objective: This study develops, validates, and empirically tests the Critical Inquiry-based E-Educational Model (CIEM) — a novel, low-bandwidth-optimized instructional framework designed to systematically enhance critical thinking skills among secondary school students.Methodology: An explanatory sequential mixed-methods design (QUAN → qual) was employed with 240 secondary-school students across four Tripoli schools. Quantitative data were analyzed using ANCOVA and Structural Equation Modeling (SEM) via AMOS 26; qualitative data underwent reflexive thematic analysis guided by Lincoln and Guba's (1985) trustworthiness criteria.Results: ANCOVA revealed a statistically significant group effect (F(1, 237) = 22.45, p < .001, Partial η² = .086, Cohen's d = 0.85). SEM confirmed a fully mediated pathway: CIEM significantly enhanced cognitive engagement (β = .54, p < .001), which in turn predicted critical thinking gains (β = .61, p < .001). Bootstrapped indirect effect: β = .33, 95% CI [.24, .42]. Power analysis (GPower 3.1; f = 0.25, α = .05, power = .95) confirmed the sample of n = 240 was adequate. Qualitative themes illuminated 'productive cognitive friction' as the primary mechanism of change.Conclusion: CIEM offers a validated, context-sensitive pedagogical framework establishing that structured asynchronous inquiry — rather than technology per se — drives critical thinking development in resource-constrained settings.
Keywords: Critical Thinking; E-Educational Model; Critical Inquiry; Structural Equation Modeling; Mixed-Methods; Libya; Asynchronous Learning; Community of Inquiry