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Digital Transformation Governance, Stakeholders’ Change Readiness, and Administrative Support in Public Junior High Schools in the Division of Manila: Basis for a Proposed Contextualized Enrichment Program

2026 · International journal of research and innovation in social science · 0 citations

Abstract

Digital transformation in schools requires more than access to technology; it depends on coherent governance, stakeholder readiness, and responsive institutional support. This study examined digital transformation governance, stakeholders’ change readiness, and administrative support in public junior high schools in the Division of Manila. A quantitative descriptive–comparative–correlational design involved 584 education personnel comprising 30 supervisors, 92 school administrators, 317 teachers, and 145 non-teaching personnel. Digital transformation governance was rated Evident overall (WM = 3.85), stakeholders’ change readiness was Observed (WM = 3.88), and administrative support was Supported (WM = 3.91). Retained aggregate-level ANOVA outputs indicated significant respondent-group differences across all governance dimensions (η² = .340–.369) and all readiness dimensions (η² = .319–.534). Tukey–Kramer comparisons showed that the most recurrent perception gaps involved supervisors and teachers or non-teaching personnel. An exploratory multiple regression based on 18 analytic observations showed that the five administrative-support dimensions did not significantly predict digital transformation governance, R² = .157, adjusted R² = −.194, F(5, 12) = 0.447, p = .807. Implementation challenges were Highly Encountered (WM = 4.26), particularly those related to stakeholder readiness. The proposed Contextualized Enrichment Program was rated Suitable (WM = 4.04), Acceptable (WM = 3.95), and Feasible (WM = 3.90). The findings support a carefully monitored pilot of context-responsive digital governance and capacity-building interventions; inferential estimates should be interpreted cautiously because the retained ANOVA and regression outputs were based on aggregate and small-sample analyses.

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