Abstract: The global transition towards Competency-Based Education (CBE) demands deep organizational reconfiguration and localized administrative stewardship to resolve systemic implementation bottlenecks. This study investigated the institutional readiness and pedagogical execution fidelity of junior secondary school mid-level executives navigating the rollout of the Basic Education Curriculum Framework (BECF) within Nandi North Sub-County, Kenya. Using Weiss’s Theory of Change and descriptive correlational research design, the study sampled 305 institutional administrators. Data were collectedvia role-customized closed-ended questionnaires. Analysis utilized descriptive metrics, Pearson’s product-moment correlation, and One-way Analysis of Variance (ANOVA) revealed that while conceptual awareness of CBE tenets is widely distributed (M = 3.41), practical readiness for execution remains deficient across both senior managers (M = 2.46) and departmental heads (M = 2.67). ANOVA models demonstrated absolute uniformity in structural preparedness across the administrative hierarchy, failing to establish role-based variance, F(1.430) < F(3.084), p = 0.2439. Pearson models confirmed a statistically significant, moderately strong positive correlation among Heads of Departments (r = 0.557, p = 0.035), supporting a systemic “learning by doing” phenomenon, whereas senior managers displayed a statistically non-significant linkage (r = 0.448, p = 0.167). The inquiry reveals a sharp dissociation between national curriculum directives and school-level operational capacity, characterized by chronic shortages of standardized assessment matrices and broken intra-institutional communication pathways. The study recommends system-wide continuous in-service retooling, the rapid deployment of standardized assessment templates by the Kenya Institute of Curriculum Development (KICD).

Abstract: The integration of machine learning–based personalized learning systems in secondary education offers significant potential to enhance instructional differentiation, learner monitoring, and academic support. However, adoption depends not only on technological capability but also on institutional readiness across infrastructure, human capacity, and leadership dimensions. This study evaluated institutional readiness and barriers to implementing ML-based personalized learning in secondary schools in Rwanda using a mixed-methods design. Data were collected from 200 institutional staff members across ten secondary schools representing all five provinces. Findings indicate moderate but uneven readiness. Infrastructure indicators show that 55% of schools reported functional ICT laboratories, yet only 42% reported reliable internet connectivity and 36% adequate technical maintenance support. Human capacity gaps were pronounced: while 84% of respondents rated staff digital literacy as high or moderate, only 18% reported high understanding of ML concepts and 22% expressed high confidence in using AI tools. Governance readiness was limited, with 61% reporting data protection policies but only 29% indicating the presence of an institutional AI or digital strategy, and 63% lacking regular data quality audits. Leadership openness to innovation was relatively strong (52%), yet only 33% reported strong ICT budget allocation. The most significant barriers identified were limited technical expertise (64%), insufficient funding (58%), and data privacy concerns (52%), whereas resistance to change was lower (29%). The study concludes that ML-based personalization adoption is constrained primarily by structural capacity and governance gaps rather than institutional resistance, highlighting the need for coordinated readiness strengthening across schools.