Developing a multi-sectoral competency-based curriculum implementation framework for transformative education in Kenya: Evidence from Uasin Gishu County
Abstract
Competency-Based Curriculum (CBC) reforms have emerged as a central strategy for improving education systems by shifting instructional focus from content mastery to competency acquisition. Although Kenya has made considerable progress in implementing CBC, challenges related to teacher preparedness, pedagogical innovation, resource adequacy, and stakeholder collaboration continue to influence implementation outcomes. This study examined curriculum trends and teacher preparedness for transformative education using Uasin Gishu County as a microcosm of the Kenyan education system. The study sought to develop a Multi-Sectoral Competency-Based Curriculum Implementation Framework (MS-CBCIF) capable of informing collaborative curriculum implementation across Kenya. Constructivist Learning Theory and Social Constructivist Theory guided this research. An explanatory survey design was adopted involving 274 respondents comprising junior secondary school teachers, headteachers, Curriculum Support Officers, and Sub-County Directors of Education. Data were analysed using descriptive statistics, reliability analysis, Pearson correlation, and multiple regressions. The findings indicated positive relationships between emerging curriculum trends, teacher preparedness, pedagogical innovation, and transformative education, while implementation challenges negatively influenced curriculum effectiveness. Teacher preparedness emerged as the strongest predictor of transformative education. Based on these findings, the study proposes the MS-CBCIF, which integrates government agencies, curriculum developers, teacher education institutions, schools, communities, development partners, and the private sector into a coordinated implementation model. The framework demonstrates that successful CBC implementation requires sustained multi-sectoral collaboration rather than isolated institutional efforts. Although based on evidence, the framework provides a methodological model for future empirical validation using real-world data.