A Framework to standardize assessment of the Kenyan Competency-Based Education Computer Science projects: a case of Competency-Based Education in Senior High School

Abstract

Computer science plays a central role in Kenya’s CBE curriculum, recognized as a key enabler of digital literacy, innovation, and future employability. Its inclusion reflects broader national education reforms aimed at equipping learners with 21st-century competencies aligned with Vision 2030 and the Digital Economy Blueprint. The transition to Kenya’s Competency-Based Education (CBE) marks a significant shift towards a learner-centered approach emphasizing practical skills and problem-solving. However, the absence of standardized assessment methods for computer science projects hinders consistent evaluation, leading to subjective grading and discrepancies in competency measurement. This study addresses this gap by developing a structured assessment framework tailored for CBE’s senior secondary level. A mixed-methods research design was employed to provide both depth and breadth—combining qualitative insights from stakeholders with quantitative data from case studies to comprehensively identify challenges in project evaluation. Specifically, responses were gathered from five educators and three curriculum developers, offering a targeted cross-section of assessment perspectives within the CBE context. The framework was developed based on competency-based grading rubrics, AI-assisted evaluation, and structured peer reviews. Findings reveal that structured assessment criteria significantly enhance grading consistency and transparency. Educators reported a 40% reduction in grading bias when using standardized rubrics. Additionally, AI-assisted grading improved efficiency, reducing assessment time by 50%. However, disparities in digital infrastructure and educator training remain key barriers to implementation. This research concludes that a hybrid assessment model—combining automated grading with human oversight—offers the most reliable approach for evaluating computer science projects in CBE. The study recommends policy integration of the proposed framework, alongside capacity building initiatives for educators to facilitate adoption. Future research should focus on optimizing AI-driven assessments while ensuring equitable access to assessment tools across diverse school environments.