A Model for the Effective Adoption and Integration of Precision Agriculture in the Secondary School Agriculture Curriculum: Evidence from Kisii and Nyamira Counties, Kenya

Abstract

Precision Agriculture (PA) is a data-driven approach that enhances efficiency, productivity, and sustainability in agriculture, but its integration into secondary school curricula remains limited, particularly in developing countries. This study developed an empirically grounded model for the adoption and integration of PA into Competency-Based Education (CBE) in secondary schools in Kisii and Nyamira Counties, Kenya. The model was developed from information on teachers' preparedness, the influence of resources and infrastructure on PA implementation, and barriers to effective PA implementation. A concurrent mixed-methods design was employed, involving 353 agriculture teachers and 254 principals. Questionnaires, interview guides, and observation checklists were used to collect data on the aspects that underpinned this model. Quantitative data were analyzed using correlation and multiple regression analyses, while qualitative data were analyzed thematically. Hierarchical Multiple Regression (HMR) was then used to develop the model. HMR coefficients (Beta weights) were used to indicate the relative strength and direction of each factor in the conceptual model diagram. Findings revealed that teacher preparedness is the strongest predictor of PA implementation (R² = 0.784), institutional resources act as enablers (R² = 0.107), and systemic barriers function as suppressors (R² = 0.095). The study proposes a three-layer adoption model integrating teacher capacity, institutional support, and systemic constraints. The model provides a scalable framework for integrating emerging Precision Agriculture into secondary education systems.