Data-Driven Decision Making in Kenyan Secondary Schools: Enablers and Barriers

Abstract

Globally, data-driven decision-making (DDDM) or data use is increasingly recognised for its potential to improve educational outcomes and enhance accountability in schools. However, despite its growing importance, many schools, especially in developing countries such as Kenya, continue to face significant challenges in effectively implementing DDDM practices. This research examined the factors that facilitate and hinder data use in Kenyan secondary schools. A qualitative case study design was employed, and semi-structured interviews were conducted to gather data. The data were analysed into themes using the NVivo qualitative data analysis programme, aligned with the research question and the conceptual framework. Results indicate that the main enablers of data use in Kenyan schools are external policy characteristics such as accountability demands, organisational features like school leadership and students, and user traits like buy-in and belief, while the main barriers include inefficient data systems, data illiteracy, the inaccessibility of some data such as inspection reports, and uncooperative parents. The study recommends training teachers in data use skills and investing in data systems and technology.