Tailoring a complexity-aware theory of change for out-of-school children education program: reflections on an evaluation of Korea–Qatar innovation initiative

Abstract

The objective of this study is to explore and discuss the conceptual and methodological importance for a more holistic and complexity-aware framework by employing the Theory of Change into the design and evaluation of international education initiatives. Through a critical analysis of the KOICA–Qatar’s Education Above All Foundation partnership project, which aimed to support Out-of-School Children (OOSC) in Cambodia, Iran, Myanmar, and Nepal, we identified several key lessons learned. First, the joint program narrowed both the conceptual and practical dimensions of educational interventions by prioritizing simplistic numerical metrics—specifically the return of OOSC/Y to formal schooling—thereby aligning with the prevailing trends in accountability and transparency in evaluating global educational programs. Secondly, the education projects within the large scale of KOICA-Qatar Education Above All Program assumed that educational impact directly resulted from program outputs, revealing a lack of clear linkage between overarching program-level educational outcomes—namely, quality education for all—and the outputs of individual sub-projects, such as student enrollment figures. Thirdly, an overemphasis on linear project-level logic, while neglecting the interconnected influence of noneducational factors—such as legal and social protection, sanitation, and health—limited the ability to effectively navigate the complexities of OOSC programs. We propose that moving beyond the conventional linear approach to educational programs requires tailoring a complexity-aware Theory of Change. Integrating Theory of Change Analysis (TOCA) into the strategic framework for educational development and the OOSC program model can enhance our capacity to plan and evaluate diverse pathways for achieving positive social and educational impact while accounting for various program assumptions, risks, and other complex macro-level factors.