Monitoring and Evaluation (M&E) are essential processes in international development, ensuring accountability, learning, and program effectiveness. This article examines the evolution of M&E from compliance-driven reporting to adaptive systems grounded in Results-Based Management (RBM), the Logical Framework Approach (LogFrame), and Theory of Change (ToC). Particular attention is given to low-resource settings, where context-sensitive and cost-effective approaches are critical. The analysis highlights practical strategies for adapting data collection and reporting, with examples from health, agriculture, and community programs. Emerging trends, including the use of mobile technologies, artificial intelligence, and machine learning, are considered for their potential to enhance real-time monitoring and predictive insights. The article concludes that participatory, culturally grounded, and adaptive approaches are essential for strengthening trust, ensuring sustainability, and embedding M&E as a culture of learning in development practice.
Anna Neya Kazanskaia (Wed,) studied this question.