This chapter introduces the monitoring and evaluation (M&E) framework applied to GenAI integration, grounded in a theory of change (ToC). It begins with the problem statement—students’ lack of understanding of GenAI’s capabilities, limitations, and ethical dimensions—and outlines intervention strategies including practical application, collaborative learning, ethics-focused discussions, and structured evaluation. The framework defines inputs (such as training materials, AI forms, and policy briefs), outputs (student engagement, reduced misconduct cases), and outcome levels. Short-term outcomes (immediate evaluation) measure knowledge, confidence, application, and awareness directly after the course, while medium-term outcomes (follow-up evaluation) capture to measure knowledge retention, application in different contexts, long-term confidence in using GenAI, and critical awareness of technology 3–6 months later. Long-term outcomes focus on broader academic and professional adoption. The chapter also details evaluation research methodology, including sampling, data collection and analysis procedures, survey instruments, indicators, and ethical safeguards, offering peers a ready-to-use framework for evaluating GenAI interventions systematically.