The course aims to provide students with a practical and quantitative understanding of Monitoring and Evaluation (M&E) systems in the context of digital, ecological, and social transitions. At the end of the course, students will be able to: Knowledge and understanding Understand the role of Monitoring and Evaluation within the project cycle, especially in relation to sustainability and transition policies. Acquire theoretical and methodological knowledge about indicators, evaluation strategies, and statistical approaches used in M&E. Applying knowledge and understanding Define and compute appropriate indicators for monitoring real-world projects. Design simple evaluation strategies using counterfactual reasoning. Apply statistical techniques (descriptive, inferential, and graphical) to real-world evaluation data using R. Making judgements Critically assess the quality, relevance, and limitations of indicators and evaluation methods. Interpret empirical results in light of project objectives and broader sustainability goals. Communication skills Effectively present and communicate evaluation findings and data-driven insights, using appropriate statistical language and graphical representations. Interact with both technical and non-technical audiences on M&E-related issues. Learning skills Develop the ability to autonomously expand their knowledge of monitoring and evaluation tools. Build transferable skills for further study or professional practice in project evaluation and policy analysis.

Basic knowledge of statistics (descriptive statistics, regression) and familiarity with R or another statistical software is recommended. Introductory tutorials will be provided at the beginning of the course.

The course introduces the main concepts, methods and tools for Monitoring and Evaluation (M&E) in the project cycle. The approach is mainly quantitative and data-driven, with practical applications in R. Topics include: - Introduction to the project cycle and the role of M&E - Theory of Change and Logical Framework - Indicators for monitoring: output, outcome and impact indicators - Descriptive statistics and data visualization for M&E - Construction of synthetic indices and performance scoring - Regression models (linear and logistic) for impact evaluation - Counterfactual approaches: Propensity Score Matching, Difference-in-Differences - Basics of experimental design and Randomized Controlled Trials - Introduction to dashboards and automated reporting in R A practical component based on real or simulated data will allow students to apply methods using R.

Main textbooks: Kusek, J. Z., & Rist, R. C. (2004). Ten Steps to a Results-Based Monitoring and Evaluation System: A Handbook for Development Practitioners. World Bank. Shah, S. H. (2024). Monitoring and Evaluation of Practice and Methods in Applied Social Research. Routledge. Additional materials and readings (including case studies, datasets, and R code) will be provided during the course.

The module covers the following topics: 1. Introduction to M&E and the project cycle 2. Theory of Change and results chains 3. Design of indicators and measurement strategies 4. Descriptive analysis and data visualization in R 5. Scoring systems and synthetic indicators 6. Regression methods for evaluation 7. Causal inference: PSM and DiD 8. Experimental methods and RCT basics 9. Reporting results: dashboards and policy briefs 10. Group project presentations

The course combines traditional lectures with hands-on sessions in R and a final group project. Students are encouraged to actively engage with practical applications, discussions, and case studies.

TThe final evaluation is composed of: Optional group project (75% of the final grade): students may choose to work in small groups to apply Monitoring and Evaluation techniques to a real or simulated dataset. The project includes a short written report and an oral presentation. Final written exam (mandatory): includes open-ended questions and practical exercises on course content. Students who submit the group project will take a shorter version of the written exam, which accounts for the remaining 25% of the final grade. Students who do not submit the group project will take the full written exam, which will determine 100% of their final grade.

The course will contribute to several Sustainable Development Goals (SDGs) of the Agenda 2030. Monitoring and evaluating the project cycle is essential for the formal assessment of SDG-related initiatives, as it enables evidence-based decision-making and continuous improvement of project outcomes. In particular, the course supports: – Goal 3: Good Health and Well-being, by promoting the use of monitoring and evaluation tools to assess health-related interventions and to improve the effectiveness, equity, and sustainability of public health projects; – Goal 10: Reduced Inequalities, by equipping students with methods to identify, measure, and address social and economic disparities within projects and policies; – Goal 17: Partnerships for the Goals, by emphasizing the role of collaborative approaches, data sharing, and coordinated evaluation practices among stakeholders in achieving development goals.