Course Outline:

Module 1: Introduction to Data-Driven Monitoring and Evaluation

• Overview of M&E in educational programs
• Importance of data-driven M&E in improving education
• Case Study: Effective use of data in M&E for educational outcomes

Module 2: Data Collection Techniques for Monitoring and Evaluation

• Techniques for gathering quantitative and qualitative data
• Tools and platforms for data collection in educational settings
• Real-Life Project: Designing a data collection plan for a school program

Module 3: Data Analysis and Interpretation

• Key methods for analyzing educational data
• Interpreting data to assess program performance and outcomes
• Case Study: Analyzing M&E data to improve teaching outcomes

Module 4: Applying Data for Program Improvement

• Using M&E data to inform decision-making and program adjustments
• Techniques for presenting and communicating data insights to stakeholders
• Real-Life Project: Developing a data-driven improvement plan for an educational program

Module 5: Best Practices and Future Directions in Data-Driven Monitoring and Evaluation

• Best practices for maintaining effective M&E processes
• Exploring trends in data-driven education M&E, including AI and predictive analytics
• Case Study: Future trends in M&E for education programs