Introduction:

The "Impact Evaluation and Data Analysis of Programs" course is designed to provide participants with a comprehensive understanding of impact evaluation methods and data analysis techniques. The course aims to enhance participants' skills in evaluating program impacts, analyzing program data, and utilizing evidence-based approaches for decision-making. Participants will gain practical knowledge and hands-on experience in designing and conducting impact evaluations, managing and analyzing program data, and communicating evaluation findings.

Course Objective:

The objective of this course is to equip participants with the knowledge and skills to effectively evaluate program impacts and analyze program data. By the end of the course, participants should be able to:

1. Understand the importance of impact evaluation and data analysis in program assessment.
2. Design and implement impact evaluation studies using appropriate methodologies.
3. Collect and manage data for impact evaluation purposes.
4. Apply quantitative and qualitative data analysis techniques to evaluate program impacts.
5. Interpret and communicate evaluation findings to stakeholders.
6. Utilize evaluation results for evidence-based decision-making.
7. Incorporate ethical considerations into impact evaluation practices.

Organizational Benefits: Organizations can derive several benefits from participating in the Impact Evaluation and Data Analysis of Programs course, including:

1. Improved Program Effectiveness: Organizations can assess the true impact of their programs by employing rigorous evaluation methods and data analysis techniques. This leads to a better understanding of program outcomes and enables organizations to make informed decisions for program improvement.
2. Enhanced Accountability and Transparency: Through impact evaluation and data analysis, organizations can demonstrate their accountability to stakeholders. By evaluating program impacts and presenting findings, organizations can provide evidence of program effectiveness and transparency in resource utilization.
3. Evidence-Based Decision-Making: Impact evaluation and data analysis provide organizations with a solid foundation for decision-making. By utilizing rigorous evaluation methods and analyzing program data, organizations can make informed decisions about program continuation, modification, or termination.
4. Strategic Resource Allocation: With a thorough understanding of program impacts, organizations can allocate resources more strategically. By identifying which programs yield the highest returns and have the greatest impact, organizations can optimize resource allocation to maximize program effectiveness.
5. Program Innovation and Learning: Through impact evaluation and data analysis, organizations can identify areas for program innovation and learning. By analyzing program data, organizations can uncover insights, best practices, and areas for improvement, leading to program innovation and increased effectiveness.

Duration:

10 days

Course Outline

1. Module 1: Introduction to Impact Evaluation and Data Analysis
• Understanding the importance of impact evaluation
• Introduction to data analysis for program evaluation
• Key concepts and terminology
2. Module 2: Impact Evaluation Frameworks and Approaches
• Different types of impact evaluation (experimental and non-experimental)
• Choosing the appropriate evaluation design
• Understanding counterfactuals and attribution
3. Module 3: Designing Impact Evaluation Studies
• Formulating evaluation questions and objectives
• Developing a logic model and theory of change
• Identifying appropriate indicators and data sources
4. Module 4: Quantitative Data Collection Methods for Impact Evaluation
• Surveys and questionnaires
• Sampling techniques and sample size determination
• Data collection tools and techniques
5. Module 5: Qualitative Data Collection Methods for Impact Evaluation
• Interviews and focus groups
• Observation and document analysis
• Ethnographic methods in evaluation
6. Module 6: Sampling Techniques for Impact Evaluation
• Probability and non-probability sampling methods
• Simple random sampling and stratified sampling
• Cluster sampling and systematic sampling
7. Module 7: Data Management and Quality Assurance in Impact Evaluation
• Data cleaning and validation
• Data coding and entry
• Ensuring data reliability and validity
8. Module 8: Descriptive Statistical Analysis for Program Data
• Summary statistics and data visualization
• Frequency distributions and measures of central tendency
• Data exploration techniques
9. Module 9: Inferential Statistical Analysis for Impact Evaluation
• Hypothesis testing and confidence intervals
• t-tests and chi-square tests
• Analysis of variance (ANOVA)
10. Module 10: Regression Analysis for Impact Evaluation
• Simple linear regression
• Multiple regression analysis
• Interpreting regression results
11. Module 11: Difference-in-Differences (DiD) Analysis
• Understanding the DiD approach
• DiD assumptions and identification strategies
• Implementing DiD analysis in impact evaluation
12. Module 12: Propensity Score Matching (PSM) Analysis
• Introduction to propensity score matching
• Matching methods and techniques
• Assessing balance and estimating treatment effects
13. Module 13: Randomized Controlled Trials (RCTs) in Impact Evaluation
• Introduction to RCTs and their advantages
• Designing and implementing RCTs
• Analyzing and interpreting RCT results
14. Module 14: Qualitative Data Analysis Techniques for Impact Evaluation
• Coding and thematic analysis
• Content analysis
• Framework analysis and qualitative comparative analysis
15. Module 15: Mixed-Methods Approaches in Impact Evaluation
• Integrating qualitative and quantitative data
• Triangulation and complementarity
• Sequential and concurrent designs
16. Module 16: Cost-Effectiveness and Cost-Benefit Analysis of Programs
• Understanding economic evaluations
• Cost-effectiveness analysis (CEA)
• Cost-benefit analysis (CBA)
17. Module 17: Data Visualization for Impact Evaluation
• Principles of effective data visualization
• Tools and software for data visualization
• Creating dashboards and infographics
18. Module 18: Geographic Information Systems (GIS) in Impact Evaluation
• Introduction to GIS and spatial data
• Spatial analysis techniques for impact evaluation
• Mapping and visualizing program impacts
19. Module 19: Monitoring and Evaluation (M&E) Frameworks for Programs
• Linking impact evaluation with M&E
• Developing M&E frameworks and indicators
• Utilizing M&E data for impact evaluation
20. Module 20: Theory of Change and Logic Models in Impact Evaluation
• Developing a theory of change
• Constructing logic models
• Using logic models for impact evaluation planning
21. Module 21: Participatory Approaches in Impact Evaluation
• Engaging stakeholders in the evaluation process
• Participatory data collection methods
• Participatory data analysis and interpretation
22. Module 22: Ethical Considerations in Impact Evaluation
• Ensuring informed consent and confidentiality
• Addressing ethical challenges in impact evaluation
• Ethical guidelines and codes of conduct
23. Module 23: Communicating Impact Evaluation Findings
• Effective reporting and dissemination strategies
• Presenting data and results to diverse audiences
• Writing impact evaluation reports
24. Module 24: Utilizing Evaluation Findings for Decision-Making
• Using evaluation results to inform program improvement
• Incorporating findings into decision-making processes
• Evidence-based decision-making in organizations
25. Module 25: Institutionalizing Impact Evaluation within Organizations
• Building evaluation capacity within organizations
• Integrating impact evaluation into program cycles
• Creating a culture of evaluation and learning
26. Module 26: Case Studies in Impact Evaluation
• Examining real-world impact evaluation studies
• Analyzing challenges and lessons learned
• Extracting insights and best practices
27. Module 27: Practical Application and Hands-on Exercises
• Applying impact evaluation techniques to real-world scenarios
• Conducting data analysis using statistical software
• Interpreting and presenting evaluation results
28. Module 28: Final Project: Designing an Impact Evaluation Study
• Applying the knowledge and skills acquired throughout the course
• Designing an impact evaluation study for a selected program
• Presenting the evaluation plan and methodology

General Notes

• All our courses can be Tailor-made to participants' needs
• The participant must be conversant in English
• Presentations are well-guided, practical exercises, web-based tutorials, and group work. Our facilitators are experts with more than 10 years of experience.
• Upon completion of training the participant will be issued with a Foscore development center certificate (FDC-K)
• Training will be done at the Foscore development center (FDC-K) centers. We also offer inhouse and online training on the client schedule
• Course duration is flexible and the contents can be modified to fit any number of days.
• The course fee for onsite training includes facilitation training materials, 2 coffee breaks, a buffet lunch, and a Certificate of successful completion of Training. Participants will be responsible for their own travel expenses and arrangements, airport transfers, visa application dinners, health/accident insurance, and other personal expenses.
• Accommodation, pickup, freight booking, and Visa processing arrangement, are done on request, at discounted prices.
• Tablet and Laptops are provided to participants on request as an add-on cost to the training fee.
• One-year free Consultation and Coaching provided after the course.
• Register as a group of more than two and enjoy a discount of (10% to 50%)
• Payment should be done before commence of the training or as agreed by the parties, to the FOSCORE DEVELOPMENT CENTER account, so as to enable us to prepare better for you.
• For any inquiries reach us at training@fdc-k.org or +254712260031
• Website:www.fdc-k.org