Mixed-Methods Evaluation for Complex Programs Training Course

Introduction

Complex development and social programs rarely yield their full story through a single methodological lens. The Mixed-Methods Evaluation for Complex Programs Training Course is specifically designed for M&E professionals, evaluators, and program managers who seek to move beyond siloed quantitative or qualitative approaches and harness the synergistic power of integrating both. This intensive program empowers participants to design and execute evaluations that provide a more comprehensive, nuanced, and robust understanding of how and why complex interventions achieve, or fail to achieve, their intended impacts in multi-faceted contexts.

This comprehensive training delves into the theoretical foundations, practical designs, and analytical techniques required for successful mixed-methods evaluation. Participants will gain hands-on experience in strategically combining quantitative and qualitative data throughout all stages of an evaluation – from design and data collection to analysis and interpretation. By mastering mixed-methods evaluation for complex programs, professionals will be equipped to generate richer insights, triangulate findings for greater credibility, address a broader range of evaluation questions, and ultimately provide more actionable evidence for adaptive management and impactful programming.

Target Audience

• M&E Officers and Specialists
• Professional Evaluators and Consultants
• Program and Project Managers of Complex Initiatives
• Researchers in Development and Social Sciences
• Data Analysts involved in Cross-Cutting Themes
• Organizational Learning Specialists
• Donors and Grant Managers

Duration

5 Days

Course Objectives

1. Understand the foundational concepts, benefits, and challenges of Mixed-Methods Evaluation (MME).
2. Differentiate between various MME designs and select the most appropriate for complex programs.
3. Design MME studies that effectively integrate quantitative and qualitative components.
4. Apply advanced techniques for collecting both quantitative and qualitative data in a coordinated manner.
5. Implement strategies for integrating, analyzing, and interpreting diverse data types.
6. Ensure the rigor, credibility, and trustworthiness of mixed-methods findings.
7. Address ethical considerations specific to collecting and using both types of data.
8. Effectively report and disseminate comprehensive mixed-methods evaluation findings to diverse audiences.

Course Content

Module 1: Introduction to Mixed-Methods Evaluation (MME)

• What is Mixed-Methods Evaluation? Definition and rationale
• The value proposition of MME for understanding complex programs
• Why MME is essential in development and social impact contexts
• MME vs. multi-method vs. quantitative + qualitative
• Overview of the different purposes and applications of MME

Module 2: Philosophical Underpinnings of Mixed Methods

• Understanding paradigms: Positivism, Interpretivism, Pragmatism
• The role of triangulation in MME
• How different worldviews influence methodological choices
• Addressing the "paradigm wars" in evaluation
• Developing a mixed-methods worldview for evaluators

Module 3: Types of Mixed-Methods Designs and Their Applications

• Exploratory Sequential Design (QUAL → QUAN)
• Explanatory Sequential Design (QUAN → QUAL)
• Convergent Parallel Design (QUAN + QUAL)
• Embedded Designs (QUAL(QUAN) or QUAN(QUAL))
• Transformative and Multi-Stage Designs for complex interventions

Module 4: Designing Mixed-Methods Evaluations for Complex Programs

• Formulating mixed-methods evaluation questions
• Developing a mixed-methods logic model or Theory of Change
• Sequencing and prioritizing quantitative and qualitative components
• Designing sampling strategies for integrated data collection
• Crafting a comprehensive mixed-methods evaluation plan

Module 5: Integrating Quantitative and Qualitative Data

• Strategies for data integration: merging, connecting, embedding
• Integrating data at different stages: design, collection, analysis, interpretation
• Typologies of integration: merging, linking, narrating, transforming
• Challenges and opportunities in data integration
• Ensuring consistency and coherence across integrated data

Module 6: Quantitative Data Collection for MME

• Designing surveys and questionnaires for MME
• Utilizing existing databases and administrative data
• Sampling techniques for quantitative components
• Ensuring data quality and validity in quantitative data collection
• Ethical considerations specific to large-scale quantitative data

Module 7: Qualitative Data Collection for MME

• In-depth interviews, focus group discussions, case studies, observation
• Purposive sampling techniques for qualitative components
• Techniques for rapport building and sensitive data collection
• Ensuring trustworthiness and rigor in qualitative data collection
• Ethical considerations specific to in-depth qualitative data

Module 8: Quantitative Data Analysis in MME

• Review of descriptive and inferential statistics relevant to MME
• Analyzing quantitative data to identify patterns, correlations, and causal inferences
• Using statistical software (e.g., R, Stata, SPSS) for quantitative analysis
• Interpreting quantitative findings for their significance
• Preparing quantitative data for integration

Module 9: Qualitative Data Analysis in MME

• Thematic analysis, content analysis, narrative analysis, case study analysis
• Coding and categorizing qualitative data
• Using Qualitative Data Analysis (QDA) software (e.g., NVivo, ATLAS.ti)
• Interpreting qualitative findings for meaning and context
• Preparing qualitative data for integration (e.g., creating memos, matrices)

Module 10: Mixed-Methods Data Analysis and Interpretation

• Techniques for mixed-methods analysis: data transformation, comparison, triangulation matrix
• Identifying convergent, divergent, and complementary findings
• Developing mixed-methods insights and explanations
• Interpreting findings in light of the integrated evidence
• Practical exercises in mixed-methods data analysis

Module 11: Ensuring Rigor and Credibility in MME

• Strategies for enhancing the quality of mixed-methods designs
• Addressing validity concerns in MME (e.g., methodological coherence)
• Ensuring ethical conduct throughout the MME process
• Peer debriefing, member checking, and external audits for MME
• Documenting the mixed-methods process for transparency

Module 12: Reporting and Disseminating Mixed-Methods Evaluation Findings

• Structuring mixed-methods evaluation reports
• Presenting integrated findings effectively and compellingly
• Visualizing mixed-methods data for clarity and impact
• Tailoring communication for diverse stakeholders (e.g., policymakers, practitioners, communities)
• Utilizing mixed-methods findings for adaptive management and policy influence

General remarks

• Customizable courses are available to address the specific needs of your organization.
• The participant must be conversant in English
• Participants who successfully complete this course will receive a certificate of completion from Lenol Development Center.
• The course fee for onsite training includes facilitation training materials, tea break and lunch.
• Accommodation and airport pick up are made upon request
• For any inquiries reach us through info@lenoldevelopmentcenter.com or +254 710 314 746
• Payment should be made to our bank