Home→Courses→Theory-Driven Evaluation and Data Integration Training Course
Research and Data Analysis
Theory-Driven Evaluation and Data Integration Training Course
Introduction
In today’s data-driven world, organizations must adopt Theory-Driven Evaluation (TDE) and Data Integration strategies to ensure impactful decision-making, measurable outcomes, and sustainable program success. Program for Theory-Driven Evaluation and Data Integration Training Course equips participants with the skills to align evaluation frameworks with theoretical models, while seamlessly integrating qualitative and quantitative data for deeper insights. Our training empowers evaluators, program managers, policymakers, and researchers to develop robust evaluations that are evidence-based, results-oriented, and capable of driving strategic change in complex systems.
The program addresses the increasing demand for evaluation capacity building, mixed-methods research, and data synthesis techniques across sectors like health, education, development, and social policy. Participants will gain expertise in linking program theories to data analysis, interpreting integrated data for policy influence, and applying real-world case studies to enhance impact evaluation, data visualization, and evidence-informed policy making. The course blends theory, practice, and technology, offering participants tools to master contemporary evaluation and data integration trends.
Programme Curriculum
Program for Theory-Driven Evaluation and Data IntegrationTraining Course
Introduction
In today’s data-driven world, organizations must adopt Theory-Driven Evaluation (TDE) and Data Integration strategies to ensure impactful decision-making, measurable outcomes, and sustainable program success. Program for Theory-Driven Evaluation and Data Integration Training Course equips participants with the skills to align evaluation frameworks with theoretical models, while seamlessly integrating qualitative and quantitative data for deeper insights. Our training empowers evaluators, program managers, policymakers, and researchers to develop robust evaluations that are evidence-based, results-oriented, and capable of driving strategic change in complex systems.
The program addresses the increasing demand for evaluation capacity building, mixed-methods research, and data synthesis techniques across sectors like health, education, development, and social policy. Participants will gain expertise in linking program theories to data analysis, interpreting integrated data for policy influence, and applying real-world case studies to enhance impact evaluation, data visualization, and evidence-informed policy making. The course blends theory, practice, and technology, offering participants tools to master contemporary evaluation and data integration trends.
Course Objectives
Understand the principles of Theory-Driven Evaluation (TDE) for complex interventions.
Apply mixed-methods research for comprehensive data integration.
Design evaluation frameworks aligned with program theories of change.
Utilize data visualization to present integrated data effectively.
Implement evidence-based decision-making in program evaluation.
Integrate qualitative and quantitative data for enhanced insight.
Assess causal pathways using theory-informed data analysis.
Employ data triangulation techniques for validation and reliability.
Strengthen capacity in impact evaluation through theory-driven models.
Translate evaluation findings into policy recommendations.
Navigate ethical considerations in data collection and integration.
Harness digital tools and AI in data integration for evaluations.
Develop practical skills through case studies and real-world applications.
Target Audiences
Program Evaluators
Data Analysts and Scientists
Policy Makers and Advisors
Monitoring & Evaluation (M&E) Specialists
Academic Researchers
Development Practitioners
NGO and CSO Managers
Public Health Professionals
Course Duration: 5 days
Course Modules
Module 1: Foundations of Theory-Driven Evaluation
Understanding Theory-Driven Evaluation (TDE)
Key components of Theories of Change (ToC)
Aligning evaluation designs with theoretical frameworks
TDE in complex program contexts
Challenges and opportunities in TDE
Case Study: Applying TDE in Health Intervention Programs
Module 2: Designing Mixed-Methods Research for Data Integration
Overview of mixed-methods research
Strategies for data integration
Designing research questions for mixed methods
Sampling techniques for mixed data
Integrating datasets for comprehensive analysis
Case Study: Mixed-Methods in Educational Program Evaluation
Module 3: Program Evaluation Frameworks and Models
Evaluation frameworks (Logical Framework, ToC)
Formative vs. Summative Evaluations
Evaluation metrics and indicators
Measuring outcomes and impacts
Adapting frameworks to dynamic programs
Case Study: Logical Framework in Social Development Projects
Module 4: Data Triangulation and Validation Techniques
Understanding data triangulation
Types of triangulation: data, investigator, theory, methodological
Enhancing data reliability and validity
Dealing with biases in evaluation
Analytical tools for triangulation
Case Study: Triangulation in Community Development Evaluations
Module 5: Data Visualization and Communication of Findings
Principles of effective data visualization
Tools for visualizing integrated data (Power BI, Tableau)
Storytelling with data
Customizing visuals for different audiences
Communicating uncertainty in data
Case Study: Data Dashboards for Policy Influence
Module 6: Evidence-Based Policy and Decision Making
From evidence to policy: the translation process
Crafting actionable recommendations
Stakeholder engagement in policy development
Communicating evaluation results to policymakers
Case examples of policy impact from evaluations
Case Study: Policy Recommendations from National Health Evaluations
Module 7: Ethical Considerations in Data Collection & Integration
Ethical standards in evaluation research
Informed consent in data collection
Data privacy and protection frameworks
Addressing cultural sensitivities in data gathering
Ethics in AI and digital data tools
Case Study: Ethical Challenges in Cross-Cultural Evaluations
Module 8: Technology, AI, and Future Trends in Evaluation
Emerging technologies in evaluation
AI tools for data integration and analysis
Predictive analytics in evaluations
Blockchain for data transparency
Future trends in evaluation methodologies
Case Study: AI-Driven Evaluation in Social Programs
Training Methodology
Interactive lectures and expert presentations
Hands-on workshops on data integration tools
Group discussions and peer learning
Real-world case studies analysis
Practical assignments and project-based learning
Post-training mentorship and support
Register as a group from 3 participants for a Discount
Upon successful completion of this training, participants will be issued with a globally- recognized certificate.
Tailor-Made Course
We also offer tailor-made courses based on your needs.
Key Notes
a. The participant must be conversant with English.
b. Upon completion of training the participant will be issued with an Authorized Training Certificate
c. Course duration is flexible and the contents can be modified to fit any number of days.
d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.
e. One-year post-training support Consultation and Coaching provided after the course.
f. Payment should be done at least a week before commence of the training, to FINESKILL TRAINING CENTER account, as indicated in the invoice so as to enable us prepare better for you.