Theory-Driven Evaluation and Data Integration Training Course
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.
Skills Covered
Course Overview
Program for 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.
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
Send us an email: info@datastatresearch.org or call +254724527104
Certification
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 DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.