Training on Research Design and Mobile Data Collection and Mapping and Evidence Based Informatics with NVivo and R

What is Evidence-Based Informatics in Development Research?

Evidence-based informatics integrates research design, digital data collection, spatial mapping, and advanced analytics to transform raw data into actionable insights. It combines mobile survey technologies, qualitative analysis, statistical computing, and geospatial tools to support decision-making in development, public health, and policy contexts.

Many organizations collect large volumes of survey and monitoring data but struggle with poor research design, inconsistent data quality, fragmented tools, and weak analytical capacity. This results in underutilized data and limited impact on decision-making.

This course provides an integrated, hands-on approach to the entire data lifecycle—from research design and mobile data collection to GIS mapping, qualitative analysis, and statistical modeling using NVivo and R. Participants will learn how to design robust studies, ensure data quality, and convert complex datasets into meaningful evidence.

Key Concepts Covered

• Research design for surveys and impact studies
• Sampling techniques and questionnaire design
• Mobile data collection using ODK (Open Data Kit)
• Data quality assurance and field data management
• GIS mapping and spatial data visualization
• Qualitative data analysis using NVivo
• Statistical analysis and modeling using R
• Evidence synthesis and reporting for decision-making

Participants will apply skills to:
• Design and implement baseline, endline, and impact surveys
• Conduct socio-economic, health, and program evaluation studies
• Collect and manage field data using mobile platforms
• Perform spatial analysis and map development indicators
• Analyze qualitative and quantitative datasets
• Produce evidence-based reports for policy and programming

By the end of the course, participants will be able to design research studies, collect high-quality mobile data, perform GIS mapping, analyze qualitative and quantitative datasets, and produce evidence-based insights for decision-making.

Duration

10 Days

Who Should Attend

• Monitoring and Evaluation (M&E) specialists
• Data analysts and research officers
• Public health and development practitioners
• GIS and spatial data professionals
• Statisticians and economists
• Policy analysts and program managers
• Academic researchers and consultants
• NGO and government staff involved in data and research

Organizational Impact

• Enhance research integrity and credibility through a standardized, mixed-methods approach.

• Improve operational efficiency with mobile data collection, reducing time and costs.

• Uncover deeper insights to support more effective and impactful programs.

Personal Impact

• Gain specialized skills in modern research and evaluation methods.

• Advance into senior research, evaluation, or data stewardship roles.

• Contribute to high-quality, reliable research and lead complex projects with confidence.

By the end of this course, participants will:

• Design effective research studies with clear objectives and methodologies.
• Utilize mobile data collection tools to gather field data efficiently.
• Apply geographic information system (GIS) techniques to map and analyze spatial data.
• Use NVivo for qualitative data analysis, including coding and thematic analysis.
• Perform quantitative data analysis using R, including statistical tests and data visualization.
• Integrate and manage data from multiple sources for comprehensive analysis.
• Present research findings effectively using visual and statistical tools.
• Understand ethical considerations in research design and data collection.

Module 1: Introduction to Research Design

• Overview of research methodologies
• Defining research questions and objectives
• Ethical considerations in research

Module 2: Mobile Data Collection Tools

• Introduction to mobile data collection apps (e.g., ODK, KoBoToolbox)
• Setting up surveys and forms
• Field data collection techniques

Module 3: Geographic Mapping and Spatial Data Visualization

• Introduction to GIS and mapping concepts
• Collecting and visualizing spatial data
• Creating maps using open-source GIS tools

Module 4: Introduction to NVivo for Qualitative Analysis

• Overview of NVivo features and interface
• Importing and organizing qualitative data
• Coding and thematic analysis

Module 5: Advanced NVivo Techniques

• Working with multimedia data in NVivo
• Creating and analyzing data matrices
• Using NVivo for mixed methods research

Module 6: Introduction to R for Data Analysis

• Overview of R and RStudio
• Importing and managing datasets in R
• Basic data manipulation and descriptive statistics

Module 7: Statistical Analysis in R

• Performing inferential statistics (t-tests, ANOVA, regression)
• Data visualization using ggplot2
• Advanced statistical methods and modeling

Module 8: Integrating Qualitative and Quantitative Data

• Combining NVivo and R for mixed methods analysis
• Merging and managing data from multiple sources
• Case studies and practical applications

Module 9: Data Presentation and Reporting

• Creating effective visualizations and reports
• Presenting qualitative findings using NVivo
• Preparing comprehensive research reports

Module 10: Final Project and Course Review

• Applying learned techniques to a final project
• Peer review and feedback sessions
• Course summary and Q&A session