Research Design, Mobile Data Collection and Data Analysis using NVIVO and STATA Course

Introduction

The Research Design, Mobile Data Collection and Data Analysis using NVivo and Stata Course is a comprehensive, practical training program designed to equip researchers, development practitioners, and data professionals with the core skills needed to plan, collect, manage, and analyze both qualitative and quantitative data. With the growing demand for evidence-based decision-making in research, policy, and programming, this course provides participants with robust tools to conduct high-quality research across various sectors.

Participants begin by exploring the principles of research design, including how to formulate research questions, choose appropriate methodologies (qualitative, quantitative, or mixed methods), and develop sampling strategies that align with ethical and practical considerations. Emphasis is placed on designing studies that generate actionable insights and support rigorous data collection and analysis. This foundation enables participants to effectively plan and execute research projects in academic, NGO, governmental, or consultancy settings.

The course introduces participants to mobile data collection technologies using platforms such as KoboToolbox and ODK. Participants will learn how to create digital surveys, configure mobile devices for fieldwork, and manage real-time data collection securely and efficiently. They will also be introduced to geospatial data integration and mobile-to-desktop data synchronization, ensuring they are prepared for modern, technology-enabled research environments.

A key component of the course is the dual focus on data analysis using NVivo for qualitative data and Stata for quantitative data. Participants will learn how to manage and code interview transcripts and open-ended responses in NVivo, while also using Stata for data cleaning, descriptive and inferential statistical analysis, regression modeling, and data visualization. By the end of the training, learners will be able to integrate qualitative and quantitative findings, write professional reports, and communicate insights in ways that influence policy, programming, and strategic decision-making.

Duration

10 days

Who should Attend?

This course is ideal for:

·       Researchers and Academicians conducting field studies, thesis research, or academic projects that require rigorous mixed-methods approaches using NVivo and Stata.

·       Monitoring and Evaluation (M&E) Officers responsible for designing studies, collecting data, and generating evidence for development programs.

·       Statisticians and Data Analysts looking to enhance their analytical skills in qualitative and quantitative data management, interpretation, and visualization.

·       Program and Project Managers who oversee surveys, assessments, or baseline studies and want to strengthen their understanding of research and data analysis tools.

·       NGO, Government, and Donor Agency Staff involved in research, learning, policy formulation, and impact evaluations in sectors such as health, education, agriculture, governance, and humanitarian work.

·       Field Researchers, Enumerators, and Data Collection Teams who use mobile tools and want to streamline the design, collection, and processing of field data.

Course Objectives

By the end of this course the learners should be able to:

·       Understand key concepts of research design and methodology, including qualitative, quantitative, and mixed-method approaches tailored to diverse research objectives.

·       Develop robust research frameworks by formulating clear research questions, choosing appropriate sampling methods, and aligning research designs with real-world data needs.

·       Plan and execute field surveys efficiently, from instrument development to survey logistics, using participatory and ethical data collection strategies.

·       Design and deploy digital data collection tools using platforms like KoboToolbox or ODK, including mobile form creation, testing, deployment, and data management in field settings.

·       Collect and manage field data via mobile devices, ensuring secure, accurate, and real-time data synchronization and storage for remote or large-scale surveys.

·       Analyze qualitative data using NVivo, including coding of interviews and open-ended survey responses, identifying patterns and themes, and generating data visualizations and query outputs.

·       Perform quantitative data analysis using Stata, including data cleaning, statistical testing, regression analysis, descriptive summaries, and data visualization for reports and presentations.

·       Triangulate qualitative and quantitative findings, ensuring comprehensive, mixed-method analysis that deepens understanding and supports robust conclusions.

·       Generate insightful reports and visual presentations from NVivo and Stata outputs that effectively communicate findings to diverse stakeholders, including funders, policy makers, and academic audiences.

·       Apply practical data skills in real-world research, evaluations, needs assessments, or academic projects, enhancing data quality, credibility, and usability in evidence-based programming.

Course Outline

Module 1: Foundations of Research and Statistical Concepts

• Introduction to research and statistics
• Key statistical terminology
• Descriptive vs. inferential statistics
• Scales of measurement
• Understanding reliability and validity
• Ethical considerations in research

Module 2: Designing Research Studies

• Role and importance of research design
• Types: experimental, quasi-experimental, non-experimental, mixed-methods
• Longitudinal vs. cross-sectional studies
• Formulating research questions and hypotheses
• Identifying variables and measurement tools
• Exercise: Designing a research blueprint

Module 3: Advanced Survey Planning and Management

• End-to-end survey lifecycle
• Principles of digital survey design
• Probability and non-probability sampling techniques
• Sample size determination tools and software
• Pre-testing and pilot studies
• Real-time quality control during survey implementation

Module 4: Introduction to Digital and Mobile Data Collection

• Mobile-based data collection ecosystems
• Overview of key platforms (ODK, KoboToolbox, SurveyCTO)
• Offline vs. online data collection
• Data security and encryption in the field
• Addressing survey fatigue and response bias

Module 5: Digital Form Design and Authoring

• Designing digital forms: constraints and logic
• Using ODK Build, KoboToolbox, and XLSForms
• Creating skip logic, constraints, calculated fields
• Multimedia and geospatial integration
• Exercise: Build a smart form with dynamic logic

Module 6: Deployment and Device Configuration

• Preparing mobile devices for fieldwork
• Installing ODK Collect, Enketo, KoboCollect
• Troubleshooting synchronization errors
• Uploading and downloading forms securely
• Exercise: Test deployment on Android device

Module 7: Hosting and Managing Survey Data

• Hosting data on cloud (ONA, Kobo, Formhub)
• Local server installation and offline workflows
• Data backup, version control, and exportation
• ODK Briefcase and Aggregate dashboard usage

Module 8: Introduction to GIS and Mapping in Research

• Geospatial data and GPS integration
• Collecting coordinates using mobile devices
• Visualization in QGIS and Google Earth
• Spatial analysis in qualitative/quantitative research

Qualitative Research with NVivo

Module 9: Understanding and Preparing for Qualitative Research

• What is qualitative research?
• Identifying sources: interviews, FGDs, policy documents
• Transcription, translation, and data cleaning
• Organizing research using NVivo key terms

Module 10: Getting Started with NVivo

• NVivo interface and project workspace
• Importing data sources and documents
• Working with multimedia and geodata
• NVivo ribbons and navigation tips

Module 11: Coding and Thematic Exploration

• Creating nodes: case, theme, relationship
• Manual and automatic coding
• Coding for sentiment and tone
• Using queries for exploratory insights

Module 12: Advanced NVivo Analytics and Visualization

• Matrix coding and cross-tabulation
• Text search, word frequency, cluster analysis
• Building concept maps, charts, and models
• Exploring sentiment and thematic clouds

Module 13: Mixed-Methods and Triangulation in NVivo

• Combining NVivo with quantitative outputs
• Importing SPSS/Stata output into NVivo
• Triangulation frameworks and visual outputs

Module 14: Writing and Presenting Qualitative Research

• Developing qualitative report outlines
• Visualizing qualitative insights for stakeholders
• Reporting ethical considerations and reflexivity

Quantitative Analysis with STATA

Module 15: Intro to Stata for Statistical Computing

• Overview of the Stata environment
• Command syntax, data import/export
• Data cleaning, labeling, and transformation

Module 16: Data Visualization in Stata

• Creating histograms, bar charts, and scatterplots
• Using graph editor for customizations
• Exporting and interpreting chart outputs

Module 17: Descriptive and Inferential Statistics

• Summary statistics, cross-tabulations
• T-tests (paired and independent)
• One-way and factorial ANOVA
• Post-hoc tests and Bonferroni corrections

Module 18: Correlation and Regression Analysis

• Pearson and Spearman correlation
• Simple and multiple linear regression
• Logistic and ordinal regression models
• Interpreting regression output

Module 19: Advanced Statistical Modeling

• Panel data analysis (fixed/random effects)
• Time-series analysis: trends, seasonality, forecasting
• Econometric model design and assumptions testing

Module 20: Nonparametric and Categorical Analysis

• Chi-square tests
• Kruskal-Wallis and Wilcoxon tests
• Mann-Whitney U tests and Friedman test

Module 21: Multivariate Analysis and Model Diagnostics

• Principal Component Analysis (PCA)
• Cluster analysis and discriminant analysis
• Model validation and multicollinearity checks

Final Integration and Knowledge Application

Module 22: Integrated Analysis and Data Use

• Connecting NVivo and Stata outputs
• Validating insights across data types
• Drawing evidence-based conclusions

Module 23: Report Writing and Dissemination

• Quantitative and qualitative reporting formats
• Communicating insights to diverse audiences
• Designing executive summaries and dashboards
• Visualization tools: Excel, Tableau, Power BI

Module 24: Data Ethics, Governance, and Open Data

• Ethical frameworks in digital research
• Informed consent and anonymization
• Data governance frameworks and FAIR principles
• Using open data for evidence-based programming

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808

Training Venue

The training will be held at our Upskill Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Upskill certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808

Terms of Payment

Unless otherwise agreed between the two parties payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.