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

Introduction

The Research Design, Mobile Data Collection and Data Analysis using NVivo and SPSS Course is an intensive, hands-on training program designed to build practical research competencies for professionals working in academic, development, public policy, and corporate environments. As data becomes central to decision-making, monitoring, and reporting, this course equips participants with modern tools and methodologies to design effective research studies, collect data efficiently using mobile technologies, and analyze both qualitative and quantitative data with NVivo and SPSS.

The course begins by grounding participants in the fundamentals of research design, including formulating research questions, selecting appropriate methodologies (qualitative, quantitative, or mixed methods), and applying ethical principles. It then transitions into mobile data collection, where participants learn to create digital survey forms, deploy them using platforms such as KoboToolbox or ODK, and manage data collection using smartphones or tablets — improving data accuracy, speed, and real-time access.

A key focus of the course is on qualitative and quantitative data analysis. Participants will use NVivo for coding, organizing, and analyzing qualitative data such as interview transcripts, open-ended survey responses, and field notes. They will also learn SPSS for quantitative data analysis, covering data entry, cleaning, descriptive statistics, cross-tabulations, inferential analysis, and visualization. This dual approach empowers learners to generate integrated insights from both narrative and numeric data.

By the end of the course, participants will be able to conduct end-to-end research — from designing tools and collecting data in the field to performing rigorous analysis and presenting results effectively. This course is ideal for researchers, evaluators, analysts, and development professionals seeking to apply modern, evidence-based approaches to research and data-driven decision-making.

Duration

10 days

Who should Attend?

This course is ideal for:

·       Research Officers and Analysts seeking to strengthen their skills in end-to-end research management and data analysis.

·       Monitoring and Evaluation (M&E) Practitioners responsible for collecting, managing, and reporting data in development, humanitarian, or public sector programs.

·       Program and Project Managers who need to interpret research findings and integrate data into evidence-based planning and decision-making.

·       Academic Researchers, and Thesis Writers conducting mixed-methods research or needing to use NVivo and SPSS in their dissertations.

·       NGO, Government, and Donor Staff engaged in baseline surveys, impact assessments, or policy research requiring mobile data collection and integrated analysis.

·       Consultants and Independent Researchers involved in field research, qualitative interviews, and quantitative survey data analysis.

·       Data Collection Teams and Field Supervisors looking to transition from paper-based to mobile and digital survey systems.

Course Objectives

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

·       Understand key principles of research design, including how to formulate research questions, choose appropriate methodologies (qualitative, quantitative, or mixed methods), and develop sound sampling strategies.

·       Plan and implement effective surveys and field research, including designing data collection tools and developing structured processes for reliable, ethical data gathering.

·       Develop and deploy mobile-based data collection tools using platforms such as KoboToolbox or ODK, including form creation, device configuration, and remote data management.

·       Collect, manage, and validate field data using smartphones and tablets, ensuring real-time synchronization, quality control, and secure data storage.

·       Analyze qualitative data using NVivo, including coding transcripts, identifying themes, conducting text-based queries, and generating visual representations of insights (e.g., word clouds, cluster maps, and models).

·       Analyze quantitative data using SPSS, including data entry and cleaning, performing descriptive and inferential statistical tests, and creating graphs and tables for reporting.

·       Triangulate qualitative and quantitative data, using results from both NVivo and SPSS to provide a comprehensive understanding of research findings.

·       Interpret and present research results effectively, using appropriate charts, narratives, and data visualization techniques for stakeholder reports and decision-making.

·       Integrate ethical and practical considerations in all stages of research, including informed consent, confidentiality, data protection, and cultural sensitivity in fieldwork.

·       Apply the skills learned to real-world scenarios, including academic research, impact evaluations, needs assessments, program monitoring, and evidence-based policy work.

Course Outline

Part 1: Foundations of Research and Statistical Literacy

Module 1: Introduction to Research and Statistics

• Importance of evidence-based research
• Overview of research types and paradigms
• Statistical thinking: concepts, variables, scales, data types
• Descriptive vs. inferential statistics

Module 2: Research Design and Methodology

• Role and structure of a research design
• Qualitative, quantitative, and mixed methods
• Developing conceptual and theoretical frameworks
• Ethics and informed consent in research
• Practical: Develop a research design around a real-world problem

Module 3: Survey Planning and Fieldwork Management

• Survey types and objectives (household, facility, online, etc.)
• Sampling methods and calculating sample size
• Enumerator training and quality assurance
• Post-survey procedures and data quality audits
• Exercise: Field planning simulation

Part 2: Mobile Data Collection and Digital Survey Tools

Module 4: Overview of Mobile Data Collection

• Benefits and challenges of mobile surveys
• Key tools: ODK, KoboToolbox, SurveyCTO, CommCare
• Question types, logic, and form structures
• Device management and offline syncing
• Data security and cloud storage

Module 5: Survey Form Design (Web Interfaces and XLSForms)

• Designing surveys using:
• ODK Build
• KoboForm
• XLSForm syntax and advanced functions
• Logic design: skip patterns, constraints, repeats
• Multimedia integration: images, GPS, audio
• Practical: Build and test digital survey forms

Module 6: Deployment and Data Hosting

• Installing ODK Collect and other clients
• Uploading and deploying forms on:
• Ona.io
• FormHub
• KoboToolbox
• Local server configuration (ODK Aggregate)
• Data export and backup protocols

Module 7: GIS Integration and Mapping Survey Data

• Introduction to GIS and QGIS
• Collecting geospatial data through mobile surveys
• Mapping responses and visual analytic

Part 3: Qualitative Research and NVivo Analysis

Module 8: Foundations of Qualitative Research

• What is qualitative research?
• Data sources: interviews, focus groups, documents
• Deductive vs. inductive analysis
• Introduction to NVivo and its interface

Module 9: Managing Projects in NVivo

• Creating projects and importing sources
• Creating nodes (thematic, case, relationship)
• Memos, annotations, and linking evidence
• Classifications and attributes

Module 10: Coding and Thematic Analysis

• Descriptive, analytic, and tree coding
• Coding queries, matrix coding, and text searches
• Word frequency and cluster analysis
• Visualizing coded data (charts, models, tree maps)

Module 11: Advanced NVivo Techniques

• Grounded Theory, Narrative, and Discourse Analysis
• Case comparisons and node matrices
• Mixed-method integration: merging with survey data
• Triangulating qualitative and quantitative insights

Part 4: Quantitative Data Analysis with SPSS

Module 12: Introduction to SPSS

• Interface overview: Data View, Variable View, Output
• Data entry, transformation, labeling
• Importing data from Excel, CSV, and mobile platforms

Module 13: Descriptive Statistics and Visualization

• Frequency tables and cross-tabulations
• Central tendency and variability
• Graphs: histograms, bar charts, boxplots, scatterplots
• Custom templates and output formatting

Module 14: Inferential Statistics

• Correlation analysis
• Simple and multiple regression
• Hypothesis testing (t-tests, ANOVA, chi-square)
• Factorial and repeated measures ANOVA

Module 15: Advanced Statistical Procedures

• Logistic regression and classification
• Non-parametric tests (Mann-Whitney, Kruskal-Wallis, Wilcoxon)
• Reliability testing (Cronbach’s alpha)
• Data transformation and recoding

Part 5: Cross-Tool Integration, Reporting and Use

Module 16: Integration of NVivo, SPSS and Field Data

• Exporting coded NVivo data for SPSS analysis
• Using SPSS outputs to inform qualitative coding
• Mixed-methods triangulation frameworks
• Reporting patterns and convergence/divergence

Module 17: Data Use and Communication

• Developing data use frameworks for organizations
• Data visualization principles for diverse audiences
• Designing infographics, executive summaries, and dashboards
• Presenting to technical and non-technical stakeholders

Module 18: Report Writing and Dissemination

• Structuring research reports for different purposes
• Writing clear narratives from mixed-method results
• Communication and dissemination strategy
• Data demand and use planning
• Exercise: Prepare a full report, presentation, and data use plan

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.