Workshop On Research Design, Mobile Data Collection And Mapping And Data Analysis Using Nvivo And R

INTRODUCTION

The rapid advancements in data science present unparalleled opportunities to enhance decision-making processes across various sectors. In development contexts, numerous data-gathering initiatives such as baseline surveys, socio-economic surveys, demographic and health surveys, and program evaluation surveys are increasingly being conducted to inform decisions. To maximize the potential of these data collection efforts, it is crucial not only to generate new insights but also to enhance individual judgment in real-world development scenarios. This ten-day hands-on workshop is meticulously designed to address these needs by empowering participants with the skills necessary to produce accurate, cost-effective data and reports that are user-friendly and instrumental in decision-making. The training will cover tools such as Open Data Kit (ODK), GIS, NVivo, and R to equip participants with comprehensive data management, analysis, and visualization skills.

Course Objectives

By the end of this course, participants should be able to:

• Understand and appropriately use statistical terms and concepts
• Design and implement universally acceptable surveys
• Convert data into various formats using appropriate software
• Utilize mobile data gathering tools such as Open Data Kit (ODK)
• Use GIS software to plot and display data on basic maps
• Conduct qualitative data analysis using NVivo
• Apply statistical techniques using R for data analysis
• Interpret statistical analysis results using R
• Identify suitable statistical techniques for different data and research questions
• Build intuitive data visualizations
• Conduct formalized hypothesis testing
• Implement linear modeling techniques such as multiple regressions and GLMs
• Perform advanced regression and multivariate analysis
• Write comprehensive reports from survey data
• Develop strategies to improve data demand and use in decision-making

Duration

10 Days

Who Should Attend

This course targets participants with elementary knowledge of statistics from various fields such as agriculture, economics, food security, livelihoods, nutrition, education, medical or public health, and others who wish to become proficient in the concepts and applications of statistical modeling.

Course Content

Module 1: Basic Statistical Terms and Concepts

• Introduction to statistical concepts
• Descriptive Statistics
• Inferential Statistics

Module 2: Research Design

• The role and purpose of research design
• Types of research designs
• The research process
• Choosing the appropriate method
• Exercise: Identify a project and develop a research design

Module 3: Survey Planning, Implementation, and Completion

• Types of surveys
• The survey process
• Survey design
• Survey sampling methods
• Determining sample size
• Planning and conducting surveys
• Post-survey activities
• Exercise: Plan a survey based on the selected research design

Module 4: Introduction to Mobile Data Collection

• Introduction to mobile data gathering
• Benefits of mobile applications
• Data types and management
• Mobile Data Collection Platforms Overview
• Managing data collection devices
• Challenges in data collection
• Data aggregation, storage, and dissemination
• Questionnaire design and logic
• Advanced data types: geoid, image, multimedia

Module 5: Survey Authoring

• Design forms using web interfaces:
  • ODK Build
  • Koboforms
  • PurcForms
• Hands-on Exercise

Module 6: Preparing the Mobile Device for Data Collection

• Installing applications: ODK Collect
• Configuring the device
• Uploading forms to mobile devices
• Hands-on Exercise

Module 7: Designing Forms Manually Using XLSForms

• Introduction to XLSForms syntax
• Creating new data types, notes, dates
• Multiple choice questions, multi-language support
• Hints, metadata
• Hands-on Exercise

Module 8: Advanced Survey Authoring

• Conditional survey branching
• Required questions, constraining responses
• Skip logic
• Grouping questions, repeating sections
• Dynamic calculations
• Hands-on Exercise

Module 9: Hosting Survey Data Online

• Platforms: ODK Aggregate, Formhub, Ona.io, KoboToolbox
• Uploading forms to servers
• Configuring local servers
• Data download methods: Manual, ODK Briefcase
• Hands-on Exercise

Module 10: GIS Mapping of Survey Data Using QGIS

• Introduction to GIS for researchers and data scientists
• Importing survey data into GIS
• Mapping survey data using QGIS
• Hands-on Exercise

Module 11: Understanding Qualitative Research

• Introduction to qualitative data
• Types and sources of qualitative data
• Qualitative vs quantitative research
• NVivo key terms and workspace overview
• Hands-on Exercise

Module 12: Preliminaries of Qualitative Data Analysis

• Introduction to qualitative data analysis
• Approaches: Deductive vs inductive
• Principles and process of qualitative data analysis
• Hands-on Exercise

Module 13: Introduction to NVivo

• NVivo interface and key terms
• Creating and managing projects
• Importing and merging documents
• Working with different data sources
• Hands-on Exercise

Module 14: Nodes in NVivo

• Types of nodes: Theme, case, relationship, node matrices
• Creating and browsing nodes
• Creating memos, annotations, and links
• Hands-on Exercise

Module 15: Classes and Summaries

• Source, case, node classifications
• Creating and importing attributes
• Query and matrix coding
• Hands-on Exercise

Module 16: Coding

• Data-driven vs theory-driven coding
• Analytic, descriptive, thematic coding
• Tree coding
• Hands-on Exercise

Module 17: Thematic Analytics in NVivo

• Organizing, storing, and retrieving data
• Cluster analysis and text searches
• Word frequency queries
• Hands-on Exercise

Module 18: Queries Using NVivo

• Queries for textual analysis and exploring coding
• Hands-on Exercise

Module 19: Building on the Analysis

• Content, narrative, discourse analysis
• Grounded theory
• Hands-on Exercise

Module 20: Qualitative Analysis Results Interpretation

• Comparing analysis results with research questions
• Summarizing findings
• Drawing conclusions and lessons learned
• Hands-on Exercise

Module 21: Visualizing NVivo Projects

• Creating models, graphs, tree maps, cluster analysis diagrams
• Generating reports and extracts
• Hands-on Exercise

Module 22: Triangulating Results and Sources

• Triangulating with quantitative data
• Using participatory techniques to measure indicators
• Comparing analyses from different data sources
• Ensuring respondent consistency
• Hands-on Exercise

Module 23: Report Writing

• Qualitative report format
• Reporting qualitative research content and interpretation
• Hands-on Exercise

Module 24: Basics of Applied Statistical Modelling Using R

• Introduction to the instructor and course
• Data and code used in the course
• Designing studies and collecting good-quality data
• Types of data
• Hands-on Exercise

Module 25: Essentials of the R Programming

• Introduction to R and R Studio
• Data structures in R
• Reading data from different sources
• Data cleaning and exploratory analysis
• Hands-on Exercise

Module 26: Statistical Tools

• Quantitative data: Measures of center and variation
• Charting and graphing continuous and discrete data
• Deriving insights from qualitative/nominal data
• Hands-on Exercise

Module 27: Probability Distributions

• Data distribution and normal distribution
• Standard normal distribution and Z-scores
• Confidence intervals: Theory and computation in R
• Hands-on Exercise

Module 28: Statistical Inference

• Hypothesis testing and T-tests
• Non-parametric alternatives to T-tests
• ANOVA and its non-parametric versions
• Power tests
• Hands-on Exercise

Module 29: Relationship Between Two Different Quantitative Variables

• Exploring relationships and correlation
• Linear regression: Theory and implementation in R
• Conditions of linear regression and multi-collinearity
• Linear regression with categorical variables and interaction terms
• Analysis of covariance (ANCOVA)
• Regression model selection and transformation
• Other regression techniques
• Hands-on Exercise

Module 30: Multivariate Analysis

• Introduction to multivariate analysis
• Cluster analysis, PCA, LDA, correspondence analysis
• Similarity and dissimilarity across sites
• Non-metric multi-dimensional scaling (NMDS)
• Multivariate analysis of variance (MANOVA)
• Hands-on Exercise

Module 31: Report Writing for Surveys, Data Dissemination, Demand, and Use

• Writing reports from survey data
• Developing a communication and dissemination strategy
• Improving data use in decision-making
• Cultural Change and change management
• Preparing a report, communication and dissemination plan, and demand and use strategy
• Presentations and joint action planning
• Hands-on Exercise

General Notes

• This course is delivered by seasoned trainers with extensive professional experience in their respective fields.
• Training includes a mix of practical activities, theoretical knowledge, group work, and case studies.
• Participants receive comprehensive training manuals and additional reference materials.
• A certificate is awarded upon successful course completion.
• Custom-tailored courses to meet specific organizational needs are available. Contact us at training@skillsforafrica.org for more information.
• The training will be conducted at the Skills for Africa Training Institute in Nairobi, Kenya.
• The training fee covers tuition, materials, lunch, and the training venue. Accommodation and airport transfer can be arranged upon request.
• Payment should be made to our bank account before the training starts, and proof of payment sent to: training@skillsforafrica.org