Introduction

The "Research Design, ODK Mobile Data Collection, GIS Mapping, Data Analysis using NVIVO and R" course is a comprehensive and multi-faceted training program designed to equip participants with the essential skills and knowledge required to conduct effective research, collect data using mobile technology, employ geographic information systems (GIS) for data visualization, and analyze data using advanced tools such as NVIVO and R. This course is an ideal choice for individuals seeking to build a strong foundation in research methodology, data collection, and data analysis techniques.

In the first part of the course, participants will delve into the critical aspects of research design, exploring the various types of research methodologies and designs available. They will learn how to formulate research questions, choose appropriate research methods, and develop a structured research plan. This foundational knowledge will serve as the basis for the subsequent modules, ensuring that participants have a solid understanding of the research process.

The course then transitions to the practical realm of data collection, focusing on the use of mobile data gathering tools like ODK. Participants will gain hands-on experience in designing mobile surveys, configuring devices, and effectively managing data collection projects. This practical training prepares them to harness the power of mobile technology for collecting data efficiently and accurately in real-world research scenarios.

Course Objectives:

1. Equip participants with a comprehensive understanding of various research design methodologies and the ability to select the most appropriate one for their research projects.
2. Provide practical training in designing and implementing mobile data collection using ODK (Open Data Kit) and similar platforms.
3. Enable participants to use GIS mapping for spatial data visualization and analysis, enhancing their ability to analyze geographical aspects of research.
4. Develop proficiency in qualitative data analysis using NVIVO, including coding, thematic analysis, and interpretation of results.
5. Introduce participants to statistical modeling using R, covering a range of statistical techniques and data visualization.
6. Foster a deep understanding of the principles of research ethics, ensuring that participants conduct research in an ethical and responsible manner.
7. Enhance participants' problem-solving and critical-thinking skills in the context of research and data analysis.
8. Provide hands-on experience in the creation of research reports and data dissemination strategies, emphasizing the importance of effective communication.
9. Equip participants with the knowledge and tools to triangulate results from various data sources for robust research outcomes.
10. Empower participants to apply their newly acquired skills to practical research projects, contributing to improved decision-making and problem-solving in their professional roles.

Organizational Benefits:

1. Enhanced Research Competency: The organization will benefit from a workforce equipped with advanced research skills, enabling them to design and execute high-quality research projects.
2. Improved Data Collection: Mobile data collection techniques will lead to more efficient and accurate data collection processes, reducing errors and increasing data quality.
3. Enhanced Geographic Insights: GIS mapping capabilities will allow the organization to gain valuable geographic insights for better-informed decision-making.
4. Qualitative Data Analysis: Proficiency in NVIVO will enable in-depth analysis of qualitative data, offering a more profound understanding of complex issues.
5. Advanced Statistical Analysis: With R, the organization can perform sophisticated statistical analyses and create data-driven visualizations for strategic planning.
6. Ethical Research Practices: Ensuring ethical research practices will enhance the organization's reputation and promote responsible research.
7. Problem-Solving Capacity: The course will improve employees' problem-solving and critical-thinking skills, contributing to better decision-making in the workplace.
8. Effective Communication: Participants will be better equipped to create compelling research reports and strategies for data dissemination, improving internal and external communication.
9. Data Triangulation: The ability to triangulate data from various sources will lead to more robust and reliable research outcomes.
10. Applied Knowledge: Employees will apply their newfound skills to organizational research projects, contributing to the organization's success.

Target Participants:

1. Research professionals and analysts looking to enhance their skills.
2. Data collection specialists interested in adopting mobile data collection methods.
3. GIS specialists and geographic analysts seeking to expand their knowledge.
4. Qualitative researchers and social scientists.
5. Statisticians and data analysts.
6. Academics and students in research-related disciplines.
7. NGOs and government agency personnel involved in data collection and analysis.
8. Public health professionals conducting research and surveys.
9. Market researchers and analysts.
10. Anyone interested in advancing their research and data analysis skills for personal or professional growth.

Introduction

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 a research method
• Exercise: Identifying a research project and developing a research design

Module 3: Survey Planning, Implementation, and Completion

• Types of surveys
• The survey process
• Survey design
• Survey sampling methods
• Sample size determination
• Planning and conducting surveys

Module 4: Introduction

• Introduction to Mobile Data gathering
• Benefits of Mobile Applications
• Data types and common mobile data collection platforms
• Managing devices
• Challenges of Data Collection
• Data aggregation, storage, and dissemination
• Question types and data types
• Questionnaire and form logic

Module 5: Survey Authoring

• Designing forms using web interfaces (ODK Build, Koboforms, PurcForms)
• Hands-on Exercise

Module 6: Preparing the mobile phone for data collection

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

Module 7: Designing forms manually: Using XLS Forms

• Introduction to XLS forms syntax
• New data types
• Multiple choice Questions
• Multiple Language Support
• Hints and Metadata
• Hands-on Exercise

Module 8: Advanced survey Authoring

• Conditional Survey Branching
• Grouping questions
• Repeating a set of questions
• Special formatting
• Dynamic calculations

Module 9: Hosting survey data (Online)

• ODK Aggregate
• Formhub
• ona.io
• KoboToolbox
• Uploading forms to the server

Module 10: Hosting Survey Data (Configuring a local server)

• Configuring ODK Aggregate on a local server
• Downloading data
• Manual download (ODK Briefcase)
• Using the online server interface

Module 11: GIS mapping of survey data using QGIS

• Introduction to GIS for Researchers and data scientists
• Importing survey data into a GIS
• Mapping survey data using QGIS
• QGIS mapping exercise

Module 12: Understanding Qualitative Research

• Qualitative Data
• Types of Qualitative Data
• Sources of Qualitative data
• Qualitative vs Quantitative
• NVivo key terms
• The NVivo Workspace

Module 13: Preliminaries of Qualitative data Analysis

• What is qualitative data analysis
• Approaches in Qualitative data analysis
• Principles of Qualitative data analysis
• Process of Qualitative data analysis

Module 14: Introduction to NVIVO

• NVIVO Key terms
• NVIVO interface
• NVIVO workspace
• Use of NVIVO ribbons

Module 15: NVIVO Projects

• Creating new projects
• Working with Qualitative data files
• Importing Documents
• Managing projects
• Working with different data sources

Module 16: Nodes in NVIVO

• Theme codes
• Case nodes
• Relationships nodes
• Node matrices
• Creating nodes
• Browsing Nodes
• Creating Memos

Module 17: Classes and summaries

• Source classifications
• Case classifications
• Node classifications
• Creating Attributes within NVivo
• Importing Attributes from a Spreadsheet
• Coding Query and Matrix Query

Module 18: Coding

• Data-driven vs theory-driven coding
• Analytic coding
• Descriptive coding
• Thematic coding
• Tree coding

Module 19: Thematic Analytics in NVIVO

• Organizing, storing, and retrieving data
• Cluster sources based on the words they contain
• Text searches and word counts
• Examining themes and structure in content

Module 20: Queries using NVIVO

• Queries for textual analysis
• Queries for exploring coding

Module 21: Building on the Analysis

• Content Analysis
• Narrative Analysis
• Discourse Analysis
• Grounded Theory

Module 22: Qualitative Analysis Results Interpretation

• Comparing analysis results with research questions
• Summarizing findings
• Drawing conclusions and lessons learned

Module 23: Visualizing NVIVO project

• Displaying data in charts
• Creating models and graphs to visualize connections
• Tree maps and cluster analysis diagrams
• Creating reports and extracts

Module 24: Triangulating results and Sources

• Triangulating with quantitative data
• Comparing analysis from different data sources

Module 25: Report Writing

• Qualitative report format
• Reporting qualitative research
• Reporting content
• Interpretation

Module 26: Basics of Applied Statistical Modeling using R

• Introduction to the course and R
• Data & Code Used in the Course
• Statistics in the Real World
• Designing Studies & Collecting Good Quality Data
• Different Types of Data

Module 27: Essentials of R Programming

• Introduction to R and R Studio
• Data Structures in R
• Data Reading and Cleaning
• Exploratory Data Analysis in R

Module 28: Statistical Tools

• Quantitative Data Analysis
• Measures of Center and Variation
• Charting & Graphing Data
• Insights from Qualitative/Nominal Data

Module 29: Probability Distributions

• Normal Distribution and Checking
• Confidence Intervals

Module 30: Statistical Inference

• Hypothesis Testing
• T-tests, ANOVA, Regression
• Power Testing

Module 31: Relationship between Two Different Quantitative Variables

• Exploring Relationships
• Correlation and Linear Regression

Module 32: Multivariate Analysis

• Cluster Analysis
• Principal Component Analysis
• Linear Discriminant Analysis
• Correspondence Analysis
• Multivariate Analysis of Variance

Module 33: Report writing for surveys, data dissemination, demand, and use

• Writing a report from survey data
• Communication and dissemination strategy
• Improving data use in decision making
• Preparing a report, communication plan, and demand and use strategy.

General Information

1. Customized Training: All our courses can be tailored to meet the specific needs of participants.
2. Language Proficiency: Participants should have a good command of the English language.
3. Comprehensive Learning: Our training includes well-structured presentations, practical exercises, web-based tutorials, and collaborative group work. Our facilitators are seasoned experts with over a decade of experience.
4. Certification: Upon successful completion of training, participants will receive a certificate from Foscore Development Center (FDC-K).
5. Training Locations: Training sessions are conducted at Foscore Development Center (FDC-K) centers. We also offer options for in-house and online training, customized to the client's schedule.
6. Flexible Duration: Course durations are adaptable, and content can be adjusted to fit the required number of days.
7. Onsite Training Inclusions: The course fee for onsite training covers facilitation, training materials, two coffee breaks, a buffet lunch, and a Certificate of Successful Completion. Participants are responsible for their travel expenses, airport transfers, visa applications, dinners, health/accident insurance, and personal expenses.
8. Additional Services: Accommodation, pickup services, freight booking, and visa processing arrangements are available upon request at discounted rates.
9. Equipment: Tablets and laptops can be provided to participants at an additional cost.
10. Post-Training Support: We offer one year of free consultation and coaching after the course.
11. Group Discounts: Register as a group of more than two and enjoy a discount ranging from 10% to 50%.
12. Payment Terms: Payment should be made before the commencement of the training or as mutually agreed upon, to the Foscore Development Center account. This ensures better preparation for your training.
13. Contact Us: For any inquiries, please reach out to us at training@fdc-k.org or call us at +254712260031.

14.  Website: Visit our website at www.fdc-k.org for more information.