Research Design, SurveyCTO Mobile Data Collection, GIS Mapping Data Analysis using NVIVO and PYTHON

Research Design, SurveyCTO Mobile Data Collection, GIS Mapping Data Analysis using NVIVO and PYTHON

Introduction:

Welcome to the Research Design, SurveyCTO Mobile Data Collection, GIS Mapping, and Data Analysis using NVivo and Python course! In today's dynamic research landscape, mastering a diverse set of tools and methodologies is essential for conducting impactful research studies. This course is designed to equip participants with the skills and knowledge necessary to design robust research studies, collect data using SurveyCTO for mobile data collection, leverage GIS mapping for spatial analysis, and perform qualitative and quantitative data analysis using NVivo and Python, respectively. Whether you're a researcher, academic, or practitioner, mastering these tools and techniques will empower you to conduct rigorous and comprehensive research studies in various domains.


Course Objectives:

  1. Research Design Proficiency: Develop proficiency in research design principles, including conceptualization, operationalization, and hypothesis formulation, to lay a solid foundation for designing research studies.
  2. SurveyCTO Mobile Data Collection: Learn how to design, implement, and manage data collection using SurveyCTO, a powerful tool for mobile data collection in both online and offline environments.
  3. GIS Mapping Techniques: Develop skills in GIS mapping techniques for spatial analysis, including data visualization, spatial querying, and spatial analysis using geographic information systems.
  4. Qualitative Data Analysis with NVivo: Explore qualitative data analysis techniques using NVivo, including coding, thematic analysis, and visualization, to derive meaningful insights from qualitative data.
  5. Quantitative Data Analysis with Python: Master quantitative data analysis techniques using Python programming language, including data manipulation, statistical analysis, and visualization, to analyze and interpret quantitative data effectively.


Organization Benefits:

  1. Enhanced Research Capabilities: Equipping employees with a comprehensive understanding of research design principles and tools such as SurveyCTO, GIS, NVivo, and Python enhances the organization's research capabilities, enabling more rigorous and impactful research studies.
  2. Increased Efficiency and Productivity: Utilizing tools such as SurveyCTO for mobile data collection, GIS mapping for spatial analysis, and NVivo and Python for data analysis streamlines research processes, leading to increased efficiency, productivity, and reproducibility in research workflows.
  3. Improved Data Quality and Rigor: Leveraging SurveyCTO for mobile data collection ensures data quality and integrity, while GIS mapping enables spatial analysis and visualization, enhancing the rigor and reliability of research findings.
  4. Facilitated Collaboration and Knowledge Sharing: Integration of SurveyCTO, GIS, NVivo, and Python facilitates collaboration and knowledge sharing among research teams, enabling seamless data exchange, analysis, and interpretation.
  5. Enhanced Decision-Making and Strategic Planning: Evidence-based decision-making and strategic planning are facilitated by the ability to collect, analyze, and interpret both qualitative and quantitative data using SurveyCTO, GIS, NVivo, and Python, informing organizational strategies, policies, and initiatives.



Target Participants:

 This course is suitable for researchers, academics, practitioners, and students across various disciplines who are involved in research projects and wish to enhance their skills in research design, data collection, GIS mapping, and data analysis using SurveyCTO, GIS, NVivo, and Python, respectively. Target participants include social scientists, environmental researchers, public health professionals, urban planners, and anyone else interested in conducting rigorous and impactful research studies.


Course Outline:

  1. Introduction to Research Design Principles
    • Overview of research methodology and research design principles
    • Conceptualization, operationalization, and hypothesis formulation
    • Case Study: Designing a research study on community health interventions
  2. SurveyCTO Mobile Data Collection
    • Introduction to SurveyCTO and its features for mobile data collection
    • Designing forms and surveys in SurveyCTO Build
    • Implementing data collection using SurveyCTO Collect
    • Case Study: Conducting a household survey using SurveyCTO for data collection
  3. GIS Mapping Techniques
    • Introduction to GIS mapping and spatial analysis concepts
    • Data visualization and thematic mapping using GIS software (e.g., QGIS)
    • Spatial querying and analysis techniques
    • Case Study: Mapping disease outbreaks using GIS for spatial analysis
  4. Qualitative Data Analysis with NVivo
    • Introduction to qualitative data analysis and NVivo software
    • Importing and coding qualitative data in NVivo
    • Thematic analysis and visualization techniques
    • Case Study: Analyzing focus group discussions using NVivo for qualitative data analysis
  5. Quantitative Data Analysis with Python
    • Introduction to Python programming language and environment for data analysis
    • Data manipulation and cleaning using Python libraries (e.g., Pandas)
    • Statistical analysis and visualization using Python libraries (e.g., NumPy, Matplotlib)
    • Case Study: Analyzing survey data on consumer preferences using Python for quantitative data analysis
  6. Advanced Analysis Techniques in NVivo
    • Advanced coding techniques (e.g., pattern-based coding, matrix coding)
    • Inter-rater reliability and qualitative data validation
    • Visualizing qualitative data using NVivo queries
    • Case Study: Conducting a content analysis of interview transcripts using advanced NVivo techniques
  7. Advanced Analysis Techniques in Python
    • Inferential statistics (e.g., t-tests, ANOVA, regression analysis) using Python libraries (e.g., SciPy)
    • Machine learning algorithms for predictive modeling using Python libraries (e.g., Scikit-learn)
    • Interpretation and reporting of quantitative analysis results
    • Case Study: Conducting regression analysis to examine predictors of customer satisfaction using Python
  8. Mixed-Methods Research Design
    • Overview of mixed-methods research design
    • Integrating qualitative and quantitative data collection and analysis
    • Triangulation and convergence of findings
    • Case Study: Designing a mixed-methods study on educational interventions
  9. Data Integration and Synthesis
    • Integrating data from multiple sources (e.g., SurveyCTO, GIS, NVivo, Python)
    • Synthesizing qualitative and quantitative findings
    • Drawing conclusions and implications from integrated data
    • Case Study: Integrating data from SurveyCTO surveys, GIS mapping, NVivo analysis, and Python analysis for comprehensive research synthesis
  10. Ethical Considerations in Research
    • Overview of ethical principles in research
    • Ethical considerations in data collection, analysis, and reporting
    • Case Study: Addressing ethical challenges in research on vulnerable populations
  11. Research Dissemination and Impact
    • Strategies for disseminating research findings
    • Communicating research findings to diverse audiences
    • Measuring research impact and engagement
    • Case Study: Developing a research dissemination plan for a community-based intervention study
  12. Project Management and Collaboration
    • Project planning and management best practices
    • Collaboration tools and platforms for research teams
    • Case Study: Managing a research project using project management software and collaborative platforms
  13. Research Proposal Development
    • Writing effective research proposals
    • Components of a research proposal (e.g., introduction, literature review, methodology)
    • Case Study: Developing a research proposal for funding submission

Essential Information

 

  1. Our courses are customizable to suit the specific needs of participants.
  2. Participants are required to have proficiency in the English language.
  3. Our training sessions feature comprehensive guidance through presentations, practical exercises, web-based tutorials, and collaborative group activities. Our facilitators boast extensive expertise, each with over a decade of experience.
  4. Upon fulfilling the training requirements, participants will receive a prestigious Global King Project Management certificate.
  5. Training sessions are conducted at various Global King Project Management Centers, including locations in Nairobi, Mombasa, Kigali, Dubai, Lagos, and others.
  6. Organizations sending more than two participants from the same entity are eligible for a generous 20% discount.
  7. The duration of our courses is adaptable, and the curriculum can be adjusted to accommodate any number of days.
  8. To ensure seamless preparation, payment is expected before the commencement of training, facilitated through the Global King Project Management account.
  9. For inquiries, reach out to us via email at [email protected] or by phone at +254 114 830 889.
  10. Additional amenities such as tablets and laptops are available upon request for an extra fee. 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 arranging and covering their travel expenses, including airport transfers, visa applications, dinners, health insurance, and any other personal expenses.

Course Date Duration Location Registration
10/06/2024 To 21/06/2024 10 Days Dubai, UAE
08/07/2024 To 19/07/2024 10 Days Nairobi Kenya
05/08/2024 To 16/08/2024 10 Days Nairobi Kenya
02/09/2024 To 13/09/2024 10 Days Nairobi Kenya
30/09/2024 To 11/10/2024 10 Days Mombasa, Kenya
28/10/2024 To 08/11/2024 10 Days Nairobi Kenya
25/11/2024 To 06/12/2024 10 Days Nanyuki, Kenya
23/12/2024 To 03/01/2025 10 Days Nairobi Kenya