Course Outline

Module 1: Introduction to Research Design

• Overview of research design principles and methodologies
• Developing research questions and hypotheses
• Selecting appropriate research designs (qualitative, quantitative, mixed methods)
• Understanding sampling techniques and sample size determination
• Case Study: Design a research project from scratch, including research questions, design, and sampling strategy.

Module 2: SurveyCTO for Mobile Data Collection

• Introduction to SurveyCTO and its features
• Setting up a SurveyCTO account and project
• Designing and building mobile surveys with SurveyCTO
• Pre-testing and deploying surveys on mobile devices
• Case Study: Develop and deploy a mobile survey using SurveyCTO to collect data in the field.

Module 3: Data Management and Quality Control in SurveyCTO

• Managing data collection projects on SurveyCTO
• Implementing data validation and quality control measures
• Real-time monitoring and troubleshooting during data collection
• Exporting and managing collected data
• Case Study: Implement quality control measures and export data from a completed SurveyCTO survey for analysis.

Module 4: Introduction to GIS Mapping

• Basics of Geographic Information Systems (GIS) and spatial data
• Understanding coordinate systems and map projections
• Collecting and preparing spatial data for analysis
• Introduction to GIS software tools (e.g., QGIS)
• Case Study: Prepare and visualize spatial data related to survey responses on a GIS platform.

Module 5: GIS Mapping and Spatial Analysis

• Creating thematic maps and spatial visualizations
• Conducting spatial analysis (e.g., proximity analysis, hot spot analysis)
• Integrating survey data with GIS maps
• Advanced GIS tools for spatial data analysis
• Case Study: Analyze spatial distribution of survey data and create thematic maps to illustrate key findings.

Module 6: Introduction to NVivo for Qualitative Data Analysis

• Overview of NVivo software and its applications in qualitative research
• Setting up a new NVivo project and importing qualitative data
• Coding and categorizing qualitative data
• Analyzing and visualizing qualitative data in NVivo
• Case Study: Import interview transcripts into NVivo, code the data, and identify key themes for analysis.

Module 7: Advanced NVivo Techniques and Mixed Methods Analysis

• Conducting mixed methods analysis in NVivo (combining qualitative and quantitative data)
• Advanced data visualization in NVivo (e.g., word clouds, cluster analysis)
• Comparative analysis across different datasets
• Reporting and exporting NVivo analysis results
• Case Study: Perform a mixed methods analysis in NVivo, integrating survey data with qualitative insights.

Module 8: Introduction to Python for Data Analysis

• Basics of Python programming and its applications in data analysis
• Setting up a Python environment (using Jupyter notebooks, Anaconda)
• Importing and managing data in Python (e.g., pandas, NumPy)
• Basic data visualization with Python (e.g., Matplotlib, Seaborn)
• Case Study: Write Python scripts to clean and visualize a dataset related to your research project.

Module 9: Advanced Data Analysis with Python

• Performing statistical analysis using Python (e.g., regression, hypothesis testing)
• Data manipulation and transformation techniques (e.g., merging, reshaping data)
• Automating data analysis workflows with Python scripts
• Integrating Python with other tools (e.g., GIS, NVivo)
• Case Study: Develop a Python script to automate data cleaning, analysis, and visualization for a complex dataset.

Module 10: Reporting and Presenting Research Findings

• Structuring research reports and presentations
• Visualizing data for reports (integrating SurveyCTO, GIS, NVivo, and Python outputs)
• Writing clear and concise research findings
• Preparing presentations and sharing results with stakeholders
• Case Study: Compile a comprehensive report combining data from SurveyCTO, GIS mapping, NVivo analysis, and Python scripts, and prepare a presentation for stakeholders.