Mastering ATLAS.ti for Research Advanced Training Course

Mastering ATLAS.ti for Research Advanced Training Course

Introduction

In today’s data-driven research landscape, qualitative analysis has become a critical skill for academics, industry professionals, and researchers. Mastering ATLAS.ti equips participants with the power to efficiently organize, code, and analyze complex textual, audio, and visual data. Mastering ATLAS.ti for Research Advanced Training Course enables learners to uncover meaningful insights, streamline research workflows, and generate evidence-based conclusions. By integrating cutting-edge qualitative techniques, participants gain a competitive advantage in research design, data interpretation, and reporting.

This intensive training program combines theoretical knowledge with practical applications, providing real-world case studies from healthcare, social sciences, market research, and technology sectors. Participants will develop advanced competencies in coding strategies, network visualization, memo writing, and collaborative research workflows. With a focus on actionable outcomes, the course ensures that learners leave with the confidence to leverage ATLAS.ti for complex research projects, enhance data-driven decision-making, and deliver impactful reports.

Course Duration

10 days

Course Objectives

By the end of this training, participants will be able to:

1. Master ATLAS.ti qualitative coding techniques for efficient data organization.
2. Apply advanced data visualization using network views and relationship mapping.
3. Conduct systematic thematic analysis to uncover research insights.
4. Utilize memo writing strategies for enhanced documentation and reflexivity.
5. Integrate mixed-methods approaches within ATLAS.ti workflows.
6. Design robust coding schemes tailored to specific research questions.
7. Perform comparative case analysis using ATLAS.ti tools.
8. Implement collaborative research workflows for team-based projects.
9. Leverage AI-assisted qualitative analytics for faster insights.
10. Ensure data integrity and reproducibility in qualitative research.
11. Generate customized reports and dashboards for stakeholders.
12. Apply ATLAS.ti techniques to cross-industry case studies.
13. Enhance research productivity and project management using ATLAS.ti features.

Target Audience

• Academic researchers and PhD candidates
• Social science and humanities scholars
• Market researchers and consumer insights analysts
• Healthcare and clinical researchers
• Policy analysts and public sector professionals
• UX/UI and design researchers
• Data analysts seeking qualitative skills
• NGO and development project researchers

Course Modules

Module 1: Introduction to ATLAS.ti

• Overview of ATLAS.ti interface and features
• Understanding qualitative data types
• Project setup and organization
• Importing and managing documents
• Case study: Coding interview transcripts from a social research project

Module 2: Data Management and Organization

• Creating and managing projects
• Organizing documents into groups
• Document versions and updates
• Efficient data retrieval methods
• Case study: Organizing focus group discussions for market research

Module 3: Basic Coding Techniques

• Open coding fundamentals
• Assigning codes to text and multimedia
• Creating and managing code lists
• Code comments and definitions
• Case study: Coding customer feedback for sentiment analysis

Module 4: Advanced Coding Strategies

• Axial and selective coding methods
• Hierarchical and networked codes
• Merging and splitting codes
• Cross-document coding
• Case study: Comparative coding in multi-site qualitative studies

Module 5: Memo Writing and Note-taking

• Creating research memos
• Linking memos to codes and quotations
• Reflective and analytic memo strategies
• Organizing memos for reports
• Case study: Documenting ethnographic observations in field research

Module 6: Network Visualization

• Visualizing code relationships
• Concept mapping and theory development
• Using networks for analysis presentations
• Interactive network exploration
• Case study: Mapping themes in patient experience research

Module 7: Query and Retrieval Functions

• Simple and complex queries
• Boolean and proximity searches
• Combining queries for thematic extraction
• Filtering data effectively
• Case study: Retrieving insights from policy evaluation datasets

Module 8: Mixed-Methods Analysis

• Integrating qualitative and quantitative data
• Linking survey results with coded themes
• Using ATLAS.ti for triangulation
• Data validation techniques
• Case study: Mixed-method analysis in education research

Module 9: Team Collaboration

• Multi-user project management
• Synchronizing team projects
• Conflict resolution in coding
• Audit trails for research accountability
• Case study: Collaborative analysis of NGO field data

Module 10: Reporting and Exporting

• Generating visual and textual reports
• Exporting data to Word, Excel, and PDF
• Customizing output for stakeholders
• Creating dashboards for presentations
• Case study: Presenting market insights to executives

Module 11: Multimedia Analysis

• Coding audio and video data
• Transcription integration
• Analyzing images and diagrams
• Multimedia memo linking
• Case study: Video analysis of classroom interactions

Module 12: Advanced Analytical Techniques

• Pattern recognition and thematic networks
• Sentiment and discourse analysis
• Co-occurrence and cluster analysis
• Integrating AI-assisted insights
• Case study: Identifying emerging trends in social media data

Module 13: Research Design with ATLAS.ti

• Aligning coding with research questions
• Developing conceptual frameworks
• Documenting methodology in ATLAS.ti
• Ensuring reproducibility
• Case study: Designing a longitudinal qualitative study

Module 14: Troubleshooting & Best Practices

• Common project issues and solutions
• Code consistency strategies
• Version control techniques
• Optimizing project performance
• Case study: Resolving complex coding conflicts in collaborative projects

Module 15: Capstone Project

• Hands-on project integrating all skills
• Real-world dataset analysis
• Presentation of findings using ATLAS.ti
• Peer review and feedback sessions
• Case study: Comprehensive analysis of healthcare service improvement data

Training Methodology

This course employs a participatory and hands-on approach to ensure practical learning, including:

• Interactive lectures and presentations.
• Group discussions and brainstorming sessions.
• Hands-on exercises using real-world datasets.
• Role-playing and scenario-based simulations.
• Analysis of case studies to bridge theory and practice.
• Peer-to-peer learning and networking.
• Expert-led Q&A sessions.
• Continuous feedback and personalized guidance.

Register as a group from 3 participants for a Discount

Send us an email: info@datastatresearch.org or call +254724527104 

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

 We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.