SubmoduleCourse Learning Outcomes (CLOs)ActivitiesFormative AssessmentToolsFeedback Approach1. Foundations of Qualitative Research and ATLAS.ti- Explain the principles of qualitative data analysis.
- Demonstrate basic navigation and project setup in ATLAS.ti.
- Import and organize textual/multimedia data.- Guided tutorial: QDA concepts.
- Video demo: Project setup in ATLAS.ti.
- Hands-on: Import interview transcripts.- Quiz on QDA fundamentals.
- Task: Set up a project and upload data.- ATLAS.ti (trial/student license).
- Sample dataset.- Automated quiz feedback.
- Instructor comments on project setup (with annotated screenshots).2. Coding, Categorization, and AI-Enhanced Analysis- Apply manual and AI-assisted coding.
- Organize codes into categories and themes.
- Use AI tools for clustering, sentiment analysis, memoing.- Workshop: Manual vs. AI coding.
- Activity: Code transcript manually and via AI.
- Group activity: Compare/refine themes.- Coding assignment: Submit coded document.
- Reflection memo: Evaluate AI’s role in coding.- ATLAS.ti AI auto-coding & pattern recognition.
- Online forum for peer discussion.- Peer review of coded samples.
- Instructor narrative feedback on coding strategy.3. Visualization, Interpretation, and Reporting- Generate visual outputs (networks, word clouds, co-occurrence tables).
- Interpret insights with AI-assisted analysis.
- Produce a qualitative findings report.- Tutorial: Creating visualizations in ATLAS.ti.
- Activity: Build at least two visuals.
- Workshop: Write structured findings with quotes, memos, AI summaries.- Portfolio: Mini qualitative report (2–3 pages) with visuals.
- Recorded oral presentation of findings.- ATLAS.ti visualization suite.
- AI-supported summary tools.