Lecture 9

From Phenomenology to Research Design

This final lecture in the unit connects the foundational practice of phenomenology directly to the practical task of designing research for your Data Science Final Project (DSFP).

The Pre-Launch Moment

Core Concept: Phenomenology prepares you to design meaningful research by grounding your inquiry in lived experience before you choose methods or collect data.

You've learned to see, describe, and interpret the lifeworld with discipline. Now we ask: How does this make you a better social data scientist?

From Lifeworld to Research Questions

Core Concept: Strong research questions grow from careful observation of the lifeworld, rather than from assumptions or vague curiosity.

Phenomenology helps you ask: “What is happening here that needs to be understood?” This comes *before* selecting methods or data.

Think about a social issue you care about. What specific observations or experiences in the lifeworld would lead you to formulate a research question about it?

From Meaning to Variables

Core Concept: Phenomenological thinking ensures that research variables are meaningful by prompting us to consider the lived experience they represent.

Variables are not neutral. They are defined and interpreted. Phenomenology asks: What experience does this variable represent? Who recognizes this category? This ensures our variables are well-grounded.

Measurement Without Distortion

Core Concept: Phenomenology cultivates awareness of the inherent simplification in all measurement, helping researchers respect the limits of their data and avoid distorting lived experience.

All measurement simplifies reality. Good research respects its own limits and avoids flattening lived experience by acknowledging what data cannot capture.

The Research Stance You Carry Forward

Core Concept: The phenomenological stance of a grounded observer and responsible interpreter is essential for ethical and insightful quantitative data analysis.

This stance—careful, grounded, and accountable—does not disappear when statistics begin. It becomes even more critical for meaningful data science.

How might consciously adopting an "ethical stance" change the way you approach a research project or even an everyday conversation? What new responsibilities emerge?

Phenomenology as the Runway

Core Concept: Phenomenology does not replace data science tools; it prepares them to be used well, ensuring that analysis is grounded in real-world context and human experience.

Think of phenomenology as the "runway" that ensures a safe and intentional "takeoff" into your Data Science Final Project.

Final Orientation

Core Concept: The goal of this unit was to learn how to study the world you already live in with care, discipline, and responsibility.

This was not about self-expression, but about world-awareness. You are now ready to move forward into the DSFP.