lecture 2 : qualitative research & mixed-method research (MMR)

Research Methodology Fundamentals: Quantitative vs. Qualitative
📌 Research is primarily divided into two methods: Qualitative Method (เชิงคุณภาพ) and Quantitative Method (เชิงปริมาณ).
🔬 The objective is for students to distinguish between these two types of research, understand their limitations, and know when to use them separately or combined.
🧪 Quantitative research focuses on measurable, numerical data (e.g., viscosity measurements), while qualitative research focuses on subjective understanding, context, and personal experiences (e.g., assessing the aesthetic satisfaction of a formulation using subjective scales).

Quantitative Research Characteristics
🔢 Quantitative research aims to convert all aspects into measurable numbers, relying on objective data collection.
🔬 Its strength lies in generalizability (representativeness of a population) and replicability (ability to repeat the study with similar results).
📉 Limitations include oversimplification and the inability to capture the depth of context or subjective realities.

Qualitative Research Characteristics
💬 Qualitative research seeks subjectivity, personal identity, and the underlying reasons (why and how) behind actions or beliefs.
✍️ Data collection often involves in-depth interviews, focus groups, observation, or document analysis, resulting in rich, textual data.
🚫 Key disadvantages are that results are not easily generalizable and the process is time-consuming and resource-intensive.

Mixed Methods Research (MMR)
🤝 MMR combines quantitative and qualitative data collection to gain a broader understanding, avoiding the necessity of choosing only one paradigm.
🔺 A key principle in MMR is triangulation, which uses both data sets to confirm (or contrast) the findings' validity and accuracy.
📉 The main challenge of MMR is the increased demand on resources (time, funding) and complexities in data analysis, especially if findings from both methods conflict.

Qualitative Data Analysis Process
📑 The analysis of qualitative data requires systematic organization, often starting with transcription (e.g., using AI tools for initial drafts).
🗂️ The core steps involve coding (highlighting important text segments) and then organizing these codes into themes or categories (thematic analysis).
💡 The researcher must be highly aware of their own subjectivity, as they are the primary research instrument; this necessitates strong justification for interpretation and methodology (credibility and dependability).

Key Points & Insights
➡️ The crucial decision in research design is selecting the method (Quantitative, Qualitative, or Mixed) based on the research question and the desired type of outcome (numbers vs. deep understanding).
➡️ Qualitative research thrives on exploratory questions seeking the *why* and *how*, often leading to the development of new theories (Grounded Theory).
➡️ When conducting qualitative analysis, ensure data saturation (no new information emerging) before stopping data collection, and use clear reporting guidelines (like COREQ checklist for interviews) for trustworthiness.

📸 Video summarized with SummaryTube.com on Jan 17, 2026, 09:32 UTC