A teaching note on mixed methods research (a kind of research approach)
A teaching note on mixed methods research (a kind of research approach) (information from perplexity.ai)
My question 1: "Regarding the subject of Research Methods for social science, highlight 6 ideas of the research approach of the mixed methods research. And then discuss briefly 3 useful practices to deal with the issues arising from using both qualitative and quantitative research in the same dissertation project."
The reply: "Mixed methods research in social science integrates both qualitative and quantitative approaches, providing a comprehensive understanding of research problems. Here are 6 key ideas about the research approach of mixed methods research:
Combination of Quantitative and Qualitative Methods: Mixed methods research combines elements of quantitative research (numerical, generalizable, structured) and qualitative research (in-depth, contextual, subjective) to address complex social phenomena comprehensively. This allows researchers to explore both the measurable trends and the underlying meanings or experiences.
Complementarity and Synergy: The approach leverages the strengths of both qualitative and quantitative methods, where quantitative data gives breadth and generalizability, and qualitative data adds depth and context. This synergy provides richer insights than either method alone.
Enhanced Validity through Triangulation: By collecting and comparing data from different methods on the same subject, the validity and credibility of findings improve owing to data triangulation. Convergent results yield stronger, more robust conclusions.
Flexibility and Complexity Management: Mixed methods research is flexible, less bound by strict paradigms, and can address complex research issues involving multiple variables and contexts. It enables exploring cause-effect relationships and contextual layers simultaneously.
Iterative Theory Development: Quantitative data can identify patterns prompting hypotheses, while qualitative data helps validate or refine these. This iterative process supports robust theory development in social science.
Research Design Variants: Common mixed methods designs include convergent parallel (collect quantitative and qualitative data simultaneously), explanatory sequential (quantitative followed by qualitative to explain results), and exploratory sequential (qualitative followed by quantitative to test hypotheses). Researchers select designs based on research questions and resource availability.
Regarding useful practices to handle issues arising from combining qualitative and quantitative methods in a dissertation:
Clear Integration Plan: Establish at the outset how the qualitative and quantitative data will be integrated and related throughout the research process, including how to compare and synthesize findings coherently to avoid bias or misinterpretation.
Adequate Researcher Expertise and Collaboration: Ensure that the research team has or acquires skills in both qualitative and quantitative methods. Interdisciplinary collaboration or additional training may be necessary to maintain rigor and successfully manage the mixed methods approach.
Resource and Time Management: Recognize that mixed methods research is resource-intensive involving data collection, analysis, and synthesis of two types of data. Plan accordingly for sufficient time, personnel, and budget to complete the study without compromising quality.
These practices help address challenges such as complexity of data integration, needed expertise, and resource demands to produce a coherent and rigorous dissertation project using mixed methods.
In sum, mixed methods research merges the breadth of quantitative data with the depth of qualitative data for enriched understanding, while careful planning and expertise handling mitigate the challenges of combining these approaches in social science research.
My question 2: "Regarding useful practices to handle issues arising from combining qualitative and quantitative methods in a dissertation, could you clarify your ideas a bit more in the context of the following research themes:
The reply: "Clarifying Integration Practices in Mixed Methods Research
Let's explore how to practically address issues that arise from combining qualitative and quantitative methods for two specific dissertation themes:
Housing Studies: “Types of domestic violence and causal factors in the public housing estate of Wong Tai Sin, Hong Kong, 2025.”
MBA Leadership: “Types of leadership style and the preference of Gen Z managerial staff of 5-star hotels in Hong Kong, 2025.”
1. Clear Integration Plan
Housing Example:
Integration: If using surveys to quantify the prevalence of different types of domestic violence, and interviews for in-depth stories of causality, plan upfront how to compare the numerical data with qualitative explanations. For example, you could use a convergent parallel design: collect both survey data and interviews at the same time, then compare which causal factors appear in both.
Why it's important: Domestic violence is often hidden. Survey data might reveal trends, but interviews can highlight underlying causes or community factors not visible in statistics—combining both can illuminate how features unique to Wong Tai Sin (e.g., neighborliness, community detachment) impact domestic violence.
MBA Example:
Integration: Use structured questionnaires to map Gen Z managers’ preferred leadership styles, then conduct focus groups to unpack why those preferences exist. Plan to link the survey results (preference trends) with qualitative insights (motivations and contextual factors) to provide a nuanced narrative.
Why it's important: Gen Z’s values may shift the meaning of “leadership”—combining methods helps surface both the ‘what’ and the ‘why’.
2. Adequate Researcher Expertise and Collaboration
Housing Example:
Practice: Domestic violence is sensitive and complex. Ensure you (or your team) are trained in both statistical analysis and qualitative interviewing (possibly trauma-informed), and consider collaborating with social workers or support organizations for access and trust.
Why: This boosts credibility and ensures that subtle signals in interview data (e.g., reluctance, euphemisms) aren’t missed, and that survey instruments are culturally tuned for the district.
MBA Example:
Practice: Gen Z leadership preferences may be shaped by dynamic workplace trends. If unfamiliar with their digital culture, collaborate with HR professionals or young hotel managers for authentic data collection and relevant analysis.
Why: Reduces the risk of misinterpreting qualitative terms, improves quantitative survey design, and facilitates meaningful synthesis.
3. Resource and Time Management
Housing Example:
Practice: Mixed methods can be resource-intensive. In Wong Tai Sin, arranging confidential interviews on domestic violence will take time (building trust, securing privacy, navigating gatekeepers), while surveys require careful distribution (possibly through local community centers or housing management).
Why: Without careful planning, you might run out of time or lose access to key informants—schedule buffer periods and budget for outreach.
MBA Example:
Practice: Hotel managers in 5-star hotels are often busy and hard to reach. Select optimal times for survey distribution and group interviews, and plan for potential delays or data gaps. Possibly align with hotel HR departments’ staff meetings for access.
Why: Ensures meaningful participation and completion of both survey and qualitative phases.
Quick Review
Integration Planning: Decide upfront how you’ll compare numbers and stories, ideally using a design that fits your theme.
Expertise & Collaboration: Team up if you lack skills in both methods or need local knowledge.
Resource Management: Anticipate time and logistical hurdles in collecting sensitive or busy-person data."
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