A note on the concepts in thematic analysis with illustrative examples: for Housing Studies students

A note on the concepts in thematic analysis with illustrative examples: for Housing Studies students (information from perplexity.ai)

My question: "Regarding the topic of thematic analysis in the context of Housing Studies, please clarify a bit what is a code and what is theme? How to link up the themes to address a specific research question? To clarify these concepts and tasks in a more concrete way, try to provide illustrative examples with reference to the following research activity:

To conduct a semi-structured research interview on 6 public estate residents in Tsuen Wan on "what factors and conditions can increase domestic violence of the residents and on what kinds of domestic violence in this regard."

The reply: "Let's break down thematic analysis focusing on codes and themes within your context: interviews with six Tsuen Wan public estate residents on factors increasing domestic violence and types of such violence.

Codes are simple, descriptive labels assigned to meaningful segments of your data — essentially tags or shorthand that capture key ideas in text snippets. For instance, when a resident says, "Neighbors fighting late at night," you might code this segment as "noise disturbance" or "community tension."

Themes are broader, more abstract patterns that emerge when you group related codes. They tell a larger story related to your research question. For example, codes like "noise disturbance," "lack of privacy," and "stress from overcrowding" might come together to form a theme titled "Environmental Stressors Contributing to Domestic Violence."

To link themes to your research question—"What factors and conditions increase domestic violence among these residents and what types occur?"—you identify themes that directly answer these parts. Themes organize your data into meaningful categories that respond to "factors/conditions" (e.g., "Financial Strain and Unemployment") and "types of violence" (e.g., "Verbal Abuse Patterns").

This process builds from:

1. Coding: Labeling relevant bits of interview transcripts.

2. Grouping Codes: Finding patterns or connections among codes.

3. Developing Themes: Abstracting larger concepts to answer your research question."

A collection of blog notes on using chatgpt for research purpose.

A note on the concepts in thematic analysis with illustrative examples: for MBA students

A note on the concepts in thematic analysis with illustrative examples: for MBA students (information from perplexity.ai)

My question: "Regarding the topic of thematic analysis, please clarify a bit what is a code and what is theme? How to link up the themes to address a specific research question? To clarify these concepts and tasks in a more concrete way, try to provide illustrative examples with reference to the following research activity:

To conduct a semi-structured research interview on 4 secretaries in the Faculty of Engineering of the ABC University on "the leadership style and effectiveness of the Faculty Head."

The reply: "Let's dive into thematic analysis, focusing on what codes and themes are, and how they relate to your research question. In thematic analysis:

• A code is a concise label that identifies an important piece of information within your data, like a keyword or concept from an interview segment.

• A theme is a broader pattern or topic that emerges by grouping multiple related codes together; it captures a meaningful, recurring idea relevant to your research question.

For example, in interviews about leadership style with secretaries at ABC University's Faculty of Engineering, a code might be "consultative decision-making" or "communication delays." These codes highlight specific observations.

By grouping related codes like "consultative decision-making," "encouraging opinions," and "inclusive meetings," you might form a theme called "Participative Leadership." Similarly, codes like "communication delays" and "lack of clarity in instructions" might form a theme "Challenges in Communication."

Themes help you answer your research question by organizing your rich data into clear, interpretable patterns that explain secretaries' perspectives on the Faculty Head's leadership and its effectiveness.

To link themes with your research question, you would:

1. Identify codes across all interviews related to leadership behaviors and effectiveness.

2. Group these codes into meaningful themes reflecting key leadership styles and outcomes described by participants.

3. Interpret these themes to explain how the Faculty Head's leadership style impacts perceived effectiveness according to secretaries."

A collection of blog notes on using chatgpt for research purpose.

A note on how to improve the quality of discussion in the literature review chapter of the dissertation report: for MBA students

A note on how to improve the quality of discussion in the literature review chapter of the dissertation report: for MBA students (information from perplexity.ai)

My question: "With reference to the part-time 4-month MBA dissertation project works, one frequent comment from dissertation supervisors is that the discussion in the chapter of literature review (Chapter 2) is weak in discussion quality; the discussion is not critical. Could you advise an MBA student can how to improve the discussion quality of the literature review in Chapter 2 (Literature Review) of the dissertation report?"

The reply: "To improve the discussion quality of the literature review (Chapter 2) in an MBA dissertation report, an MBA student should focus on several key strategies to make the discussion critical, analytical, and well-structured rather than just descriptive or a summary of existing literature.

Here are specific recommendations for enhancing the chapter's discussion quality:

Develop a Clear Objective and Structure

• Clearly define the purpose of the literature review in relation to the dissertation topic. It should show how the review supports the research objectives, identifies gaps, and frames the theoretical foundation.

• Use a "funnel" approach: start with broad context and general theories, then narrow down to specific studies directly relevant to the research questions.

• Organize themes logically with smooth transitions to guide readers through the arguments and build a coherent narrative.

Critical Analysis and Synthesis

• Go beyond summarizing studies; critically evaluate the methodologies, findings, and theoretical contributions of each source.

• Compare and contrast different studies showing agreements, contradictions, strengths, and limitations. Highlight methodological biases, outdated sources, or narrow scopes.

• Identify research gaps explicitly, showing how the literature falls short and justifies the new study.

• Synthesize information by grouping studies into themes or concepts rather than listing them one by one, drawing connections between studies.

Express the Student's Scholarly Voice

• Make the student's evaluative voice clear at the paragraph level, especially in topic sentences and concluding sentences of paragraphs.

• Take a position on the theories and evidence presented, explaining why some are more valid or applicable.

• Use critical questions to probe assumptions, generalizability, and alternative interpretations.

Use Theoretical Framework and Practical Relevance

• Link the literature review closely to the theoretical framework that guides the dissertation methodology.

• Discuss how the reviewed literature relates to the practical problem the dissertation addresses, reinforcing the significance.

Enhance Clarity and Impact

• Use schematic diagrams or conceptual models for complex theories or relationships to make the discussion more vivid and memorable.

• Summarize key points at the end of each section to reinforce the critical insights gained.

By incorporating these strategies, the literature review will transform from a descriptive summary into a critical, analytical, and well-argued foundation supporting the dissertation research."

A collection of blog notes on using chatgpt for research purpose.

A note on how to moderate a focus group: for Housing Studies students

A note on how to moderate a focus group: for Housing Studies students (information from perplexity.ai)

My question 1: "My interest in doing my part-time 4-month Housing Studies dissertation project is to employ the focus group (with 5 participants) to conduct 1 session; due to time constraint, I could only afford to conduct a brief focus group session. My topic area is on "what are the level of confidence of the Hong Kong Gen Z to purchase an apartment in 2025 and the main factors that affect their confidence level". Two of the participants female Gen Zs; two are male Gen Zs; the last one is a lecturer in Housing Studies. Please suggest 4 questions to discuss in the focus group session. More importantly, please offer me some advice how to moderate the focus group session, as I have no experience in doing so."

The reply: "For the focus group on "the level of confidence of the Hong Kong Gen Z to purchase an apartment in 2025 and the main factors affecting their confidence," here are four suggested questions:

1. How confident do you feel about purchasing an apartment in Hong Kong in 2025? What reasons contribute most to your confidence or hesitation?

2. What are the main factors or challenges that influence your decision or confidence when considering buying property? (e.g., price, financing, government policies, market trends)

3. How do you perceive the current housing market and government measures related to home ownership for your generation?

4. What sources of information or advice do you rely on when thinking about buying an apartment, and how do these affect your confidence?

Regarding moderation advice for a novice with a 5-person mixed group (4 Gen Zs and 1 lecturer):

• Prepare your session by clarifying objectives and developing a discussion guide with clear, open-ended questions.

• Start with brief introductions and a friendly icebreaker to create a comfortable atmosphere.

• Maintain neutrality and avoid influencing opinions; let participants express themselves freely.

• Use observational skills to notice who is engaging or silent, encouraging quieter members gently and balancing dominant voices.

• Set ground rules emphasizing respect, openness, and that there are no wrong answers.

• Keep the discussion on track by gently steering back if conversations stray.

• Engage all participants equally, asking follow-up or probing questions like "Can you tell me more about that?" to deepen insights.

• Be authentic and approachable to build trust and encourage honest sharing.

• Manage your session time carefully to cover all questions while allowing meaningful discussion.

This approach ensures effective data collection and a positive group dynamic despite your lack of prior moderation experience."

My question 2: "What if one or two of the participants are reluctant to talk? As a moderator, what are the techniques to deal with this situation in the session?"

The reply: "When one or two participants are reluctant to talk in a focus group, there are several effective moderation techniques to encourage their participation without putting pressure on them:

• Gently invite them by saying something like, "What’s your take on this?" or "I’d like to hear from those who haven’t spoken yet" to create a welcoming invitation to share.

• Use open-ended questions that encourage expression without the need for right or wrong answers, which helps quieter participants feel more comfortable.

• Create a safe and respectful environment by setting ground rules at the start, encouraging all voices to be heard, and reminding talkative participants to share airtime.

• Use smaller group discussions or paired interactions briefly within the session if possible, as smaller settings are less intimidating for quiet individuals.

• Allow strategic silences after asking a question, giving participants time to think and respond at their own pace.

• Incorporate non-verbal methods such as writing down thoughts anonymously or using visual tools, allowing contributions without speaking up immediately.

• Provide positive reinforcement by validating quieter members' contributions when they do speak, encouraging further sharing.

• Avoid forcing participation; respect if some prefer to listen rather than speak, but keep them engaged through gentle encouragement and attentive listening.

These strategies help foster balanced participation and a comfortable atmosphere for all group members, especially novices to moderation."

A collection of blog notes on using chatgpt for research purpose.