A brief teaching note on the research method of semi-structured observation

A brief teaching note on the research method of semi-structured observation (information from perplexity.ai)

My question 1: "Briefly highlight the main ideas of semi-structured observation as a research method in social science with reference to the following topics: (1) favored research philosophy, (2) favored research method design techniques, (3) favored research method design quality criteria, (4) favored data analysis techniques, and (5) favored researcher's impression management approach in conducting the semi-structured observation."

The reply: "Here is a brief highlighting of the main ideas of semi-structured observation as a research method in social science with reference to the specified topics:

(1) Favored Research Philosophy:

Semi-structured observation aligns well with interpretivist and constructivist philosophies, which view reality as socially constructed and emphasize understanding participants' subjective experiences rather than assuming an objective independent reality. It is also pragmatically used across a range of paradigms depending on research goals.

(2) Favored Research Method Design Techniques:

The design of semi-structured observation involves having a flexible yet guided approach, typically with an agenda or a set of open questions/themes but allowing researchers to remain open to unexpected findings. It combines specific research questions with openness to discovery, enabling researchers to identify practical problems experienced by participants in natural settings.

(3) Favored Research Method Design Quality Criteria:

Quality in semi-structured observation studies involves transparency, rigor, and reflexivity. Researchers are expected to keep comprehensive notes, be attentive and avoid premature conclusions, document their decisions systematically, and provide enough detail for others to inspect and build upon the study. Triangulation and clear reporting of limitations are also important.

(4) Favored Data Analysis Techniques:

Data analysis frequently uses qualitative coding, thematic analysis, and sometimes content analysis. Thematic analysis is predominant, involving coding interview or observation data to identify patterns and themes that reveal deeper meanings of participants’ experiences. Data are organized into categories to facilitate comparison and interpretation.

(5) Favored Researcher's Impression Management Approach:

Researchers conducting semi-structured observation maintain roles of empathetic listener and observer, balancing openness with sensitivity. They manage impressions by demonstrating empathy, openness, and reflexivity, maintaining transparency about their role, and engaging participants respectfully to encourage genuine responses while minimizing bias.

These points provide a cohesive overview of how semi-structured observation is used in social science research from philosophical underpinnings to practical conduct and analysis."

My question 2: "Clarify your information for this discussion on semi-structured observation a bit more with reference to the following research project topics:

1. MBA related: "to assess the shopping atmosphere of the shopping malls in Sheung Shui, Hong Kong during public holidays in 2025"

2. Housing studies related: "to assess the atmosphere of neighborhood in the public space of the public housing estate in Tsuen Wan, Hong Kong in 2025"."

The reply: "Here is a more detailed clarification of semi-structured observation in relation to the two research project topics:

1. MBA Related Project: Assessing shopping atmosphere in Sheung Shui malls during 2025 public holidays

• Favored Research Philosophy: Pragmatism best fits this application, combining qualitative insights with observable behaviors and environmental factors. This allows understanding how shoppers and ambient conditions interact to shape the atmosphere.

• Favored Method Design Techniques: A semi-structured observation guide is developed, covering shopper flow patterns, crowd density, shopper interactions, ambient noise and lighting, and mall layout features. Observations focus on peak holiday periods to capture dynamic atmosphere changes.

• Favored Quality Criteria: High rigor through detailed field notes, regular cross-checking with mall management data if available, and use of multiple observation sessions for reliability. Reflexivity on the observer's influence and efforts to minimize disruption are key.

• Favored Data Analysis Techniques: Thematic analysis of observational notes to identify patterns in shopper behavior and atmosphere characteristics, supported by descriptive statistics on crowd density or dwell time if recorded.

• Favored Researcher’s Impression Management: Researcher remains unobtrusive to avoid altering shopper behavior, practicing neutrality and sensitivity to cultural and social norms of mall visitors, enabling authentic captures of atmosphere.

2. Housing Studies Project: Assessing neighborhood atmosphere in public housing estate public space, Tsuen Wan, 2025

• Favored Research Philosophy: Interpretivism/constructivism is ideal to capture residents’ lived experiences and social meanings attached to neighborhood atmosphere.

• Favored Method Design Techniques: Semi-structured observation focuses on social interactions, communal activities, use patterns of public space (e.g., seating, playgrounds), and environmental elements such as cleanliness and maintenance. Observation across various times/days collects comprehensive atmosphere data.

• Favored Quality Criteria: Credibility via thick descriptive notes, reflexive field journaling on researcher positionality and community engagement, and possible participant feedback on observations to validate interpretations.

• Favored Data Analysis Techniques: Coding and thematic analysis to extract key themes around social cohesion, place attachment, and environmental factors shaping atmosphere.

• Favored Researcher’s Impression Management: Building rapport with residents if feasible, showing empathy and cultural respect, and maintaining transparency about observational purpose to encourage natural behavior and genuine social exchanges.

In summary, semi-structured observation in shopping mall atmosphere research utilizes pragmatism with flexible but focused methods emphasizing observable interactions and environmental cues. Meanwhile, in public housing neighborhood atmosphere research, it embraces interpretivism emphasizing social meanings, resident engagement, and context-rich observations.

Each project’s design optimizes quality and rigor through tailored observation guides, iterative data analysis, and mindful researcher conduct suitable for their social settings in Sheung Shui and Tsuen Wan respectively.

This approach ensures semi-structured observation effectively captures the nuanced atmospheres relevant to MBA and housing studies inquiries in Hong Kong 2025."

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