A brief teaching note on the ethnographic approach as a research methodology

A brief teaching note on the ethnographic approach as a research methodology: for MBA and Housing Studies students (information from perplexity.ai)

My question: "Briefly highlight the main ideas of the ethnographic approach as a research methodology in social science with regard to the following topics: (1) favored research philosophy, (2) favored research approach(es) (both on (i) the research methods (i.e. quantitative, qualitative mixed methods) and (ii) the reasoning approaches (i.e. inductive, deductive and abductive reasoning).) (3) favored research method design techniques, (4) favored research method design quality criteria, (5) favored data analysis techniques, and (6) favored researcher's impression management approach in conducting the ethnographic approach."

The reply: "Here is a brief summary of the main ideas of the ethnographic approach as a research methodology in social science with regard to your specified topics:

1. Favored Research Philosophy:
   Ethnography typically aligns with an interpretivist or constructivist philosophy, emphasizing understanding human behavior and cultures from the perspective of the participants within their natural settings. It values subjective meanings and social contexts.

2. Favored Research Approaches:
   (i) Research Methods: Ethnography heavily favors qualitative methods, primarily participant observation, interviews, and sometimes archival research, to gather rich, contextual data.
   (ii) Reasoning Approaches: The approach is mostly inductive, building theory and insights from detailed observations and interactions. Sometimes abductive reasoning is used to explore surprising findings and refine interpretations.

3. Favored Research Method Design Techniques:
   Ethnographic design is flexible and emergent, often involving iterative cycles of data collection and analysis. Techniques include participant observation (active or passive), in-depth interviews, field notes, document analysis, and sometimes digital ethnography.

4. Favored Research Method Design Quality Criteria:
   Emphasis on authenticity, credibility, trustworthiness, and reflexivity. Critical reflexivity by the researcher to examine their own role and biases is important. Triangulation through multiple data sources and member checking with participants to validate findings are common practices.

5. Favored Data Analysis Techniques:
   Thematic analysis and constant comparative methods prevail, involving coding data to identify patterns, themes, and constructs. The process is interpretive and holistic, often developing new theory grounded in the lived experiences observed.

6. Favored Researcher's Impression Management Approach:
   Ethnographers manage impressions by building trust and rapport with participants, establishing good relations through prolonged engagement and respectful presence. They practice ethical transparency, informed consent, and critically reflect on their interactions to minimize bias and subjectivity.

This overview reflects the core ideas around ethnography emphasizing qualitative, naturalistic, and interpretive approaches deeply embedded in participants' lived social worlds."

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

A brief teaching note on structured observation as a research methods

A brief teaching note on structured observation as a research methods: for MBA and Housing Studies students (information from perplexity.ai)

My question 1: "Briefly highlight the main ideas of 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 structured observation."

The reply: "Structured observation as a research method in social science has the following main ideas linked to the requested topics:

(1) Favored Research Philosophy:
Structured observation is typically aligned with a positivist or post-positivist philosophy, favoring objectivity, standardization, and hypothesis testing. It seeks to produce quantifiable and replicable data with minimized biases through a structured and systematic approach to observing predefined behaviors or events.

(2) Favored Research Method Design Techniques:
The method involves a predefined plan and coding system, such as checklists or coding sheets, for systematic data collection during observations. Researchers define specific behaviors or events prior to observation, focusing on measurable and clearly operationalized variables. Structured sampling and time frames are often established for consistency, allowing for controlled and focused data gathering.

(3) Favored Research Method Design Quality Criteria:
Quality criteria emphasize objectivity, reliability, and consistency. Structured observation relies on clear definitions of categories and variables to maintain standardization across different observers and settings. This reduces subjective interpretations and enhances replicability. It also aims for systematic analysis by quantifying behaviors and ensuring data validity through careful design.

(4) Favored Data Analysis Techniques:
Data generated from structured observation is generally quantitative and suitable for statistical analysis. The use of coding systems allows for counting frequencies, durations, or sequences of observed behaviors. Analysis often includes comparing data across time, groups, or conditions, identifying patterns and trends that support hypothesis testing.

(5) Favored Researcher's Impression Management Approach:
Researchers conduct structured observations with minimal subjective involvement to avoid influencing the behavior observed. While some participation or presence is inevitable, the structured format helps observers maintain professionalism and neutrality. Impression management may involve using unobtrusive observation techniques and ensuring transparency and ethical considerations to maintain trust and credibility with participants.

In summary, structured observation in social science is a systematic, objective, and replicable method rooted in positivist philosophy, employing predefined coding schemes for reliable data collection and quantitative analysis, with researchers managing their presence carefully to minimize bias and maintain ethical integrity."

My question 2: "Clarify your information for this discussion 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: "To clarify the information on structured observation related to the two research projects in Hong Kong:

1. For the MBA topic "assessing the shopping atmosphere of malls in Sheung Shui during public holidays 2025":

   • Structured observation here would involve systematically observing shopper behaviors, interactions, movement patterns, and visual/spatial factors contributing to the shopping atmosphere. Using predefined behavior categories (e.g., social interactions, time spent, expressions of enjoyment or stress), observers would record data during public holidays.

   • The research philosophy would lean positivist focusing on objective, quantifiable aspects of shopper experience. Designing a detailed coding scheme and using time sampling techniques would ensure reliability. Data analysis might include frequency counts and pattern detection of shopper behaviors to infer atmosphere quality.

   • Impression management would require observers to be unobtrusive to avoid altering shopper behavior. Observer training and clear category definitions would ensure consistency.

   • In the context of shopping malls, visual network analysis and spatial layout are important as they affect shopper movement and atmosphere, informing structured observation variables (e.g., visibility, clustering of shops).

2. For the housing study topic "assessing atmosphere in the public space of Tsuen Wan public housing estate 2025":

   • Structured observation would focus on behaviors in public spaces such as social interactions, use of space, duration and types of activities, and environmental cues contributing to neighborhood atmosphere.

   • The positivist research approach ensures objective observation of defined behavioral indicators. Coding sheets with specific behaviors such as group size, activity type, and social interactions would facilitate systematic recording.

   • Ensuring high inter-observer reliability would be critical due to subjective nature of atmosphere. Using multiple observers and standardized training would strengthen design quality.

   • Data analysis would involve quantifying behaviors and examining patterns to assess social and spatial dynamics in the public space.

   • Observer presence is to be minimized and ethical considerations upheld given the public housing context.

These clarifications illustrate how structured observation applies practically to assess atmosphere in both shopping malls and neighborhood public spaces by focusing on observable, quantifiable behaviors and environmental factors in a systematic, structured manner within a positivist framework. Observers' impression management is key to maintaining natural behaviors and valid data collection in both contexts.For the MBA project on assessing the shopping atmosphere in Sheung Shui malls during public holidays 2025, structured observation would systematically record shopper behaviors, social interactions, and spatial usage based on predefined categories, reflecting a positivist philosophy aiming for objectivity and replicability. The design would include coding schemes and time sampling focusing on quantifiable, observable indicators like visitor flow, engagement, and visible emotional expressions. Data analysis would involve statistical counts and pattern detection, while observers remain unobtrusive to avoid influencing shopper behavior. Visual and spatial factors like shop visibility and clustering would also be relevant to understanding the atmosphere.

For the housing study on neighborhood atmosphere in Tsuen Wan public housing estate, structured observation would focus on social interactions, activities, and usage patterns of public spaces, again grounded in positivism to ensure objective, reliable measurement. The design would use detailed behavioral coding, multiple trained observers for inter-rater reliability, and minimize observer impact on natural behavior. Data analysis would quantify frequency and duration of behaviors to assess social dynamics and space use. Ethical conduct and unobtrusive observation would be critical given the residential context.

In both projects, structured observation emphasizes systematic, objective measurement of observable behavior in defined contexts, supported by rigorous design and researcher impression management to maintain data validity.For the MBA project on assessing shopping atmosphere in Sheung Shui malls during public holidays, structured observation would use a positivist approach focusing on quantifiable shopper behaviors and spatial interactions, such as foot traffic, social interactions, and engagement with stores. The design involves predefined coding of observable behaviors and time sampling to ensure systematic data collection, with data analyzed statistically to identify behavior patterns contributing to atmosphere. Researchers would remain unobtrusive to minimize influence on shoppers, considering visual factors like shop visibility impacting shopper movement and mall atmosphere.

For the housing study assessing neighborhood atmosphere in Tsuen Wan's public housing estate, the positivist philosophy underpins systematic observation of social activities and use of public spaces, with detailed behavioral coding of interactions, group size, and activity types. Multiple trained observers and standardized procedures ensure reliability and consistency. Data analysis would quantify observed behaviors to understand social dynamics shaping atmosphere. Ethical consideration and minimizing observer presence are critical due to the residential setting.

Both projects exemplify structured observation’s strength in producing objective, replicable, and quantifiable insights on atmosphere by focusing on well-defined observable behaviors, using rigorous design, and careful researcher impression management."

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

A brief teaching note on secondary research method: for MBA and Housing Studies students

A brief teaching note on secondary research method: for MBA and Housing Studies students (information from perplexity.ai)

My question 1: "Briefly highlight the main ideas of secondary 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 secondary research method."

The reply: "To address the user's query on the main ideas of the secondary research method in social science with respect to the specified topics, I found the following key insights from the gathered sources:

1. Favored Research Philosophy:

   • Secondary research in social science often aligns with positivism and pragmatism. Positivism focuses on objective knowledge and observable phenomena, often underpinning the use of existing data to test hypotheses or confirm patterns. Pragmatism is favored for its flexibility, allowing researchers to combine qualitative and quantitative insights from secondary sources based on the research problem's needs. Interpretivism is also acknowledged in contexts where the social reality is subjective and understanding context matters, though less dominant in traditional secondary research.

2. Favored Research Method Design Techniques:

   • Secondary research design techniques emphasize systematic data collection from existing sources like textbooks, journals, reports, and reliable online databases. The design typically involves defining clear research questions, identifying relevant secondary data sources, and organizing data thematically for analysis. Mixed methods design may be adopted by integrating quantitative data from secondary numerical datasets with qualitative content analysis for richer insights.

3. Favored Research Method Design Quality Criteria:

   • Key criteria include credibility, relevance, timeliness, and source reliability of the secondary data. The CRAAP test (Currency, Relevance, Authority, Accuracy, Purpose) is a common tool for evaluating data quality. Researchers must be cautious of data biases, outdated information, and methodological flaws in original studies. Transparency in documenting data provenance and any modifications applied is essential for quality assurance.

4. Favored Data Analysis Techniques:

   • Secondary research data analysis often employs qualitative thematic analysis, content analysis, and quantitative statistical re-analysis if numerical data are available. In mixed designs, triangulation combines different methods to enhance validity. Grounded theory approaches may also be used to generate new hypotheses from secondary data.

5. Favored Researcher's Impression Management Approach:

   • Researchers conducting secondary research often engage in reflexivity and transparent reporting to manage impressions, acknowledging the limitations and the context of secondary data sources. Their role includes critically assessing existing data, avoiding over-interpretation, and clearly communicating the scope and boundaries of their conclusions. A collaborative stance in narrative retelling or data synthesis may also be adopted to balance researcher influence.

These highlights capture the philosophical foundations, method design, quality standards, analysis approaches, and researcher stance typical in secondary research approaches in social science."

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

1. MBA related: "to learn more about gen z employees' preference on the leadership style of their supervisors in Hong Kong four-star hotels in 2025"

2. Housing studies related: "to learn more about the lived experience of elderly residents in public housing estate in Tsuen Wan, Hong Kong with regard to the quality of residential life in 2025"."

The reply: "To clarify the earlier information about secondary research method in social sciences with reference to your two specific research project topics, here is a more focused explanation:

1. MBA Project on Gen Z Employees' Leadership Preferences in Hong Kong Four-Star Hotels in 2025:

   • Research Philosophy: A pragmatic and partially interpretivist philosophy would be suitable, accommodating the complex, subjective preferences of Gen Z employees about leadership styles. Pragmatism allows combining qualitative insights (e.g., perceptions, attitudes) with quantitative data from secondary sources.

   • Method Design: Secondary data would involve collecting recent reports, surveys, hospitality industry analyses, and social media insights related to Gen Z workforce expectations and leadership trends in Hong Kong hotels. Mixed methods design—integrating statistics on workforce demographics and thematic content analysis of qualitative data—would be favored.

   • Quality Criteria: Emphasis should be on the currency, relevance, and reliability of secondary data, focusing on sources from 2024-2025 hospitality management and HR market research.

   • Data Analysis: Use content analysis to identify themes in Gen Z's values (e.g., flexibility, collaboration, communication style) and quantitative re-analysis of workforce trends data.

   • Researcher Impression Management: The researcher should maintain reflexivity about potential biases in secondary sources and contextualize findings within the dynamic hotel labor market post-pandemic, transparently reporting limitations.

   • Supporting points from recent studies highlight Gen Z employees prioritize flexible schedules, collaborative leadership, meaningful work, openness to social media integration, and avoidance of rigid hierarchies in hospitality settings in Hong Kong 2025.

2. Housing Studies Project on Elderly Residents' Lived Experience in Tsuen Wan Public Housing in 2025:

   • Research Philosophy: An interpretivist paradigm is most appropriate here to deeply understand the subjective, lived experiences and perceptions of elderly residents regarding quality of residential life.

   • Method Design: Secondary research would be oriented toward qualitative data sources such as government reports on public housing, social work case studies, prior ethnographic or interview-based research about elderly housing in Tsuen Wan or Hong Kong.

   • Quality Criteria: Prioritize studies with trustworthy qualitative rigor—authenticity, credibility, and transferability of lived experience accounts from the recent past (circa 2020-2025) to ensure relevance to 2025 living conditions.

   • Data Analysis: Thematic content analysis of narrative case studies or policy evaluations to extract recurrent themes about residents’ feelings of safety, social connectedness, and environmental satisfaction.

   • Researcher Impression Management: Reflexive acknowledgment of the researcher’s interpretive role and careful contextualization of data within larger social policy and demographic trends affecting elderly public housing.

   • This approach ensures a nuanced understanding of elderly residents' complex social realities and well-being indicators within the Hong Kong public housing context.

These clarifications show how secondary research's philosophy, design, quality, analysis, and researcher stance differ and adapt according to the projected topic's nature—quantitative/qualitative, young workforce versus elderly residents, hospitality industry versus housing studies. The above reflection aligns with the latest social science secondary research principles and methodologies."

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