Types of Data Collection Methods
Key Learning Objectives
Identify and describe different methods of data collection, and their strengths and weaknesses.
Explain the role of naturalistic observation, case studies and surveys in psychological research.
Types of Data Collection Methods
Primary vs. Secondary Data Collection
Primary data collection: Direct methods of data collection:
Surveys: Questionnaires, interviews, experiments.
Secondary data collection: Indirect methods:
Sources include documents, articles, etc.
Often used in meta-analysis to systematically assess previous research and derive conclusions (e.g., Clark and Stansfeld, 2007).
Research Approaches
Quantitative vs. Qualitative Methods
Quantitative methods: Use of questionnaires and tests.
Qualitative methods: Use of interviews, observations, and documents.
Table 2.3 Summary
Quantitative Methods
Standardised tests: Assess ability to solve problems and apply knowledge, commonly norm-referenced.
Questionnaires: Economical, quick methods to gather participants' feelings and beliefs. Challenges include time-consuming design and potential low motivation if lengthy.
Importance of clearly phrased questions to avoid confusion (e.g., double-barrelled and leading questions).
Qualitative Methods
Interviews: Gather profound insights into participant experiences and opinions, can be time-consuming.
Types:
Face-to-face
Telephone or online
Focus group interview
Observations: Study behavior in natural or lab settings.
Types: Naturalistic vs. laboratory observation.
Documents: Various types including personal, public, and archival documents providing rich data sources.
Quantitative Data Collection Methods
Standardised Tests
Measure problem-solving ability and knowledge application, often compared to age norms.
Offer insights into personality traits but can be costly and time-consuming.
Questionnaires
Economical, simultaneous administration, but risk low returns if perceived as lengthy.
Importance of clear wording, avoiding double-barrelled and leading questions to maintain data integrity.
Qualitative Data Collection Methods
Interviews
Provide in-depth experiences. Categories:
Face-to-face: More personal but resource-intensive.
Telephone/Online: Cost-effective, can reach diverse samples but risk participant hesitation.
Focus group: Provides diversity and interaction but challenges include moderator effectiveness and data analysis difficulties.
Structured vs. Unstructured Interviews
Structured: Pre-determined questions, same order for all participants (e.g., 'Who supported you at university?').
Unstructured: Conversational, exploratory (e.g., 'Tell me about your experience as a student president.').
Semi-Structured: Predetermined and follow-up questions (e.g., career challenges).
Naturalistic and Laboratory Observations
Naturalistic Observation
Observing behavior in natural settings without interference (e.g., observing cell phone use among students).
Advantages: Greater ecological validity, can reveal phenomena that can’t be replicated in lab.
Disadvantages: Difficult to generalize and replicate, behavior might alter due to observer presence.
Example study: Koen and Durrheim (2010) on segregation in lecture halls.
Laboratory Observation
Conducted in controlled settings, more control over variables increasing internal validity.
Concerns about real-world applicability despite ease of replication (e.g., Milgram experiment).
Documents in Research
Types of Documents
Include personal documents (diaries), public documents (university records), archival records (service records).
Challenges: Difficulty in making generalizations from document analysis.
Conclusion
Concept Check Questions
People's attitudes about social issues? (Method: survey)
Experiences of anxiety disorder sufferers? (Method: case study)
Territoriality in animal behavior? (Method: naturalistic observation)
Influence of food-related cues? (Method: experiment)