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Chapter 10: Non-Experimental Design II: Observational and Archival Methods
Chapter Objectives
Distinguish between naturalistic and participant observation methods.
Articulate the problems that can occur in observational research and how researchers address those problems.
Explain how thematic analysis can be a tool for evaluating qualitative data.
Define archival research and explain why it is non-experimental.
Observational Research
Key Concepts
Naturalistic Observation: Involves observing behaviors in natural settings with minimal intrusion on the environment.
Participant Observation: The researcher becomes part of the group being observed, impacting the data collection process.
Problems with Observational Research
Lack of control over variables can lead to challenges in drawing conclusions.
Observer bias can occur, necessitating tools like behavior checklists and techniques for interobserver reliability.
Reactivity from participants can affect behavior, suggesting the need for unobtrusive methods.
Ethical considerations include consent and privacy.
Thematic Analysis
A qualitative analysis method for identifying patterns within data.
Steps in thematic analysis:
Familiarize with Data: Understand the dataset thoroughly.
Code Data: Mark key segments of data.
Search for Themes: Identify broader themes within the codes.
Review Themes: Refine themes based on relevance and prominence.
Define and Name Themes: Summarize the essence of each theme captured.
Write Report: Compile findings into a coherent narrative.
Archival Research
Characteristics
Involves using data that was previously collected for other purposes.
Content Analysis: Often utilized to analyze archival data, allowing researchers to derive insights from existing datasets without reactivity.
Challenges include missing data and biases inherent to the original data collection methods.
Advantages and Limitations
Advantages: Enables researchers to study phenomena with existing data, thus saving time and resources.
Limitations: Potential biases and lack of control over how data was originally collected; data may not fit research needs directly.
Analyzing Observational and Archival Data
Data Analysis Techniques
Factor Analysis: Helps identify clusters within datasets to form factors.
Meta-Analysis: Evaluates effect sizes across studies addressing similar hypotheses, assessing the consistency and size of effects.
Examples of Methods
Naturalistic Observation Example
Study in a science museum where parental engagement was observed. Findings indicated a gender difference in parental interaction, with parents explaining science concepts more to sons than daughters.
Participant Observation Example
A volunteer at a homeless shelter observed and recorded identity maintenance strategies of homeless individuals, exploring the impact of time spent homeless on self-perception and social interactions.
Summary
Observational research is a valuable method for examining psychological phenomena in natural or controlled settings.
Thematic analysis aids in understanding qualitative responses.
Archival research facilitates analysis of pre-existing data sets for empirical inquiries.
Factor analysis and meta-analysis serve as important tools in analyzing data from archival sources.