Research Methods Review Flashcards

Chapter 7: Experimental Design

• Requirements of a True Experimental Design:
  • True experimental designs aim to establish causality through controlled manipulation and observation.
• Criteria for Establishing Causality in True Experiments:
  • Covariation: There must be a correlation between the independent and dependent variables.
  • Temporal Order: The independent variable must precede the dependent variable.
  • Non-spuriousness: Alternative explanations for the relationship must be eliminated.
• Quasi-Experimental Designs:
  • These designs resemble experimental designs but lack random assignment.
  • Major types include:
    • Nonequivalent control group designs
    • Before-and-after designs
    • Time series designs
• Statistical Controls in Quasi-Experimental Designs:
  • Used to account for pre-existing differences between groups when random assignment is not possible.
  • Techniques may include analysis of covariance (ANCOVA) or propensity score matching.
• Sources of Causal (Internal) Validity:
  • History: Events occurring during the study that could affect the dependent variable.
  • Maturation: Natural changes over time in participants.
  • Testing: The effect of taking a test on subsequent administrations of the same test.
  • Instrumentation: Changes in the measurement instrument.
  • Regression to the mean: The tendency for extreme scores to move closer to the average upon retesting.
  • Selection: Differences between groups due to non-random assignment.
  • Attrition: Loss of participants during the study.

Chapter 8: Survey Research

• Definition of Survey Research:
  • A method of gathering information from a sample of individuals using a standardized questionnaire.
• Features Making Survey Research Popular:
  • Versatility: Can be used to study a wide range of topics.
  • Efficiency: Data can be collected from large samples at relatively low cost.
  • Generalizability: Results can be generalized to the population from which the sample was drawn.
• Rules and Pitfalls in Writing Clear and Meaningful Questions:
  • Use clear and concise language.
  • Avoid double-barreled questions (asking two things at once).
  • Avoid leading questions (that suggest a desired answer).
  • Avoid negative questions (that use double negatives).
  • Ensure questions are culturally appropriate.
• Poorly Worded Survey Questions and Measurement Validity:
  • Can lead to misunderstanding, misinterpretation, and inaccurate responses.
  • Threatens the validity of the survey results.
• Importance of Questionnaire Organization:
  • The order of questions can influence responses.
  • Start with easy, non-threatening questions.
  • Group related questions together.
  • Place sensitive questions later in the survey.
• Basic Survey Designs:
  • Cross-sectional: Data collected at one point in time.
  • Longitudinal: Data collected at multiple points in time.
  • Trend: Data collected from different samples at different times.
  • Panel: Data collected from the same sample at different times.
  • Cohort: Data collected from individuals who share a common characteristic or experience.

Chapter 9: Qualitative Research

• Origins of Qualitative Research:
  • Rooted in anthropology, sociology, and other social sciences.
  • Focuses on understanding the meaning and interpretation of social phenomena.
• Types of Ethnographic Study:
  • Realist Ethnography: Objective account of a culture or group.
  • Critical Ethnography: Examines power relations and social inequalities.
  • Autoethnography: Researcher's personal experiences are central to the analysis.
• Participation and Observation Roles in Field Research:
  • Complete Observer: Researcher does not participate in the activities of the group being studied.
  • Participant Observer: Researcher participates in the activities of the group being studied.
  • Complete Participant: Researcher fully integrates into the group and their identity as a researcher may be concealed.
• Process of Participant Observation:
  • Entering the Field: Gaining access to the research site and establishing rapport with participants.
  • Developing & Maintaining Relationships: Building trust and maintaining ethical boundaries.
  • Sampling People & Events: Selecting participants and events that are relevant to the research question.
  • Taking Notes: Recording observations, interviews, and reflections.
  • Managing Personal Dimensions: Addressing emotional and ethical challenges.
• Intensive Interviewing:
  • In-depth, open-ended interviews with a small number of participants.
  • Aims to understand participants' experiences, perspectives, and meanings.
• Focus Groups:
  • Small group discussions facilitated by a moderator.
  • Used to explore attitudes, beliefs, and experiences related to a specific topic.
  • Samples are typically purposive, aiming for representation of key subgroups.

Chapter 10: Secondary Data and Content Analysis

• Definition of Secondary Data:
  • Data that were collected by someone else for a different purpose.
  • Examples include government statistics, archival records, and survey data.
• Factors Influencing the Quality of Secondary Data Analysis:
  • Data quality: Accuracy, completeness, and reliability of the data.
  • Data relevance: Appropriateness of the data for the research question.
  • Data access: Availability and accessibility of the data.
• Ethical Issues in Secondary Data Analysis:
  • Privacy: Protecting the confidentiality of individuals.
  • Informed consent: Ensuring that participants have given consent for their data to be used.
  • Data ownership: Respecting the rights of the data owners.
• Strengths and Weaknesses of Using Secondary Data:
  • Strengths: Cost-effective, time-saving, allows for large-scale analysis.
  • Weaknesses: Data may not be relevant, data quality may be questionable, limited control over data collection.
• Benefits and Drawbacks of Using Historical Research:
  • Benefits: Provides insights into past events, trends, and patterns.
  • Drawbacks: Data may be incomplete, biased, or difficult to access.
• Types of Comparative Research:
  • Cross-national: Comparing data across different countries.
  • Cross-cultural: Comparing data across different cultures.
  • Cross-temporal: Comparing data across different time periods.
• Definition of Content Analysis:
  • A systematic method for analyzing the content of communication.
  • Typically begins with text, speech broadcasts, or visual images.
• Difficulties in Developing Reliable and Valid Coding Procedures in Content Analysis:
  • Defining coding categories: Ensuring that categories are clear, mutually exclusive, and exhaustive.
  • Training coders: Ensuring that coders understand the coding scheme and apply it consistently.
  • Assessing inter-coder reliability: Measuring the extent to which different coders agree on the coding of the same content.

Chapter 12: Evaluation Research and Policy Analysis

• Definition and Purpose of Evaluation Research:
  • The systematic assessment of the design, implementation, or outcomes of a program or policy.
  • Purpose is to provide information for decision-making and improvement.
• Inputs, Outputs, and Outcomes in Evaluation Research:
  • Inputs: Resources invested in a program (e.g., money, staff, materials).
  • Outputs: Direct products or services delivered by a program (e.g., number of clients served, number of workshops conducted).
  • Outcomes: Changes that occur as a result of the program (e.g., improved health, increased employment).
• Types of Evaluation Research:
  • Needs Assessment: Identifies the needs of a population.
  • Evaluability Assessment: Determines whether a program can be evaluated.
  • Process Evaluation: Examines how a program is being implemented.
  • Impact Evaluation: Assesses the effects of a program on outcomes.
  • Efficiency Evaluation: Compares the costs and benefits of a program.
• Importance of Design Decisions:
  • The choice of evaluation design can affect the validity and reliability of the findings.
  • Designs may include experimental, quasi-experimental, and non-experimental approaches.
• Goal of Policy Research:
  • To provide evidence-based information to inform policy decisions.
• "Evidence-Based" Policies:
  • Policies that are based on the best available research evidence.
• Challenges of Implementing True Experimental Designs in Evaluation Research:
  • Lack of randomization: It may be difficult to randomly assign individuals or groups to treatment and control conditions.