Content Analysis Content analysis is a systematic, objective, and quantitative method for analyzing written, spoken, or visual communication. It involves coding textual or visual data into categories to identify patterns, themes, or trends. It is widely used in media studies, psychology, and communication research.
Memory Effect Memory effect refers to the influence of prior exposure on a participant’s responses in a study. In repeated measures or longitudinal designs, participants may remember previous questions or answers, which can affect the accuracy of current responses and introduce bias. It threatens internal validity.
Research Biases Research biases are systematic errors that affect the validity and reliability of study results. Common types include: Selection bias: Unequal group characteristics Confirmation bias: Researcher favors data supporting their hypothesis Measurement bias: Faulty instruments or procedures skew data Publication bias: Preference for publishing positive results over null findings
Objectivity Safeguards Objectivity safeguards are methods researchers use to minimize bias and ensure neutrality in data collection and analysis. Common safeguards include: Standardized procedures: Using the same protocols for all participants Blinding: Participants or researchers are unaware of group assignments Replication: Repeating studies to confirm findings Peer review: External evaluation of research methods and results
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Causal Comparative Research Design Causal comparative research design, also known as ex post facto design, involves comparing two or more groups based on a pre-existing condition or characteristic to determine cause-effect relationships. The independent variable is not manipulated but observed as it naturally exists. Example: Comparing academic performance of students from rural and urban schools
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Types of Constructs Constructs are abstract concepts used in research to explain behavior or phenomena. They are measured indirectly through indicators. Types of constructs include: Unidimensional: Represent a single trait (e.g., self-esteem) Multidimensional: Comprise multiple related components (e.g., intelligence, which includes verbal and spatial abilities) Concrete: Observable and measurable behaviors (e.g., hours studied) Abstract: Intangible
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Strengths and Weaknesses of Field Experiment Strengths: High ecological validity due to natural setting Behavior observed in real-world context Participants may be unaware, reducing demand characteristics Weaknesses: Less control over extraneous variables Ethical issues may arise (e.g., lack of informed consent) Difficult to replicate and measure precise effects
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Discourse Analysis Discourse analysis is a qualitative research method used to study language use in texts, conversations, or social interactions. It examines how language constructs meaning, power relations, identity, and social norms. Researchers analyze patterns, metaphors, structures, and context to interpret how communication shapes and reflects social reality.
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Steps of Evaluating Data in Qualitative Research Evaluating data in qualitative research involves a systematic and interpretive process. The key steps include: Data Organization: Transcribe interviews, group notes, and compile field observations. Coding: Identify key themes or patterns in the data through open, axial, or selective coding. Theme Development: Group codes into meaningful categories or
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Ex Post Facto Research Ex post facto research refers to a type of non-experimental study in which the researcher examines the effect of a naturally occurring independent variable on a dependent variable. The term means “after the fact,” as the cause has already occurred, and the researcher analyzes data retrospectively without manipulation or random assignment.
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