Chapter 6

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Observational Methods

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12 Terms

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Observational research

  • Naturalistic observation (field observation)

  • Systematic observation

  • Contrived (set-up) observation

  • Participant observation

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Naturalistic observation

Observing behaviors as they naturally occur, often over extended periods

  • Provides rich, qualitative data and excellent ecological validity—but typically challenging to quantify

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Systematic observation

Focuses on specific, pre-defined behaviors using structured coding systems

  • Makes data quantifiable and hypothesis-driven, but may miss unexpected behaviors

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Contrived observation

Behavior is observed in controlled settings—either in a lab or orchestrated field context

  • Offers control and repeatability but may reduce naturalness

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Participant observation

The researcher becomes part of the group being studied—offering insider insight, but introducing the risk of losing objectivity and ethical complexities

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Quantitative

Emphasizes counting clearly defined behaviors across potentially large samples, enabling statistical analysis

  • example: recording frequency of sharing among preschoolers

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Qualitative

Focuses on rich, descriptive accounts of behaviors in context—like detailed field notes or narrative summaries—often from small samples

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Coding systems

Essential for systematic observation—researchers define and operationalize behaviors into specific categories and recording procedures

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Reactivity

When individuals alter behavior because they’re being observed

  • Mitigated through unobtrusive or disguised observation techniques

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Observer bias

  • Subjective expectations may skew what the observer notices or records

  • Use “blind” observers and inter-rater reliability checks to reduce bias

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Reliability

Consistency among observers (inter-rater reliability) or consistency in the same observer (intra-rater reliability) ensure measurement stability

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Ecological validity

Naturalistic observation excels here as behaviors are observed in real-life settings, increasing the generalizability to real-world contexts