Key Insights

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  Quantitative research treats context as a stable container, isolating few variables to build generalizable models.

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  Qualitative research views context as dynamic, inseparable from people and phenomena, emphasizing thick, situated understanding.

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  There is a fundamental tension between uncertainty (lack of information) and complexity (too much information) in research.

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  The Technology Acceptance Model exemplifies quantitative reductionism focusing on perceived usefulness and ease of use.

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  Qualitative methods help uncover novel, innovative user behaviors often invisible in quantitative data.

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  Scholarly pragmatism enables bridging epistemological divides by focusing on what works practically rather than foundational truths.

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  Popper's distinction between the context of discovery (qualitative) and context of justification (quantitative) supports a complementary research cycle.

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  Edge cases like digital nomads provide rich qualitative data that, when tested quantitatively, can inform understanding of broader populations.

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  Quantitative methods reduce complexity, but often at the cost of ignoring important idiosyncratic contextual factors.

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  Collaboration across qualitative and quantitative paradigms is necessary to balance depth and breadth in UX and information research.

Notable Quotes