Class 4 Reading notes-Ting

  • When to Use Which User-Experience Research Methods
    • from other articles which is more about the specificities of planning a research in action, which is more valuable for experienced users and industry veterans who may not be doing research very well, this articles feels more useful for a student to understand the entire landscape of different research tools and their best application scenarios: attitudinal vs. behavioral / qualitative vs quantitative.
    • as shown by the diagram it’s safe to say it’s recommended to use attitudinal research for more abstract, organizational, touchy-feely type of topics, and behavioral for more hands on, hard to express actions, and the qualitative/quantitative depends on whether it is easy to put it into measurable metrics.
    • then there is new matrix about context of product use, divided into natural/scripted/not using/hybrid, which makes a lot of sense for various specific need; and there is also the distinction between studies done for different phases of the product, strategize/execute/assess

  • “Tell Me What Happened” & Other Stories | Research Design Review
    • “in narrative research, the story is the data…(it’s about) what they say, how they say it, why they say it, and the context in which they say it.” since the story itself is the focus, the article emphasize the importance of a story told “by a variety of methods that serve to complete the ‘narrative environment,'” including interviews, observations, and content analyses, etc.
    • another matrix for data analysis is mentioned: thematic analysis (“what” is said), structural analysis (“how” it is said), dialogic/performance analysis (“who” it is said to, “when”, and “why”), visual analysis, etc.
    • it’s all about find context for data and put it into perspectives

  • Patterns in UX Research :: UXmatters
    • this article talks about identifying pattern in research data rather than design models. the article went into a list of “typical” pattern types, I particularly like the “interpretation” part of each pattern type in the article, trying to assign a story to each data configuration. All the types of patterns are interesting, might be more interesting if provided with concrete evidence and statistical explanations

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