Research & Ethnography
What is unspoken
A nested classificatory hierarchy
Unfinished
Record them all
Recommendations for field notes
In Defense of Browsing
The illustrated guide to a Ph.D.
When users never use the features they asked for
An Article by Austin Z. HenleyWe deployed our tool. Almost no one used it.
The handful that did use it, used it once or twice and barely interacted with it. After a few days, zero people were using it.
Why did they tell me they wanted these features?
Why Most Published Research Findings Are False
A Research Paper by John P.A. IoannidisThere is increasing concern that most current published research findings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientific field. In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance.
How can we develop transformative tools for thought?
A Research Paper by Andy Matuschak & Michael NielsenConventional tech industry product practice will not produce deep enough subject matter insights to create transformative tools for thought.
...The aspiration is for any team serious about making transformative tools for thought. It’s to create a culture that combines the best parts of modern product practice with the best parts of the (very different) modern research culture. You need the insight-through-making loop to operate, whereby deep, original insights about the subject feed back to change and improve the system, and changes to the system result in deep, original insights about the subject.
A hypothesis is a liability
A Research Paper by Itai Yanai & Martin LercherThere is a hidden cost to having a hypothesis. It arises from the relationship between night science and day science, the two very distinct modes of activity in which scientific ideas are generated and tested, respectively [1, 2]. With a hypothesis in hand, the impressive strengths of day science are unleashed, guiding us in designing tests, estimating parameters, and throwing out the hypothesis if it fails the tests. But when we analyze the results of an experiment, our mental focus on a specific hypothesis can prevent us from exploring other aspects of the data, effectively blinding us to new ideas.
Keep digging
An Article by Ryan SingerThe hardest thing about customer interviews is knowing where to dig. An effective interview is more like a friendly interrogation. We don’t want to learn what customers think about the product, or what they like or dislike — we want to know what happened and how they chose... To get those answers we can’t just ask surface questions, we have to keep digging back behind the answers to find out what really happened.
Fast Path to a Great UX – Increased Exposure Hours
An Article by Jared SpoolAs we’ve been researching what design teams need to do to create great user experiences, we’ve stumbled across an interesting finding. It’s the closest thing we’ve found to a silver bullet when it comes to reliably improving the designs teams produce.
The solution? Exposure hours. The number of hours each team member is exposed directly to real users interacting with the team’s designs or the team’s competitor’s designs. There is a direct correlation between this exposure and the improvements we see in the designs that team produces.
Weighing up UX
An Article by Jeremy KeithMetrics come up when we’re talking about A/B testing, growth design, and all of the practices that help designers get their seat at the table (to use the well-worn cliché). But while metrics are very useful for measuring design’s benefit to the business, they’re not really cut out for measuring user experience.
Monkeys testing random designs
A Tweet by Jared SpoolA/B testing is an effective approach to use science to design and deliver deeply-frustrating user experiences.
A/B testing without upfront research is just random monkeys testing random designs to see which of those designs do “best” against random criteria.
If drug testing was actually implemented like most A/B tests, you’d give 2 drugs to 2 groups of people and pick the “winner” by whichever group had fewer deaths.
You and Your Research
A Speech by Richard HammingThis talk centered on Hamming's observations and research on the question "Why do so few scientists make significant contributions and so many are forgotten in the long run?"
What's Wrong With This Model?
What's wrong with the rational model
- We Don’t Really Know the Goal When We Start
- We Usually Don’t Know the Decision Tree – We Discover It as We Go
- The Nodes Are Really Not Design Decisions, but Tentative Complete Designs
- The Goodness Function Cannot be Evaluated Incrementally
- The Desiderata and Their Weightings Keep Changing
- The Constraints Keep Changing
Deciding what to design
We Don’t Really Know the Goal When We Start
The most serious model shortcoming is that the designer often has a vague, incompletely specified goal, or primary objective. In such cases, the hardest part of design is deciding what to design.
I came to realize that the most useful service I was performing for my client was helping him decide what he really wanted.
Today, we recognize that rapid prototyping is an essential tool for formulating precise requirements. Not only is the design process iterative; the design-goal-setting process is itself iterative. Knowing complete product requirements up front is a quite rare exception, not the norm. Therefore, goal iteration must be considered an inherent part of the design process.
Evaluating goodness
The Goodness Function Cannot be Evaluated Incrementally
The Rational Model assumes that design involves a search of the decision tree, and that at every node, one can evaluate the goodness function of several downward branches. In fact, one cannot in general do this without exploring all the downward branches to all their leaves, which is possible in principle, but leads to a combinatorial explosion of alternatives in practice.
Changing constraints
The Constraints Keep Changing
The explicit listing of known constraints in the design program helps here. The designer can periodically scan the list, asking, “Can this constraint now be removed because the world has changed? Can it be entirely circumvented by working outside the design space?”
They just don't work that way
Perhaps the most devastating critique of the Rational Model, although perhaps the hardest to prove, is that most experienced designers just don’t work that way.
“Conventional wisdom about problem-solving seems often to be contradicted by the behavior of expert designers. Empirical studies of design activity have frequently found ‘intuitive’ features of design ability to be the most effective and relevant to the intrinsic nature of design. Some aspects of design theory, however, have tried to develop counter-intuitive models and prescriptions for design behavior.” — Nigel Cross
We must outgrow it
Why all this fuss about the process model? Does the model we and others use to think about our design process really affect our designing itself? I believe it does. I believe our inadequate model and following it slavishly lead to fat, cumbersome, over-features products and also to schedule, budget, and performance disasters.
The Rational Model, in any of its forms, leads us to demand up-front statements of design requirements. It leads us to believe that such can be formulated. It leads us to make contracts with one another on the basis of enshrined ignorance. A more realistic process model would make design work more efficient, obviating many arguments with clients and much rework.
The Waterfall Model is wrong and harmful; we must outgrow it.