Not So Easy to Learn

Don Norman suggests everyday things should have sufficient affordances that they do not need printed instructions. PUSH vs PULL on doors, for example.

Gary Larson's humorous look at affordances. more

Doug Engelbart suggests that making computers easy to learn, notably the one button mouse, unfairly limits the professional user.

Mike Caulfield suggests that our new wiki, like the bicycle, is easy to use but not so easy to learn. But it may be more like the piano, difficult to use and difficult to learn.

Wiki aspires to be close to the machine in that it makes little attempt to hide how computers work in a distributed system. Many useful tasks require a sequence of operations that might leave things in an undesirable state if abandoned mid workflow.

Modern design would name each task, provide a button, and then handle each and every exceptional circumstance that might interrupt the abstracted work. We have resisted this temptation.

Carver Mead notes that semiconductor devices have rich properties that are concealed by digital logic. In his text on analog design he suggested that we study nature for hints as to how to exploit the richness of the world rather than overcoming it.

Federated wiki was founded on the notion that the quirky behavior of networked computers was not something that needed to be overcome. Instead we sought to match computer and network behavior to the equally quirky human social behavior.

We find this wiki behaves somewhat like a musical instrument. A fine instrument is preferred over a cheap one. It should feel good in everyday use. But it should also reveal new possibilities as one acquires proficiency. This has been our experience.

We are increasingly inclined to write about how we used wiki in not so obvious ways. I might conclude Project X with a page, Making of Project X. In one case I even wrote Making of the Making of Project X. There I explained how I wrote about the patterns I had discovered writing X.

We approach extensions now with an eye toward fitting into social workflow first and only then expanding the computational power of any new mechanism. To those waiting for new features this must surely dissapoint. But those who stay with us enjoy the satisfaction of their own discoveries.

What is difficult to learn, rewards students for their persistence with some of life's deepest joy. Examples I share with my kids and my students: aikido, downhill skiing, long-term relationships, dance, music, writing.