Action
Specification
Forming
the goal
Input
Devices
Intentions
Forming
the intention
Evaluating
the outcome
Gulf of Execution
Specifying
the action
Interpreting the
state of the world
The Observer
Physical
System
User
Executing
the action
Perceiving the
state of the world
Gulf of Evaluation
Interface
Display
Evaluation
Interpretation
• Don Norman’s gulf of execution and evaluation
The World
• Don Norman’s seven stages of action
[ 4] Norman, D. A. The
Design of Everyday
Things. New York: Basic
Books, 2002.
[ 5] Norman, D. A.
Personal correspondence, 31 October
2008.
In the feedback-loop model of interaction, a person is closely coupled with a dynamic system. The
nature of the system is unspecified. (The nature of
the human is unspecified, too!) The feedback-loop
model of interaction raises three questions: What
is the nature of the dynamic system? What is the
nature of the human? Do different types of dynamic
systems enable different types of interaction?
[ 6] Verplank, B.
Interaction Design
Sketchbook, February
2001. (unpublished
manuscript.)
January + February 2009
[ 7] Pangaro, P. “New
Order from Old: The
Rise of Second-Order
Cybernetics and
Implications for Machine
Intelligence.” Keynote
presentation given
at the annual confer-
ence of the American
Society for Cybernetics,
Vancouver, Canada,
October 1988. <http://
pangaro.com/NOFO>
[ 8] Cooper, A. The
Inmates Are Running the
Asylum. SAMS,1999.
[ 9] Haque, U. Personal
correspondence, 25
August 2008.
In 1964 the HfG Ulm published a model of interaction depicting an information loop running from
system through human and back through the
system [ 3].
Don Norman has proposed a “gulf model” of
interaction. A “gulf of execution” and a “gulf of evaluation” separate a user and a physical system. The
user turns intention to action via an input device
connected to the physical system. The physical system presents signals, which the user interprets and
evaluates—presumably in relation to intention [ 4].
Norman has also proposed a “seven stages of
action” model, a variation and elaboration on the
gulf model [ 4]. Norman points out that “behavior
can be bottom up, in which an event in the world
triggers the cycle, or top-down, in which a thought
establishes a goal and triggers the cycle. If you
don’t say it, people tend to think all behavior starts
with a goal. It doesn’t—it can be a response to the
environment. (It is also recursive: goals and actions
trigger subgoals and sub-actions.) [ 5]”
Like Norman’s models, Bill Verplank’s wonderful
“How do you…feel-know-do?” model of interaction
is also a classic feedback loop. Feeling and doing
bridge the gap between user and system [ 6].
Representing interaction between a person and
a dynamic system as a simple feedback loop is
a good first approximation. It forefronts the role
of information looping through both person and
system [ 7]. Perhaps more important, it asks us to
consider the user’s goal, placing the goal in the
context of information theory—thus anchoring our
intuition of the value of Alan Cooper’s persona-goal-scenario design method [ 8].
A Systems-Theory View
The discussion that gave rise to this article began
when Usman Haque observed that “designers often
use the word ‘interactive’ to describe systems that
simply react to input,” for example, describing a set
of Web pages connected by hyperlinks as “
interactive multimedia.” Haque argues that the process of
clicking on a link to summon a new webpage is not
“interaction”; it is “reaction.” The client-server system behind the link reacts automatically to input,
just as a supermarket door opens automatically as
you step in front of it.
Haque argued that “in ‘reaction’ the transfer
function (which couples input to output) is fixed;
in ‘interaction’ the transfer function is dynamic,
i.e., in ‘interaction’ the precise way that ‘input
affects output’ can itself change; moreover in some
categories of ‘interaction’ that which is classed as
‘input’ or ‘output’ can also change, even for a continuous system [ 9].”
For example, James Watt’s fly-ball governor
regulates the flow of steam to a piston turning a
wheel. The wheel moves a pulley that drives the
fly-ball governor. As the wheel turns faster, the
governor uses a mechanical linkage to narrow
