
The basic thesis:

I believe that there are a number of human activities that 
cannot be studied in the traditional ways -- in particular, 
learning, innovation, customization, coordination.  These are 
all meta-level activities that are performed to enhance the 
long-term performance of work, but not the immediate performance 
of it.  We know from experimental psychology that short-term 
rewards outlast long-term benefits.


How strong is the claim being made?

Is this environment unique?  

Learning is co-adaptive:

Users are influenced by the environment in which the learning 
is situated and they actively interact with the environment.
To learn is to be active, not passive, to interact not 
react.

Innovation is co-adaptive:

Experimental Psychologists are looking for phenomena that can be
predicted and, ideally, controlled.  They look for the items that can
be replicated under different conditions and generalized to 
new situations.

What happens when the phenomena of interest are not directly 
replicable?  What if we are looking for unusual events?  What 
if, by controlling all the variables, we look the effect?  In 
Psychology, the effect is not there.  Yet, in individual circumstances


In Psychology, the term 'anecdotal evidence' is used as a slur, to
describe sloppy, poorly thought out research.  The reasons are 
good ones:  many apparent phenomena are the result of random 
variation.  People are extremely susceptible to 

(Tukey's recent work on coincidence and large numbers -- why do people
assume that there's some psychic phenomenon at work when one person 
hits the jackpot twice in the same year.  While it is true that 
there is a less than one in a trillion chance that that particular 
person will hit the jackpot twice, the chances that someone will 
is closer to one in four.  Which suddenly isn't all that unusual.)

Because of our own biases and tendencies to look for significance
when the result is merely the effect of the random distribution, 
many branches of science have turned to statistics to determine 
whether particular phenomena are "significant" or not.  Because 
these valuations have a great deal to do with sample size and 
the power of the tests being used, many "important" findings are 
not statistically "significant".

What do we do with phenomena that are changing -- in which the act of
isolating the phenomenon from it's environment fundamentally changes
it?  What happens when "controlling the variables" means removing 
the effects we are interested in?

The study of human interaction with technology is not a study of
natural phenomena.  It is a study of people, who are changed by the
technology they use, and technology, which is changed by the people
who create and use it.  To isolate either in an attempt to understand 
the "real" phenomena is to apply the wrong scientific models.

One must ask what the value of a controlled experiment is if 
the phenomenon being studied is how the people and the technology 
change over time.  

If we study change, why use static techniques?  This is not a case
where cetis parabis applies directly..."all other things being equal"
is not useful.  

The concept of situated action is not so different from the 
concept of stimulus control, although the two are derived from 
widely divergent branches of science, with very different 
global perspectives.  The former comes from anthropology, with 
an emphasis on the "gestalt" or whole.  The latter comes 
from behavioral psychology, in which the goal is to predict 
and control specific aspects of behavior.  Both are largely 
atheoretical, driven primarily by observation, not theory.

It has been said that the natural sciences have large quantities 
of data and very few theories that can explain it, whereas 
the social sciences have many theories and very little data.

Perhaps this is not accidental.  Perhaps this is because the 
richness of social scientific research so deeply involves the 
context in which it is situated that the principles that can 
be extracted in the natural sciences do not apply. 

The assumption in social sciences is that the observer is biased and
brings a model of the world with which to view situations.  Certain
patterns may emerge that appear in other contexts -- these are
important findings.  However, they are the result of complex
combinations of factors and are not necessarily predictable 
or controllable.  The nature of understanding here is different 
from that of the natural sciences.

(By the way, the natural sciences are changing to.  Until 
Goedel's theorm and Heisenberg's Principle of Uncertainty, 
Physicists assumed that they could continue with reductionist 
approaches until they reached some form of absolute proof. 
Goedel demonstrated that the mathematics we use will necessarily 
either overdescribe or underdescribe the phenomena.  Heisenberg
....


Sidman's chapters on transition states and multiple response 
situations.




I am interested in how and under what circumstances people customize
their software and I contend that examining this as a co-adaptive
phenomenon provides important insights, both about customization
itself and about the nature of co-adaptive phenomena.

What is important here is not the speculation that people 
adjust to their environments and that they provid new environments...


Given complex software, how and under what circumstances do 
people customize?  Argue that describing the use of customizable 
software as a co-adaptive phenomenon provides important insights.

 


What's the relationship between the structurational model and 
co-adaptive phenomena?

The structurational model addresses one of the problems in studying
this kind of phenomenon -- 



Why is this interesting?

What are the implications?


Things to draw together:

co-adaptive phenomena cannot be studied in traditional ways.

Specific characteristics of the local context affect the behavior 
and ...

