Date: Sat, 22 Aug 1998 08:19:26 -0400 (EDT)
From: Francois Lachance <lachance@chass.utoronto.ca>
Subject: time enough for training and learning
Willard,
This may be of interest to those engaged in stratetizing
the future situation and situating of humanities
computing within and beyond the general academic
landscape.
Brad Fortner, Operations Manager, Rogers Communication Centre,
Ryerson Polytechnical University, in "Industry Leaders Review
Government's Role in New Media", an article appearing in
<title>new media.pro</title> July 1998 quotes William Buxton
While we live in a world that talks of interactive
media, be very clear that 99% of the students
graduating from computer science programs have
never produced a program to be used by other human
beings, and are not evaluated on their ability
to do so. As long as that is the way it is, and
the people who are creating this technology
have no background in sociology, anthropology or
anything that's relevant, we have a problem.
(p. 24)
Buxton is a researcher specializing in human-computer
interaction and technology-mediated collaborative
work. He has edited collections and may be well-known
to Humanist readers for <title>Readings in human-computer interaction:
a multidisciplinary approach</title> which he wrote and edited with
Ronald M. Baecker (1987).
I'm intrigued by the underlying metaphor of ownership ("we have a
problem") and its rhetorical suitability since it always
leaves the listener/reader an out: what do you mean "we"?. Sometimes
I wonder if a more impersonal formulation such as "the skill mix
in the labour pool is proving inadequate" or such as "poor design
practices are replicated by accounting practices that fail to capitalize
development costs over a sufficiently extended period of time".
Of course, it then becomes less easy to fall for scenarios that pit
the disciplines one against the other. It becomes easier to admit
to one's imaginative ken working organizations based on team models
with a place for the "translators" to go between the technically
specialized and the technically bewildered; it becomes easier to factor
long life (sic) learning and make Buxton's one percent grow.
Long life learning as opposed to life long learning is learning
that is willing to interrogate quality of life issues. Too often "life
long learning" in the literature poses as a synonym for training and
is rarely parsed as "long life = learning".
Francois
wonders how machines make promises
in scifi --
<http://www.chass.utoronto.ca/~lachance/sd/sd0003.htm>
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