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Avdi: This is The Cache Flush,
a programmer's audio scrapbook.

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This is episode 10,
recorded April 26th, 2023.

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I am your host, Avdi Grimm,
and this episode represents

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a semi reboot of the podcast.

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Up till now, it's been a collection
of random musings, but I think

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I'm gonna change up the format.

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See, I have this collection of books
and papers, which fall under the loose

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categorization of software humanities.

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They're texts at the intersection
of programming and ethics and

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psychology and politics and systems
thinking, and just all the wider

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systems that software is part of.

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And since I haven't really been able
to stick to the previous format of

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random musings and commentary, I
thought that instead I would use

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this podcast to present selections
from these texts without commentary.

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Because a lot of these books,
I think they're important.

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They deserve wider recognition
and also, I need an excuse and

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a nudge to keep reading them.

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So without further ado,
today's selection is by John M.

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Carroll.

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It's from a paper called
Making Errors, making Sense.

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Making Use.

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This paper is one of many collected
in the book software Development and

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reality construction, which itself
is the proceedings of a conference

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by the same name from back in 1988.

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We find that users are always
fundamentally motivated

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to get something done.

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Both the organizational context for
learning new software and the internalized

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standards that adult learners have
for determining what is worth spending

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time on bias users against a learning
for the sake of learning attitude.

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New users want to get started fast.

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They like to jump the gun
executing a procedure when it is

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merely mentioned in an overview.

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They like to skip around on their own
in a training sequence, people want

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to learn by doing to reason things
out instead of merely reading about

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them, they resent rigidly structured
exercises that often compel them to

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copy text character for character, and
then subject them to insincere praise

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for these forced accomplishments.

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They like to test hypotheses
that they generate on the fly

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and to make use of their prior
knowledge and reason by analogy.

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This active orientation to learning
often badly misfits training designs,

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which are predicated on instructional
models that begin with a logical analysis

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of what needs to be learned, and then
successively decompose each learning

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objective into a step-by-step sequence
of preview, practice, test, and review.

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We have considered five characteristic
user errors, but we can turn the

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tables a bit on these five and see them
also as indicators of specific human

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propensities in learning and reasoning.

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Viewed in this way, the characteristic
problems become evidence of

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a powerful learning strategy.

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Instead of merely seeing these problems
as reflecting deficiencies in systematic

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instruction, we can ask what they can
tell us about human learners that we

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might use to develop more effective
approaches to the design of instruction.

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The five characteristic problems
correspond to five components

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of a powerful learning strategy,
one that covers most cases

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of human learning quite well.

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One.

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People learn by doing.

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They try to act in order to learn.

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Two people learn by
thinking and reasoning.

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They generate and test
hypotheses in order to learn.

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Three, people seek to work in a meaningful
context and toward meaningful goals.

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Four, people rely on their prior
knowledge when they try to manage

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and assimilate new experience.

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And five people use error diagnosis and
recovery episodes as a means of exploring

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the boundaries of what they know.

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There is a simple, albeit paradoxical
way to summarize these points.

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Just the things that make people good
learners, for example, a desire to

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make sense and to accomplish meaningful
work also create the learning problems

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that ruin systematic instruction.

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People need to make sense in
order to learn, but they need

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to learn in order to make sense.

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The challenge of designing usable
instructional systems is to allow

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people to make sense of their
own learning activity and thereby

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to refine what they already know
and discover new things as well.

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These findings called for a new approach
to online training, one that seeks

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to provide an exploratory environment
for the new user, an environment that

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affords active involvement in the
learning process, one that encourages

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initiative and hypothesis testing.

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A major consideration  in
this approach is user error.

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Error is a major consideration for any
training model, but the standard rote

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practice model typically just ignores
the problem printing steps in bold face

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and imploring learners to be careful.

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From an active learning perspective,
the problem is completely different.

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Errors are expected.

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They are unavoidable.

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They are opportunities to learn.

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If learners are going to take initiative
in directing their own learning,

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they are going to make errors.

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The problem for designers of training
is to manage the consequences

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of errors so that the greatest
possible learning benefit obtains

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so again, that was John M.

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Carroll with the essay, making
Errors, making Sense, making use

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from the book, software Development
and Reality Construction.

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And this has been the
cash flush for today.

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If you enjoy this show, you can support it
by getting a membership at graceful.dev.

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Where you can get two weeks free trial
by using the coupon code, CACHEFLUSH,

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all caps, all one word, or by pitching
in to my Patreon patreon.com/ofd Grimm.

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Thanks for listening.

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Have a great day.

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And don't forget to flush.

