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AGENT led decision tree

Posted: Wed May 07, 2014 8:17 pm
by richmond62
This is just an excuse for me to dig some screen shots of my M.A. Thesis out of the vaults.

However, they should make their point.
K1.png
K2.png
K3.png

Re: AGENT led decision tree

Posted: Wed May 07, 2014 8:18 pm
by richmond62
K4.png
K5.png
K6.png

Re: AGENT led decision tree

Posted: Wed May 07, 2014 8:20 pm
by richmond62
K7.png
K8.png
K9.png
That should suffice.

Re: AGENT led decision tree

Posted: Wed May 07, 2014 8:25 pm
by Peregrine
So that's basically kind of a wizard for setting up your application?

Re: AGENT led decision tree

Posted: Wed May 07, 2014 8:31 pm
by richmond62
It's a prototype Wizard that would do everything for you.

The idea underpinning this was that learning to use a computer via a WIMP-GUI,
followed by learning a programming language should not be necessary for, for
example, a Professor of Ethno-Botany.

There are several scenarios:

1. The Prof. has to learn all that extra stuff on top of his/her speciality; taking considerable time away from research is his/her field.

2. The Prof. sits next to a computer programmer who knows nothing about Ethno-Botany; and they end up having a fight.

3. You have a Super-Wizard that allows the Prof. to get on with making his/her computer program without knowing much more than
to type in his/her language and click with a mouse.

Re: AGENT led decision tree

Posted: Wed May 07, 2014 8:43 pm
by richmond62
Those screenshots were taken just now on my Ubuntu box
opening the stack with RR/Livecode 2.2.1 with the messages turned
off, as the scripts in the stack were making my screen go black and crashing RR/LC 2.2.1.

The stack was originally made on Macintosh 10.3 with embedded Quicktime movies
[the talking head really did Talk and Move] and audio files.

It was trialled at a Primary school in Scotland on machines running Windows XP
with Quicktime installed and proved very effective.

When the teachers came into the school computer room (where they taught kids how to use
a Paint program) theyw ere moaning about losing their free time. After 15 minutes they were
excited about the idea of making small programs for content delivery and reinforcement
without any significant cognitive overhead.