10.06.2015 Views

Learning in Affectively Intense Virtual Environments - LITE

Learning in Affectively Intense Virtual Environments - LITE

Learning in Affectively Intense Virtual Environments - LITE

SHOW MORE
SHOW LESS

You also want an ePaper? Increase the reach of your titles

YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.

31<br />

followed the same search pattern <strong>in</strong> the Real Life “<strong>Affectively</strong> <strong>Intense</strong>” computer science<br />

build<strong>in</strong>g as they did <strong>in</strong> the virtual tra<strong>in</strong><strong>in</strong>g environment.<br />

Most participants used a systematic search pattern, fight<strong>in</strong>g fires as they<br />

searched. Most participants followed a general search pattern, go<strong>in</strong>g from floor to floor<br />

look<strong>in</strong>g for the dead and <strong>in</strong>jured, fight<strong>in</strong>g fires if necessary along the way.<br />

Alternate search pattern learned better. Participants, who performed best <strong>in</strong><br />

learn<strong>in</strong>g, used an alternative search pattern, locat<strong>in</strong>g dead and <strong>in</strong>jured first, and fight<strong>in</strong>g<br />

fires after. Two participants followed a slightly different technique, f<strong>in</strong>d the dead and<br />

<strong>in</strong>jured first and fight fires last. These two participants had the highest cumulative correct<br />

count <strong>in</strong> the “<strong>Affectively</strong> <strong>Intense</strong> Group”.<br />

Focus on the <strong>in</strong>jured personnel. There was a general trend among the participants<br />

to focus on f<strong>in</strong>d<strong>in</strong>g <strong>in</strong>jured personnel <strong>in</strong>stead of both types “dead” and “<strong>in</strong>jured”. This<br />

was particularly true for the males. One participant stated “I didn’t bother look<strong>in</strong>g for the<br />

dead”. This is augmented by the fact there were two participants who never even<br />

attempted to look for the dead. They made a 0 score for Dead Correct Count <strong>in</strong> the real<br />

computer science build<strong>in</strong>g test<strong>in</strong>g.<br />

Many participants noted the environment’s realism. Many participants<br />

commented on the realism of the computer science build<strong>in</strong>g <strong>in</strong> the experiment.<br />

Participants noted realism would be enhanced with more objects. Participants<br />

also stated that it could be better if all rooms and offices conta<strong>in</strong>ed more objects, or as<br />

one participant stated “the rooms could use a little more attitude”.<br />

Participants had difficulty differentiat<strong>in</strong>g between dead and <strong>in</strong>jured personnel.<br />

The participants tended to get the room numbers of the dead and <strong>in</strong>jured personnel <strong>in</strong> the<br />

build<strong>in</strong>g <strong>in</strong>correct at times because they did not correctly identify which were dead and<br />

which were <strong>in</strong>jured. This could be due to the similarity <strong>in</strong> the model used to denote<br />

“dead” and “<strong>in</strong>jured”. Both were represented by a model of a person <strong>in</strong> a white lab coat,<br />

ly<strong>in</strong>g down to signify “dead” and sitt<strong>in</strong>g on the ground to signify “<strong>in</strong>jured”.<br />

3.2.2. Measurement Tools. This section deals with the measurement tools<br />

employed <strong>in</strong> the experimental setup.

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!