Activity
An Audiogame Adventure
A student who is blind's science project to see if people with functional vision can be out ranked by those with none when playing audiogames.
This science project was done by Don, who is a student at Texas School for the Blind and Visually Impaired (TSBVI).
Question:
Can, or will, those with functional vision be outranked by those with none when playing audiogames? Or will players who are totally blind outrank those with functional vision?
Materials
- Audio game – SuperLiam
- 2 pairs of headphones
- A headphone splitter that is stereo
Preparation
Prior to trials
- Obtain permission to install game software on a computer.
- Obtain 2 pairs of headphones, and a splitter.
Group selection will be random from a list of volunteers; there will be no bias against those with vision. That is not the meaning of this experiment
Procedure
- Each volunteer will simply be given instructions in a readme file, no personal instructions.
- Say, “You have 15 minutes to get info from the readme.” Set timer for 15 minutes. Say, “Begin!”
- After 15 minutes have elapsed, say, “Time is up. Close the readme instructions file by holding down the alt plus f 4. I will help you navigate to the game.”
- You have until the end of the period to rack up as many points as possible! Plug in headphones, hand volunteer a pair.
- Process volunteers individually.
- Record points earned by each volunteer.
- Analyze data.
Data:
Averages
- No functional vision: 5,065 points
- With Functional Vision: 2,462 points
Conclusion
The evidence that I gathered did indeed support my hypothesis.
Variations
Testing whether students who are given personal instruction vs. instructions from a document will perform better was also considered. There was not time for this testing.
NGSS Standards:
- Plan and conduct an investigation individually and collaboratively to produce data to serve as the basis for evidence, and in the design: decide on types, how much, and accuracy of data needed to produce reliable measurements and consider limitations on the precision of the data (e.g., number of trials, cost, risk, time), and refine the design accordingly. (HS-ESS2-5)
By Laura Hospitál
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