Below is an outline of a plan for the analysis of our WiiCane data. Our data collection instruments are: a pre-questionnaire asking for participant characteristics (sex, age, grade level, visual impairment, prior mobility training); data collected by the WiiCane equipment on veering and coverage performance in response to feedback; and a post-questionnaire that allows participants to describe in their own words how they liked working with the device.
(1) Descriptive statistics for all of our pre-questionnaire demographic items (sex, age, grade, visual impairment, mobility training experience, etc.)
(2) Descriptive statistics for number of trials for veering and for coverage. Correlations of number of trials with subject characteristics, if they occur (e.g. do participants with prior mobility training, or longer history of visual impairment, or different age levels, do different numbers of trials in the same time period).
(3) The learning trend over successive trials will be plotted to see if it is linear, if it shows a sudden change (indicating that the participant suddenly "gets" what to do), and the rate of learning.
(4) Since number of trials is expected to vary with subjects, we will focus on the change from the first trial to the last trial for each subject as the measure of total amount of progress. For veering, we hypothesize that the average deviation from the center will be smaller in the last trial than in the first and the number of corrective feedbacks triggered will also be smaller in the last trial. For coverage, we hypothesize that the number of corrective feedbacks will be smaller in the last trial than in the first. We can also look at whether there is a bias toward too wide vs. too narrow.
If we look at these alone, essentially we have a series of paired t-tests. We can also build in one or two factors such as age, number of years of prior training, or blind vs. deaf-blind. In that case we will have an analysis of variance.
(5) Qualitative analysis of post-questionnaire comments and recommendations for improvement.
(5) Qualitative analysis of post-questionnaire comments and recommendations for improvement.
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thanks for this discussion, Annette. As you can see, we are beginning to accumulate and post videos for each test session. This is going to make for quite a lot of video by the end, so we need to put them on YouTube. We have limited the viewership only to people associated with the project. In addition to the videos, you will also be getting data log files which include information on how many times various feedbacks were issued, etc. Once we have everything collected, we will meet to discuss how it will be easiest and most efficient for you to access the data, and create some templates that let you see just what you want to look at.
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