User:Alexander L. Davis/Notebook/In the Problem Pit/2013/03/14
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* It is going to be important to draw the citizen science sample from the same population as those who are offered the program. If people use self-projection, then those projections will be most valid from the actual sample, rather than MTurk masters participants who may be idiosyncratic. | * It is going to be important to draw the citizen science sample from the same population as those who are offered the program. If people use self-projection, then those projections will be most valid from the actual sample, rather than MTurk masters participants who may be idiosyncratic. | ||
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| + | * I feel like their ability to generate questions is not so good. They seem to pick up on the intuitive things that most people would think of: do they want the device, do they think the money is enough. What methods can we use to help them generate effective questions using their knowledge? Are we already tapping that? | ||
==Unexpected Observations== | ==Unexpected Observations== | ||
| - | * | + | * The person in the configural condition had an unexpected approach, asking progressive questions about this person's willingness to participate, as if it were a willingness to accept for the program. |
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==New Hypotheses== | ==New Hypotheses== | ||
* There seems to be a consistent self-projection element. People think other people would do or not do for the same reasons as themselves. | * There seems to be a consistent self-projection element. People think other people would do or not do for the same reasons as themselves. | ||
==Current Protocol== | ==Current Protocol== | ||
| - | * | + | * Here is the idea for the acceptance sampling method. The distribution of new ideas (new errors) can be modeled according to a failure distribution. We want to estimate that parameter. What is the sample size needed to do that? |
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==Current Materials== | ==Current Materials== | ||
* [[Media:Volunteer_prediction_1.doc | Materials]] | * [[Media:Volunteer_prediction_1.doc | Materials]] | ||
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* Believed others would not enroll for the same reasons: invasiveness, too little compensation, and that it "might be difficult to remember what to do and when." | * Believed others would not enroll for the same reasons: invasiveness, too little compensation, and that it "might be difficult to remember what to do and when." | ||
* Others would enroll if they didn't care about the invasiveness. | * Others would enroll if they didn't care about the invasiveness. | ||
| + | * The most important thing that needs to be explained is how the frame will track usage (this needs to be corrected; the smart-meter tracks the usage, so they need to know it's already being tracked, they are just now able to see it). | ||
| + | * Make the expectations of them clear (what is expected of me?). | ||
| + | * Have an image of the frame rather than a link. | ||
| + | * Explain why we want this info, how will it be used. | ||
| + | * People throw the mail away without reading it. | ||
| + | * Might use a telephone interview. | ||
==Faults== | ==Faults== | ||
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* Broke the questionnaire up into multiple pages, with a random subset of two questions on each page. | * Broke the questionnaire up into multiple pages, with a random subset of two questions on each page. | ||
* Cut the length by having participants do two-thirds (55) of the predictions. | * Cut the length by having participants do two-thirds (55) of the predictions. | ||
| + | * Need to explain how the frame works. | ||
<!-- ##### DO NOT edit below this line unless you know what you are doing. ##### --> | <!-- ##### DO NOT edit below this line unless you know what you are doing. ##### --> | ||
Current revision
Main project pageNext entry
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Entry titleFirst Pass CommentsThese are the first two pretests. I have a vague concern about the research, not knowing exactly what the focus or story is. I am considering xx. Created a qualification in MTurk for one participant to allow him to be in future problem pit studies. I need to create an acceptance sampling method to keep the number of pre-test participants bounded.
Unexpected Observations
New Hypotheses
Current Protocol
Current MaterialsNew Data
Participant 1
Participant 2
Faults
Corrections
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