Survey Results (Back) <-----------------------> (Forward) Questionnaire Methods 


            The significant difference in Openness between samples was reaffirming because this is what Simo’n (1987) and Carroll and Carolin (1989) found. The Openness factor probably correlates highly with the Cattell Q1 factor (experimenting; liberal; freethinking) because some of the descriptors overlap.

The traditional problem with data as rich as the kind I got from the survey is that it is exceedingly difficult to code and analyze statistically. The advantage is that it allowed me to see the whole situation more objectively because I wasn’t forcefully pigeon-holing my respondents into multiple-choice answers. I also became aware of certain differences and factors I had not thought of before.

I did not expect to get so many replies back and as I waded through them, I realized that it would be very difficult to codify the data into numbers that were statistically measurable. I also noticed that while some replies agreed with what Mulcahy suggested, there seemed to be many deviations. I also started to notice differences related to other factors such as age and gender.

After reading all the replies, I singled out the core factors I wanted to explore and extracted statements from the replies that I thought would dichotomize gamers on those factors. I also found the Openness and Agreeableness factors to be weak in that no respondents scored below the average and most were between a 3 number range. Taking from these lessons, I wrote up a questionnaire that consisted almost completely of multiple choice questions.

I will postpone the other results I found into the results section of the questionnaire because the results are much clearer there, and it makes no sense to write out a set of weak results for this section when the latter one is available.


Survey Results (Back) <-----------------------> (Forward) Questionnaire Methods