Week 10: Playtesting (Part 2)
May 7, 2024
Hello and welcome back to my blog! I can’t believe I have finally finished both the coding and data collection parts of my project, and now all that’s left is data analysis—besides slide-making, of course.
Recruiting Playtesters: The Struggle Continues
If I’d thought finding enough people to play my game was difficult enough last week, it only became more of a challenge this week. One of my main goals was to somewhat expand the age range of my sample pool, having mainly recruited fellow high school students the week before. However, this was not easy. I unexpectedly managed to recruit quite a few teachers and administrators, through a combination of emails, in-person visits, and help from Ms. Silva, but I didn’t want to stop at only BISV students and teachers. Despite finals week occurring at many universities, a number of college students volunteered to help me, which I am eternally grateful for. (If you’re one of them and you’re reading this, thank you!)
Some of my friends also offered to help me recruit more playtesters, which had an additional benefit besides simply increasing the sample size. Though there may not be direct connections between every volunteer I know personally, I was hoping to include some people who I didn’t know and had no connection with in order to further diversify the sample pool.
Qualitative Analysis
One thing that I noticed while running playtests was that not everyone behaves rationally, even when instructed to in both the written directions and verbal introduction. I considered removing any data from irrational behavior, but I realized I couldn’t afford to and could instead get more interesting results if I included it.
I will elaborate more on the qualitative results during my presentation, but a few observations I made while processing the data include a higher rate of irrational (or experimenting) behavior in the baseline group, a tendency by some participants in the treatment group to avoid using the AI feature during at least one game, and certain patterns in behavior based on age group. Frankly, I didn’t expect to have so many interesting qualitative results to discuss, but the unpredictability of human participants can be quite prominent within a decently-sized sample pool.
Data Analysis
At this point, my Notes app is full of ideas for data analysis that were either brainstormed or suggested to me by my advisors, and I’m afraid I won’t get to them all on the presentation. In the meantime, though, I am working on figuring out how to draw the correct graphs on Google Sheets, which seems determined to misrepresent my data by using the wrong columns for everything.
Here’s a sample graph after I managed to get it to work:
For next week, I’ll be working on the statistics part of the data analysis and my presentation slides. Thank you for reading and see you soon!
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