Week 10: A Wild Ride

Hi readers, welcome to the final blog!

It’s been a long ten weeks, but we’re finally here! Since the last update on robotics, we’ve won our division as first pick and made it three rounds into the Einstein playoffs of the FIRST Robotics Competition World Championships. Needless to say, I was quite busy as a core pit crew member. Hence which is why I didn’t notice that my form stopped gathering data two days in.

“Wait, what?” you might ask. Yep, I wasn’t gathering data for all four days of the competition. Despite testing my website after pushing new code, I didn’t know to distinguish between new and old instances of Chrome. Apparently, there’s a special kind of cookies that my website relied on to publish to a Google Form for data. As soon as I discovered this, I changed my App Script and code to directly write onto a Google Sheet. 

Additionally, I added a prequiz and postquiz asking participants redoing the quiz to rate their previous experience, and compare it to their experience using a new model. However, the data I lost on their accuracy would never come back. 

But while robotics is what distracted me from this project, it ironically saved me, too. Our team’s technical mentor conveniently owned a robotics design discussion server and was willing to advertise it. Thanks to our exceptional performance, I found numerous willing volunteers, giving me a whopping 57 responses to work with!

This does change my participant demographics from my previously desired 9th grade level to a relatively scattered group. Because of research ethics around minors and privacy, I couldn’t simply ask what grade they were in. However, I could largely assume them to be high schoolers unfamiliar with 4D, with some middle school and college outliers.

Now onto the data analysis! I will be concealing the final results for my symposium presentation, but I can share some thoughts on the process. Using several Google Sheets formulas, I compiled data on overall accuracy, improvement after reading, outlier removal based on abnormally short analysis or answering times, and more. The following results were quite unexpected, with individual performances ranging wildly, and averages showing surprising trends. However, I’ve gained a pretty clear picture of how I think each model and each reading supplement affected my participants.

Overall, I’m proud of how far I’ve taken this project in ten weeks, and definitely look forward to presenting my findings soon.

If you’d all like to explore what I’ve made for yourselves, or even take the quiz to try, the link is still here: https://thunderrhombus.github.io/4DVisualizerQuiz

Otherwise, thanks for reading, and see you at the symposium!