Week 6: Survey Distribution Updates & Data Analysis

Akshaya K -

Hello everyone! Welcome back to my blog. In today’s post, I am going to be discussing updates on survey distribution and data analysis.

Updates on Survey Distribution
I have not made much progress since last week, mainly because everybody — University of Kansas, BASIS Phoenix, and most of my piano teacher’s students —  is on spring break right now. However, my advisor Dr. Sawyer did tell me she can get me 30 responses from her college students next week, so I’m excited for those! My piano teacher has also been consistently asking, and I’ve gotten 4 more responses from her students. Additionally, in order to expand my sample size, I have been asking a few of my own friends who take private singing lessons.

As for the high school students, as I mentioned, I gave out around 50 consent forms, but I’ve only gotten 8 forms back, which is a bit lower than I expected. On the bright side, all 8 students who returned their forms completed my survey without issues, so at least participation was 100% once they reached that step. The lack of responses has been disappointing, but I plan to send out more reminders next week after break—hopefully, most students just forgot to get the forms signed and returned.

So far, I’ve got 27 responses (which is already a lot, I know!), but my original minimum goal was 50 and ideally, I’d love to reach 75 -100. I really do believe a large sample size is necessary for me to draw solid conclusions. With a little more time and effort, I think I can get there!

Data Analysis
Having a delay in responses means I am going to have less time to actually analyze the data. However, I’ve been researching data analysis methods ahead of time, so once I get all the data, I’ll be ready to go, and the process will be relatively smooth. As of right now, I’m planning to use correlation analysis to look for relationships between intrinsic and extrinsic motivation and performance anxiety. But as I was looking through my data, I realized that there are many other interesting patterns I could analyze. For example, I could determine which physical symptoms of anxiety are most common and whether there are differences in symptoms between high school and college students. To do this, I’ll need to spend some time organizing and separating my data, since everything is mixed together right now. However, I’m still exploring my options!

In the coming weeks, I’ll talk more about how I’m going to analyze my data and share my results. Thank you so much for reading, and stay tuned for more updates!

More Posts

Comments:

All viewpoints are welcome but profane, threatening, disrespectful, or harassing comments will not be tolerated and are subject to moderation up to, and including, full deletion.

    tanay_n
    Hey Akshaya! What specific data analysis strategies might you employ to differentiate physical symptoms of anxiety between high school and college students? I'm excited to see what the results are!
    March 23, 2025 at 11:07 am - Reply
    camille_bennett
    Hi Akshaya, thanks so much for sharing. Do you think there are any other promotional strategies for your study that could help get more participants?
    March 25, 2025 at 10:38 am - Reply
    akshaya_k
    Hi Tanay! Thank you for your comment and interest in my project! First, I would split the data between college and high school students and create a contingency table that shows how many students from each group reported each symptom. If I want to keep it simple, I could calculate the percentage of each group experiencing each symptom and compare those percentages between high school and college students. This would help identify which symptoms are most and least prominent in each group and if there are any notable differences between them. If I want to go further than that, I could perform a Chi-Square Test on the contingency table. To do that, I would have to calculate the expected values for each category using the formula: E = (Row Total × Column Total) / Grand Total. Then, I would be able to calculate the Chi-Square statistic and the p-value, which would help me determine if there is a statistically significant difference in the physical symptoms of anxiety between high school and college students.
    March 30, 2025 at 9:09 pm - Reply
    akshaya_k
    Hi Ms. Bennett! Thank you for your comment! To help me get more participants, I could reach out to more music teachers around Arizona by cold emailing them, which I am currently doing. Also, I think sending out consistent reminders through email or at meetings and classes could help boost participation because there are many people who seem interested but forget to return their consent forms. This has actually helped me increase participation in the past week! Additionally, reminding music students of the benefits of my research and how the findings could potentially benefit them might encourage more participation.
    March 30, 2025 at 9:21 pm - Reply

Leave a Reply

Your email address will not be published. Required fields are marked *