Week 10: Wrapping Things Up
Hello everyone! Welcome back to my blog! This week, I’ve been wrapping up my data analysis and working on my final products.
P Values
In the past week, I calculated the p values for the correlation coefficients I talked about last week to see if they were statistically significant. I found that the only value that was statistically significant was the one between intrinsic motivation and performance anxiety in school students (r=-0.44). This means all the other correlations could have just been due to chance, so I can’t draw significant conclusions from them.
There could be a few reasons for this. First off, it might be because the sample size was too small, and the correlations were too weak. The only statistically significant correlation also happened to be my strongest correlation. The other correlations were weak or close to 0, and there were only about 35 participants per group. Generally, it’s hard to get statistically significant results with small groups unless the correlations are strong. Based on the p values, there is also a possibility that there were no clear or consistent relationships between the variables.
Limitations & What Could Have Been Done Differently
As I mentioned earlier, one limitation was the small sample size, so a larger sample size could have yielded more statistically significant results (if there was more time).
Another limitation was the survey scales. The survey used a 5-point Lichert scale for all the sections that asked participants to rate statements. However, they may not have captured the motivation and anxiety levels with accuracy. If I had used more detailed survey scales (e.g. 7-point or 10-point Lichert scales), the data may have been more accurate.
A third limitation was that the confounding variables — which could have significantly affected the results — were not controlled for. These variables include performance frequency (which I talked about last time), type of instrument, years of experience, and type of performance (group vs. solo). If there was more time, multiple regression analysis could have been used to examine how much anxiety scores are influenced by motivation types and confounding variables.
Final Products
First off, I am working on a research paper and a research poster that go more into depth into everything I’ve talked about in my blog posts and what I’ll talk about in my presentation.
Additionally, I am making a brochure about coping with performance anxiety. Since I hit the time limit for my presentation, I ended up focusing just on my correlations and wasn’t able to go into coping strategies. But throughout this project, I’ve learned a lot about coping strategies and how they work, and I even had a question on my survey that allowed me to determine which strategies were the most commonly used among participants. So, I still want to share that information with my audience because I think it could really help my fellow music students. This brochure will include the most commonly used strategies and explain how they work.
That’s all for today. Thank you so much for reading, and stay tuned for next week!
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