I plan on using these two datasets from the B.C. government about tuition fees ad public post-secondary institutions.
Describe the dataset. What kind of data does it contain?
The first dataset, "Annual International Tuition Fees for Arts Program - Full-time International Students by Economic Development Region", tracks the annual tuition paid by each international student for each year from 2011 to 2018. It's sorted by these regions: Mainland/Southwest, Vancouver Island/Coast, Kootenay, Cariboo, North, and Thompson Okanagan. Kwantlen Polytechnic University is one of the Mainland/Southwest institutions, so that will be interesting to analyze. The second dataset is the "Annual Tuition Fees for Graduate Arts Program - Full-Time Domestic Students by Economic Region", which measures the same data over the same amount of time for domestic students.
Is there anything about your data that you don't understand? How will you find this out?
Kwantlen Polytechnic University is only listed in the second dataset, not the first, so I might have to find another source if I want to compare the two. Through working for The Runner, I've written and read quite a few stories about international student tuition at KPU, so I know there are statistics available about the rates online. Generally, the institutions listed in each data set are different, which seems to be the biggest inconsistency.
Kwantlen Polytechnic University is only listed in the second dataset, not the first, so I might have to find another source if I want to compare the two. Through working for The Runner, I've written and read quite a few stories about international student tuition at KPU, so I know there are statistics available about the rates online. Generally, the institutions listed in each data set are different, which seems to be the biggest inconsistency.
What are some questions you hope to answer with your data? List at least three.
The most obvious thing to take away from these datasets is that tuition is much higher for international students than it is for domestic students, so I'd like to measure that difference through a graphic that makes it easier to understand. It also seems clear that tuition is getting higher for all students with each passing year, so I'd like to determine by which percentage it is getting higher for domestic students and international students. That way, I'll be able to tell if the increase is disproportionate. I want to figure out which institutions are charging international students the most compared to what they charge their domestic students. Particularly, I want to look at where KPU stands in regards to how much its international students pay for tuition when compared to what its domestic students pay.
The most obvious thing to take away from these datasets is that tuition is much higher for international students than it is for domestic students, so I'd like to measure that difference through a graphic that makes it easier to understand. It also seems clear that tuition is getting higher for all students with each passing year, so I'd like to determine by which percentage it is getting higher for domestic students and international students. That way, I'll be able to tell if the increase is disproportionate. I want to figure out which institutions are charging international students the most compared to what they charge their domestic students. Particularly, I want to look at where KPU stands in regards to how much its international students pay for tuition when compared to what its domestic students pay.
Looking specifically at the tuition fees of international students is an interesting way to focus your study, and will likely lead to some interesting findings. I also liked that you chose two data sets to use, but the inconsistencies you mentioned could pose problems when trying to compare them. If possible, picking data sources with high amounts of overlap could help you minimize these risks, though it may also be easier to simply compare whichever data you can find that is shared between the sets you currently have. Either way, you've definitely got a unique concept, and I look forward to reading about your findings!
ReplyDeleteInteresting use of two datasets to analyze two "levels" of tuition. You've picked an interesting topic to focus on as tuition rates for both domestic and international students are always increasing. I look forward to seeing your findings on which institutions charge international students more than domestic students.
ReplyDeleteI think they are good data sets, however you shouldn't limit yourself to Kwantlen. If the data isn't there you shouldn't get stuck on finding it. Move to different universities that are there. Also include the titles of the data set in the blog post rather than just linking them in case the links break. You have good questions to answer for this data set.
ReplyDeleteComparing tuition rates for domestic and international students are a highly talked about subject throughout the school which I've experienced in many classes. I'm really interested in hearing about what you find and what you decide to focus on. Vancouver is a big hub so I think it would be interesting to see the trends of international tuition rates across the city. That being said, I agree with Tiffany that you shouldn't limit yourself to Kwantlen. It is a good place to start and link to a document supporting how much the international student community has increased. Just a technical critique: the way the two data set links were confusing for a moment; maybe formatting it a different way would help?
ReplyDeleteYour analysis is very thorough which I really appreciated. I think looking at the difference in costs for international versus domestic student is very interesting, but you should definitely look further than Kwantlen as well. Well done.
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