Data Visualization Update 2

Here is the information I currently have about my data visualization on international student tuition.

An opening “lead” sentence for your final report, based on the most interesting thing you’ve found in your data so far. You can change your lead later on if you find something more interesting in your data:
I will be analyzing the disparity between tuition charged to international students and domestic students within institutions in the Lower Mainland from 2011 to 2018. So far, I have found that of the five institutions I'm analyzing, the one with the consistently largest biggest disparity (and, as such the largest total disparity from 2011 to 2018) between how much it increased tuition for international students versus domestic students during this time was easily UBC.
Over those six years, it increased its tuition for international students by $12,884 and only $538 for domestic students. This leaves the disparity between the respective increases at $12,346.
The institution with the lowest disparity, BCIT, increased its tuition for the average international student by $3,089 over the same time frame. For domestic students, the increase totalled at only $303. This leaves its disparity at $2,786.
There is a $9,560 difference between these two figures, which makes me question why UBC is charging so much more for its international student tuition than smaller colleges, which surely get less funding. Although they have less students, government funding is usually proportionate. It really shows how extreme the difference can be for international students compared to what international students are paying. Also strange is the fact that Emily Carr was the only institution to not increase its its international tuition at all for the first three years documented in this sheet. I'd like to emphasize this with my chart as well as strive to find out why.

A link to an Excel workbook containing two sheets: The first with your raw data, just as you downloaded it from the Internet. The second showing a small slice of your data that backs up the conclusions of your lead sentence and could be used as the basis for a Datawrapper chart (more details below). Briefly explain what your spreadsheet contains so it’s clear what you’re trying to show with your data:
I decided to trim both datasets to only include institutions in the Mainland/Southwest economic development region because it's more relevant information to me as a citizen of Metro Vancouver. My workbook has four tabs because I chose two sets, with one for the international and domestic tuition I've selected combined into one sheet and "Disparity" being the slice I intend to use. I also decided to only use institutions that are listed in both datasets, so I can reasonably compare all of them. I'm considering making a bar graph to compare the average increase in domestic and international tuition for each institution in the mainland from 2011/2018, so I'd need to compare each institution's domestic increase amount and international increase amount for it to be effective. A line chart could also work!

A link to the original dataset (the same one as in Update 1, unless you’ve changed your dataset since then):
I used these two datasets: "Annual International Tuition Fees for Arts Program - Full-time International Students by Economic Development Region" and "Annual Tuition Fees for Graduate Arts Program - Full-Time Domestic Students by Economic Region". 

A link to one news story, study or written report related to your data that you could refer to in your final report to provide additional context. Provide a brief summary of it and why you think it’s relevant to your data:
This article by the Globe and Mail, "B.C. universities impose steep tuition increases for foreign students", features several interviews from KPU students—which, ironically, is not included in both domestic and international amounts on these datasets—but more importantly, it effectively explains how the exponential increase to international tuition impacts the students who pay it. This is crucial context for understanding the huge increase. It also explains the perspective of university administration, which is that "international tuition rates haven’t kept up with the cost of education." I've also done some writing on this subject, so I know that government funding to universities only applies to full-time enrolled domestic students. They finance international students' services and programming out-of-pocket, so they say they need to charge more, but that doesn't make it easier on the students who are suffering to make ends meet in a new country.