When comparing the Math scores from 5 countries all culturally different, we can see a vast difference between the high and low scores regarding some of the countries. In the year 2000, the tests show that the countries of Finland, Japan, South Korea, and the province of Hong Kong all tested at significantly higher levels than the United States. However, there have been some major declines concerning the test results within the past twenty years. One of the very interesting trends we can see here are the extremely high math scores from students coming out of the Eastern countries such as Japan, South Korea, and Hong Kong. This raises a couple questions we should ask ourselves. Does scoring higher on math exams generally make individuals down the line more successful? Or is success (in this case economic and financial success) based on other aspects? We would need a more comprehensive and in-depth dive into these topics to answer those questions, however, what we can take note of is the state of businesses within these countries that have students with these high scores.
Something we see is that many students living in these countries vastly outnumber students in the west when it comes to pursuing their education in STEM degrees. For example, according to the World Economic Forum “China had 4.7 million recent STEM graduates in 2016.” (World Economic Forum) Compare this to the roughly 570, 000 students within the United States who graduate within these same degree programs that same year, and we can see where the emphasis lies within these countries. Does this mean that this will automatically contribute to a successful economy or life for that individual? No, however we could argue that the odds for financial success are greatly increased. With these numbers it is no wonder why experts say the economy of China will surpass the United States by 2025.
In regards to South Korea, if we compare it with North Korea, we can see there are no comparisons regarding the economics and success of the two. South Korea is a sprawling country with a bustling economy, it has developed its own culture regarding particular South Korean fashion, its own music “K-pop”. It is also the birth place of Samsung the largest smart phone manufacture in the world.
Japan from a business standpoint is very successful, with the design of vehicles so well that they even outpace their American competitors in sales. The phrase “Buy Japanese” has even entered into the American lexicon when it comes to buying vehicles. They are also known for their advancement in robotics and for developing one of the greatest gaming consoles ever to hit the world stage, Nintendo.
Link to animation graph below: https://www.loom.com/share/d90d394ddc0e43ce83297eeb23ff687c
#setwd("/Users/myron/Documents/R/CSV Files")
#install.packages("mapmate")
#devtools::install_github('thomasp85/gganimate')
#install.packages("colorspace")
#library(ggplot2)
#library(readr)
#library(dplyr)
#library(gganimate)
#library(viridis)
#library(colorspace)
#Data_New <- read_csv("Data_New.csv")
#View(Data_New)
#head(Data_New)
# Keep only 3 names
#Data <- Data_New %>%
#filter(Country %in% c("Japan", "South Korea", "United States", "Hong Kong", "Finland"))
#filter(sex=="F")
# Plot
#Data %>%
#ggplot(aes(x=year, y=Mathmatics, group=Country, color=Country)) +
#geom_line() +
#geom_point() +
#scale_color_viridis(discrete = TRUE) +
#ggtitle("Pisa Math scores over the past 20 years") +
#theme_ipsum() +
#ylab("Subject Scores") +
#transition_reveal(year)However, rote memorization, testing drills, and the pursuit of STEM degrees is not the only type of education that can garner high math scores. Finland has a school system that at least in the west is envied. Finland places more of an emphasis on every student having a balanced education, yet it still remains competitive with the above countries. The school system being a complete 180 degrees from the above countries looks at a more balanced education. This means less stress, more time to focus on interesting hobbies, and an overall balance to education that is outside just testing. As we can see from the bar chart the reading skills of Finland are just as high as any other country on there. Finland also places a lot of reverence on their teachers and instructors. These are the most sought after professions on Finland, so this may be one reason why education is very competitive.
The United States places last in all categories, on the lists however that does not mean we are not competitive. The United States has always been know for creativity and entrepreneurship. It has a bustling economy, many small business owners, and we apply for the most patents in the world. Although our test scores are significantly lower than these other countries we offer the intangibles not found on rigorous math, science and reading test with our innovation and ambition.
The reason for the choice of these specific charts is the detail that it tells us from the visuals. In the first graph we can see where every country is in its testing of math, science or reading at any time within the past 20 years. We can see the improvements or the declines of grades by each country, some more significant than others. For example, if we trace Finland’s timeline for mathematics, we can see it starts off very strong, however withing the past 10 years the scores drop significantly. From these visuals we can capture what might have been happening at this particular moment in time, from there we can go back and analyze the moment from where the trend starts and form a hypothesis then draw conclusions. Link to animation graph below:
https://www.loom.com/share/3f9462e134cd4c31a0dab36090f9fb22
#setwd("/Users/myron/Documents/R/CSV Files")
#install.packages("mapmate")
#devtools::install_github('thomasp85/gganimate')
#install.packages("colorspace")
#library(ggplot2)
#library(readr)
#library(dplyr)
#library(gganimate)
#library(viridis)
#library(colorspace)
#Data_New <- read_csv("Data_New.csv")
#View(Data_New)
#head(Data_New)
# Keep only 3 names
#Data <- Data_New %>%
#filter(Country %in% c("Japan", "South Korea", "United States", "Hong Kong", "Finland"))
#filter(sex=="F")
# Plot
#Data %>%
#ggplot(aes(x=year, y=Mathmatics, group=Country, color=Country)) +
#geom_line() +
#geom_point() +
#scale_color_viridis(discrete = TRUE) +
#ggtitle("Pisa Math scores over the past 20 years") +
#theme_ipsum() +
#ylab("Subject Scores") +
#transition_reveal(year)References:
Next Big future, https://www.nextbigfuture.com/2017/08/future-tech-dominance-china-outnumber-usa-stem-grads-8-to-1-and-by-2030-15-to-1.html, 4/18/2020 World Economic Forum, http://www3.weforum.org/docs/HCR2016_Main_Report.pdf, 4/18/2020