Group Members
Kotomi Okawa - majors in Math Science, IMS.
Yurika Oya - majors in Network Design, IMS.
Junya Onoe - majors in Network Design, IMS.
Ryosuke Suzuki - majors in Math Science, IMS.
Why caused Education Difference?
Topic and Rationale
As a result of our discussion, our topic is determined to Education Grid Difference in Japan. We are interested in this topic, since, in Japan, many people in low income are seemed to be not able to get a high education. Today, there are social problems – income difference, home environment and friend relationship - relative to education in Japan. Thus we will try to find solutions to solve this problem.
Methodology
At first, we are going to investigate information about this topic with internet and books. Secondly, we collect statistics about income difference, and analyze this. Finally, we come to conclustions and suggest solutions.
Pros and Cons
This topic has only good aspect. There are a lot of information in web site. So we
can easily get access.
Result
We took the statistics about a correlation between the deviation value of high school and the number of the passes of the four-year university per person.
Figure 1 shows how related the deviation value of high school with the number of the passes of the four-year university. The number of the passes of the four-year university per person is the number that divided the pass results by the number of enrolled students of a high school.
Between 65 and 75 of the deviation value of high school, the number of the passes of the four-year university per person is about 2.5. In other words, the person who went to high school with deviation value between 65 and 75 has high number of the passes of the four-university, 2.5. On the other hand, the person who went to high school having low level of the score from 35 to 50, doesn’t have high number of the passes than that of high level of the score. To see this statistics, the more the deviation value of high school is, the more the number of the passes of the four-year university per person is. With
Excel’s analyze, this statistics has the positive correlation coefficient, 0.0801.
As a result of this statistics (figure 1), it was shown that there was a positive correlation between them.
Why this happens? By our conjecture, a high level person can easily get the pass of a high level high school. Then he or she can easier get the passes of the four-year university because of the high level education and consciousness of education than who do not go to a high level. Therefore, education difference between them happens.
Parent of income and academic ability of children
Statistics A
In statistic A, it was shown that the more income the parents get, the higher score the children have.
Statistics B
less than 30 minuites more than
30 minutes ~2 hours 2 hours
In statistic B, it was shown that the more income the parents get , the more time the children study.
(Reference http://nnt-sokuhou.com/archives/37274823.html)
(graph 1: Gender Equality Bureau Cabinet Office 2007)
As for the number of people to enter the high school, neither a man nor a woman makes much of a difference. (According to blue line and orange line.) But, when it comes to advance rate of university it is different. In 2007, 53.5% of men and only 40.6% of women enter the university. (According to gray line and yellow line.)
We think this result happened because the trend that the women does not need to go to the university for is left. In resent, the social advance of the woman is outstanding and the difference of the advance rate of university becomes small, but there are a few differences.
Ranking of scholarly ability in Janpan(2015) (http://gigazine.net/news/20151201-household-income-map/)
These data show that difference of scholarly ability by prefecture. Their data points out Shiga-ken and Okinawa-ken is low rank. This reason related to rate of
Rank Average
1 秋田県 82.02
2 福井県 78.23
3 石川県 73.89
中略
46 滋賀県 38.14
47 沖縄県 31.64
atypical employment.
Next data is ranking of rate of atypical employment. It shows high scholarly ability rate’s prefecture is low atypical employment rate.
Rank Rate
1 沖縄県 44.52%
18 滋賀県 38.40%
中略
38 石川県 35.55%
39 秋田県 35.34%
47 福井県 32.73% (http://todo-ran.com/t/kiji/15855)
Conclusion
As high school’s deviation value is high, the number of university’s pass record is high. As income of parents is high, children’s study time increases. Advancement rate in high schools isn’t different from gender. However male’s advancement rate in university is higher than female’s by 13%. High scholarly ability rate’s prefecture is low atypical employment rate. While low scholarly ability rate’s prefecture is high atypical employment rate. Therefore great home environment delivers prodigy.