Are there enough teachers to handle the students in the country? Is the class size optimal for both teaching and learning?
These are the questions to be answered by the project, which can be measured through the student to teacher ratio. By comparing this to the global averages, it determines how the Philippines will be higher (having larger class sizes) or lower (having smaller class sizes). Moreover, this study also aims to seek differences in ratios between the education levels (Primary, Lower Secondary and Upper Secondary).
Despite the student’s access to education, the quality can be heavily influenced by the ratio between students and teachers.
A teacher with too many students is unable to properly tend to all of them, which affects the teachers’ well-being and the students’ learning and performance. A study by Mingoa (2017) presents oversized classes as one of the factors affecting teachers’ stress.
Another study by Galang et al. (2021) identifies that smaller student-teacher ratios among Asian countries yield better academic results, measured by Programme for International Student Assessment (PISA) scores.
As such, this project aims to find insights on how the ratio of the Philippines compares with the rest of the world.
There are two datasets provided by DepEd which are necessary for the study: number of teachers by school year and enrollment data by school year. The amount of teachers are sub grouped by region and by the level of education they teach: Elementary, Junior High School, and Senior High School. Enrollment data on the other hand, are grouped by region, birth sex, and grade level.
Due to the scope of the study, the enrollment data only focuses on public school students, as the DepEd can only disclose the amount of public school teachers.
The UNESCO UIS Data also presents both number of teachers by year and enrollment data per year. Each data is grouped by country, and can be classified further into the continent they belong. By the definition of their data, the levels of education are classified by Primary, Lower Secondary, and Upper Secondary.
Before combining the two major datasets, it was necessary to set a definition that Primary (Elementary), Lower Secondary (Junior High School), and Upper Secondary (Senior High School) for brevity.
For the scope of the school years, the team selected 2017 to 2021. This is the latest data presented by DepEd and the earliest year where the Philippines implemented Senior High School (S.Y. 2016-2017).
To obtain the averages, most of the data were summed up by school year and divide the number of enrollees over the number of teachers. For the UNESCO UIS dataset, this was done individually for each country. However, due to the large size of this dataset some countries were removed due to inconsistency, that is when the data for the country's enrollment is present but the number of teachers is not, and vice versa.
Primary Research Question
The graph shows that the average student-teacher ratio of the Philippines is higher than the global average. This means that the Philippines holds a larger average class size for one teacher.
Secondary Research Question
This graph shows the variations of the Philippine average student-teacher ratio vs the global average across the levels of education. Despite the low global average of Upper Secondary education, the Philippine's ratio for the education level is extremely high.
To analyze the data in accordance with our hypothesis, we used an independent samples t-test comparing the data from the Philippines with the Global Averages. This test is used since the values for the global averages are not yet known and there was no formal sampling done to obtain the local data.
Education Level | PH Mean | Global Mean | T-value | P-value | Action |
---|---|---|---|---|---|
All Levels | 27.9598 | 17.5372 | 3.8522537620 | 0.0012135709 | Reject null hypothesis |
Primary | 24.8189 | 21.1054 | 0.7053675400 | 0.4808020180 | Accept null hypothesis |
Lower Secondary | 25.3394 | 15.5298 | 2.2816610469 | 0.0229238344 | Reject null hypothesis |
Upper Secondary | 33.7210 | 13.8681 | 6.7001625537 | 6.18x10-11 | Reject null hypothesis |
The following results are presented above. The tables and the Python code used to run these tests can be accessed by clicking here.
Note that all tests are conducted with a 95% confidence level.
Education Level | PH Mean | Global Mean | T-value | P-value | Action |
---|---|---|---|---|---|
All Levels | 27.9598 | 17.5372 | 3.8522537620 | 0.0012135709 | Reject null hypothesis |
Since the p-value is less than 0.05, we reject the null hypothesis, indicating a statistically significant difference between the Philippines' ratio and the global averages.
We want to find the difference between the Philippines ratios vs the Global averages among the different levels, that is, comparing the Philippines' primary level data with the global primary data, and so on. The following comparisons are presented below.
Education Level | PH Mean | Global Mean | T-value | P-value | Action |
---|---|---|---|---|---|
Primary | 24.8189 | 21.1054 | 0.7053675400 | 0.4808020180 | Accept null hypothesis |
For the primary level, we found no statistically significant difference since the p-value is greater than 0.05, meaning the null hypothesis must be accepted.
Education Level | PH Mean | Global Mean | T-value | P-value | Action |
---|---|---|---|---|---|
Lower Secondary | 25.3394 | 15.5298 | 2.2816610469 | 0.0229238344 | Reject null hypothesis |
For the lower secondary level, a statistically significant difference is indicated.
Education Level | PH Mean | Global Mean | T-value | P-value | Action |
---|---|---|---|---|---|
Upper Secondary | 33.7210 | 13.8681 | 6.7001625537 | 6.18x10-11 | Reject null hypothesis |
For the upper secondary level, a strong difference is indicated given the shockingly low p-value obtained.
With the T-test results and acceptance/rejection of the hypotheses, we obtain insight for the different research questions. For the primary research question, it can be seen that the average student-teacher ratio (of all levels) of the Philippines is significantly higher compared to the global average. In other words, classrooms in the Philippines are more likely to feature a large number of students in a single section or class.
As for the secondary research questions, we can see that the same can be said for the lower-secondary, and upper-secondary levels of education, with the upper-secondary ratio showing a more concerning difference hinted by it having the highest T-value and lowest p-value. Among the three levels of education, only the primary level bears no significant difference when compared to its global average counterpart.
With this information, we can imply that teachers in the Philippines are stretched thinly with more students to juggle which affects their ability to cater to all of their students’ individual needs and, equally important, their own needs and well-being.
Missing data – In certain “year” categories, some countries had no data/missing data. To overcome this the research instead focused on continental averages instead of averages per country.
Formatting consistency – With the mentioned missing data, in order to crunch all the numbers, new data sets were formed to handle missing values and to make the coding process easier.
Dealing with outliers – Given the nature of the research topic/question, there are little to no outliers (since this topic covers ratios and averages of large samples instead of individual samples) so “outliers”, if any, were left as is.
Teachers in the Philippines, except for primary-level teachers, handle more students than normal. This greatly adds challenge to an already difficult job as they would have to manage larger records, guide more pupils, check more tests, etc… The added workload can potentially negatively affect the teacher’s well-being, and if a teacher cannot teach properly, students cannot learn properly.
I am a 3rd year standing BS Computer Science student from UP Diliman. I am still not sure why I decided to pursue this course and have no idea when I will be able to graduate. I just thought using computers is cool and that I will learn how to hack facebook accounts.
I have many hobbies, including reading mangas, playing video games, playing instruments, and spending time with friends. However, I waste most of my time watching reels instead of doing things I should be doing. Thank you very much!
Hello, I'm John and I am currently a computer science student at the University of the Philippines Diliman. I've personally been part of 40+ student classes so I'm glad to have the opportunity to dig deeper about this topic using the math and programming skills I have honed throughout my studies.
In stark contrast to the heavy math and programming in my course, I have a deep passion for art, both digital and traditional. I also love getting into the details and analyzing all forms of art, especially movies, music, and other forms of media.
I am Cedric, a 2nd year BS Computer Science student from the University of the Philippines Diliman. As an avid C language user, taking up CS 132 has become my first and actual application of some programming languages. I have learned a lot about Python and HTML through the contributions I have made to this portfolio.
My drive for problem solving has helped me enjoy these projects, in spite of the fact that I have no programming background before starting college.