A Comparative Study on the English Proficiency of Students from Public and Private Schools

| ABSTRACT Previous studies showed that educational context factors like schools could influence the English proficiency of students. One of the greatest predictors of proficiency among language learners is the type of school they are attending – either public or private. Empirical data also suggested that English profici ency had an impact on students’ performance in science and math courses. Hence, this study examined which type of senior high school (SHS) – public or private school – could produce more proficient students in using the English language. The data gathering process focused on SHS students from both public and private schools, who were enrolled in the academic track of Science, Technology, Engineering, and Mathematics (STEM). The study investigated their English proficiency and looked into their profile variates; the difference in their English proficiency in terms of grammar, vocabulary, and reading comprehension, which turned out to be significant whether they were in a public school or private school; the relationship between their English Proficiency and the type of school they attended which was also significant; and the relationship between their English proficiency and their academic performance in English courses which was found to have nothing to do with the former.


Introduction
The term "proficiency" has been used as a great deal in the contemporary world. It is employed to describe language learners' competency in a language, both in a foreign country and even in the classroom, as they are able to read, write, comprehend, and interpret signs in a language other than English. Proficiency is also devised for language learners to realize their own performance of language use whether they are learning and using it in a physical classroom, in a virtual classroom, through independent taskbased activities, or in a blended environment.
One study (Santana et al., 2017) found that one of the greatest predictors of proficiency among language learners is the type of school they are attending -either public or private. Thus, administrators and educators in public and private schools alike all do their best to provide the best learning climate and environment possible. Indeed, while there are excellent public schools, there are excellent private schools as well.
However, in the study by Getie (2020), it was revealed that educational context factors like schools and the English language learning scenarios (e.g., the seating arrangements, the classrooms, and other physical environments creating the learning climate) have an undesirable impact on students' attitude toward learning the English language. In Canada, schools are ranked by the Fraser Institute, which oftentimes finds favor with private schools, albeit it assigns high ranks to public schools (Our Kids, 2018). In the USA, the scenario is somewhat similar: there are good public schools, yet, several of the best schools, in an overall assessment, are funded by private sectors and individuals. On another note, as per Center on Education Policy (Jeong, 2007), it concluded that low-income students attending public schools in the urban areas could, in general, perform equally in academic aspects with that of their peers from private high schools.
In the Philippines, children are sent by their parents to private schools due to the latter's impression that students from private schools speak English well and even better than how the public school students speak the language (Cruz, 2014). However, this conception is not at all times true. In the annual elimination competitions organized by the English-Speaking Union Philippines, having students from public schools who are able to reach the final round or even become champions is not unusual and is nothing to be amazed or doubtful of. Nonetheless, among parents, there is a general observation and impression that La Salle and Ateneo students speak the English language more fluently and accurately than how students from the University of the Philippines (UP) use it. Another impression is that students in the nearest private schools communicate with one another using the English language, unlike students in the nearest public schools who allegedly and presumably communicate with one another in the vernacular or local language. (Cruz, 2014) The 2003 Program for International Student Assessment (PISA) results depicted that students enrolled in private high schools had better performance in science, reading, math, and problem-solving (OECD, 2004). As per academic records of students enrolled in high schools whose curricula generate more exposure to English, there is a significant difference in their performance in the subject areas of math, science, and language proficiency (Özbay, 2015).
Hence, in this study, the researcher determined which type of senior high school -public school or private school -in Catbalogan City, Samar, Philippines, could produce more proficient students in using the English language. Further, since Abedi (2010) espoused that English language proficiency had an impact on students' performance in reading, science, and math, the researcher in this study focused on the senior high school academic track, Science, Technology, Engineering, and Mathematics (STEM), which is a preparatory curriculum for students who want to venture in said intertwining disciplines.
In a STEM curriculum, English is the medium of instruction that is better and easier to understand by students as Math and Science have several technical terms in English. The difference between the STEM curriculum with the other academic tracks is its scope of advanced concepts and topics. Under said track, students can become an architect, a chemist, a biologist, a pilot, an astrophysicist, an engineer, a nutritionist, a nurse, a dentist, a doctor, and a lot more. As to grade level, the researcher chose Grade-12 students for the reason that, for almost six (6) years of being high school students, they are expected to have been able to adjust from their elementary days and have enough knowledge of the English language. Also, this grade level is the stage wherein they are preparing for and are presumably ready to level up as college students.
Therefore, as mentioned, this study assessed the English proficiency of the STEM students, being the respondents of this study, from public and private schools. Moreover, it investigated their profile variates; the significant difference in their English proficiency in terms of grammar, vocabulary, and reading comprehension; the significant relationship between their English proficiency (grammar, vocabulary, and reading comprehension) and the type of school they attended; and the significant relationship between their academic performance in English and their English proficiency in grammar, vocabulary, and reading comprehension.
Specifically, this study ascertained to answer the following empirical queries: 1. What is the profile of the student-respondents in terms of:

Research Design
This is a descriptive and correlational quantitative research study. This is descriptive because it looked into the profile of the student-respondents according to their age, sex, type of school attended, and academic performance in English using their general weighted average (GWA) in English subjects. It also assessed the student-respondents' English proficiency in grammar, vocabulary, and reading comprehension. On the other hand, this study employed a correlational design because it tested and ascertained the significant difference in the student-respondents' English proficiency in terms of grammar, vocabulary, and reading comprehension; the significant relationship between their English proficiency (grammar, vocabulary, and reading comprehension) and the type of school they attended; and the significant relationship between their academic performance in English and their English proficiency in grammar, vocabulary, and reading comprehension.

Instrumentation
The research instrument consisted of two (2) parts. Part I was a survey questionnaire that was used to elicit the STEM students' profiles such as age, sex, SHS enrolled in (type of school attended), and GWA in English subjects (academic performance in English). Part II was a standardized test (MBA Rendezvous, 2018) that was utilized to assess the English proficiency of STEM students in grammar, vocabulary, and reading comprehension. The English proficiency test had three (3) categories: Grammar I and II, Vocabulary, and Reading Comprehension. The questions for grammar contained 30 questions, for vocabulary -10 questions, and for reading comprehension -10 questions. The total number of questions was 50 items.

Validation of the Instrument
Although the research instrument used in this study was a combination of a profile questionnaire and a standardized English proficiency test, it still underwent a validation process. First, it was reviewed by the researcher's adviser, then by three (3) content experts. Their comments and suggestions for improvement were considered in the revision of the questionnaire.
To determine the reliability of the instrument, it was pilot-tested in one (1) senior high school in Samar, Philippines, other than the respondent schools, using STEM students as pilot respondents. The half-split reliability test method was employed wherein the number of items was divided into two (2), odd and even numbers were separated.
The results showed that the correlation between the odd and even test items were 62.4 positive correlations, and a Spearman-Brown coefficient in equal length of 76.8 percent depicted that the items were reliable. Also, Cronbach's Alpha was computed with a 76.8 percent, which implied that the research instrument was acceptable.

Sampling Procedure
The total population, both from public and private schools, was 136. There were 65 students from public schools and 71 from private schools. The researcher used Sloven's formula to get the sample size and came up with the number of 102 studentrespondents. Thus, she took 51 students from public schools and 51 students from private schools. As the researcher employed simple random sampling in identifying the specific student-respondents from each type of school, she had them write their names on a piece of paper, placed them in a bowl, and drew lots from it to determine the target student-respondents.

Data Gathering Procedure
After selecting and finalizing the tools for data gathering, the researcher made a letter for the approval of the respondent schools. The researcher personally visited the schools to ask permission for the administration of the profile questionnaire and standardized test and for the collection of the necessary data thereafter. One of these was asking for the list of Grade 12-STEM students' names.
The researcher explained the purpose of the study to the students who had been picked in the simple random sampling process. Their consent was obtained first prior to the administration of the research instrument. Also, they were explained that their responses to the study would be treated with the utmost confidentiality and that only the researcher would have access to their personal data and test results. After the student-respondents had completed the said research instrument, the same was personally retrieved by the researcher. The answers to the English proficiency test were checked, and the scores were tallied and handed to a professional statistician for data analysis.

Statistical Treatment of Data
Right after gathering the relevant information in the study, data analysis immediately followed using appropriate statistical tools for the identified research design. Said statistical tools employed are the following, namely: frequency count, percentage, mean and standard deviation, weighted mean, and Pearson's Product moment correlation coefficient. The researcher hired a professional statistician to work on the statistical treatment of the gathered data, but she was the one who analyzed and interpreted the statistical computations and results.

Results and Discussion
The data gathered from the student-respondents, the subsequent statistical treatment and analysis, and the corresponding interpretations of the findings are presented in this section. The data consist of the student-respondents' profile and their English proficiency as they attended, whether public or private school.

Profile of the Student-respondents from Public and Private Schools
This section discusses the data pertaining to the profile of the STEM students in public and private schools who were involved in this study. Their profile included their age, sex, type of school attended, and academic performance in English (GWA in English subjects). Table 1 shows the information about the age and sex of the student-respondents in public schools. The oldest student-respondent was 19 years old, while the youngest was 15 years old. Thirty-six of the student-respondents were 18 years of age, or 70.6 percent. The average age of the student-respondents posted at 17.67 years, with a standard deviation of 0.683 years. Therefore, most of the respondents were still in Adulthood. Twenty-six or 51 percent of the student-respondents were female, and the rest were male. Most of the respondents were female. Table 2 shows the information about the age and sex of the student-respondents in private schools. The oldest student-respondent was 19 years old, while the youngest was 16 years old. Twenty-five of the student-respondents were 18 years of age, or 49 percent. The average age of the student-respondents posted at 17.63 years, with a standard deviation of 0.662 years. Therefore, most of the respondents were still in Adulthood. Twenty-nine or 56.9 percent of the student-respondents were female, and the rest were male. Most of the respondents were female. Table 3 shows the student-respondents' GWA in their English subjects in public schools. Two or 3.9 percent of the studentrespondents obtained a higher grade of 96 above. Only one or 2 percent of the student-respondents obtained the lowest grade of 75-80. Twenty-six or 51 percent of the student-respondents had a grade of 86-90. The mean grade of the student-respondents was 90.06 averages with a standard deviation of 3.313 averages. Most of the respondents had higher grades in their English subjects. Table 4 shows the student-respondents' GWA in their English subjects in private schools. Two or 3.9 percent of the STEM students obtained a higher grade of 96 or above. Twelve or 23.5 percent of them obtained the lowest grade of 75-80. Sixteen or 31.4 percent of the STEM students had a grade of 86-90. The mean grade of the student-respondents was 85.29 averages with a standard deviation of 5.654 averages.

English Proficiency of the Student-respondents from Public and Private Schools
This section discusses the data pertaining to the English proficiency of the STEM students in public and private schools who were involved in this study. Their English proficiency was classified into three (3) categories, but in four (4) parts, namely: Grammar I, Grammar II; Vocabulary; and Reading Comprehension. Table 5 shows the public-school student-respondents' English proficiency in terms of Grammar I. There was 24 or 47.1 percent of the STEM students who got the score of 10 -12. Therefore, the student-respondents had high English proficiency in Grammar I. Table 6 shows the private-school student-respondents' English proficiency in terms of Grammar I. There were 36 or 70.6 percent of the STEM students who got the score of 10 -12. Therefore, the student-respondents had a very high English proficiency in Grammar I. Table 7 shows the public-school student-respondents' English proficiency in terms of Grammar II. There was 30 or 58.8 percent of the STEM students who got a score of 13 or above. Therefore, the student-respondents in public schools had a very high English proficiency in Grammar II. Table 8 shows the private-school student-respondents' English proficiency in terms of Grammar II. There was 26 or 51 percent of the STEM students who got a score of 13 or above. Therefore, the student-respondents had high English proficiency in Grammar II. Table 9 shows the public-school student-respondents' English proficiency in terms of Vocabulary. There was 24 or 47.1 percent of the STEM students who obtained a score of 9 or above. Therefore, the student-respondents in public schools had high English proficiency in Vocabulary. Table 10 shows the private-school student-respondents' English proficiency in terms of Vocabulary. There was 30 or 58.8 percent of the STEM students who obtained a score of 7-8. Therefore, the student-respondents had high English proficiency in Vocabulary. Table 11 shows the public-school student-respondents' English proficiency in terms of Reading Comprehension. There were 26 or 51 percent of the STEM students who got a score of 9 or above. Therefore, the student-respondents in public schools had a very high English proficiency in Reading Comprehension. Table 12 shows the private-school student-respondents' English proficiency in terms of Reading Comprehension. There were 21 or 41.2 percent of the student-respondents who got the score of 7-8. Therefore, the student-respondents in private schools had high English proficiency in Reading Comprehension. Table 13 reflects the difference of English proficiency between public and private schools in terms of Grammar of the studentrespondents. Since the computed p-value (Sig.2-tailed) of the English proficiency in terms of grammar was less than the 0.05 level of significance, which was 0.03, there was sufficient evidence to reject the null hypothesis.

Difference of English Proficiency between Students from Public Schools and Students from Private Schools
The same table reflects the difference in English proficiency between public and private schools in terms of the Vocabulary of the student-respondents. Since the computed p-value (Sig. 2-tailed) of the English proficiency in vocabulary was less than the 0.05 level of significance, which was 0.02, there was sufficient evidence to reject the null hypothesis.
Again, Table 13 reflects the difference in English proficiency between public and private schools in Reading Comprehension of the student-respondents. Since the computed p-value (Sig.2-tailed) of the English proficiency in reading comprehension was less than the 0.05 level of significance, which was 0.00, there was sufficient evidence to reject the null hypothesis.
As mentioned, Table 13 reflects the difference in English proficiency between public and private schools in grammar, vocabulary, and reading comprehension of the student-respondents. Since the computed p-value (Sig. 2-tailed) of the English proficiency in grammar, vocabulary and reading comprehension was less than the 0.05 level of significance, there was sufficient evidence to reject null hypotheses. Therefore, the English proficiency of the STEM students in grammar, vocabulary, and reading comprehension had a significant difference, and these differed between public and private schools. Table 14 reflects the relationship between English proficiency and the type of school attended by the student-respondents. Since the computed p-value was less than the 0.05 level of significance, there was sufficient evidence to reject the null hypothesis. Therefore, the English proficiency had a significant relationship to the type of school attended by the student-respondents. Table 15 reflects the relationship between academic performance in English and the English proficiency of STEM students in grammar, vocabulary, and reading comprehension. Since the computed p-values of grammar and vocabulary were greater than the 0.05 level of significance, there was sufficient evidence to accept the null hypothesis. Therefore, the academic performance in English of the student-respondents had no significant relationship to their English proficiency in grammar and vocabulary.

Relationship between Academic Performance in English and the English Proficiency
On the other hand, there was a significant relationship between the STEM students' academic performance in English and their English proficiency in reading comprehension.

Conclusions
The following are the conclusions made based on the findings of the study: 1. The oldest student-respondent in public schools was 19 years old, while the youngest was 15 years old, and 36 of the respondents were 18 years of age. While in private schools, the oldest student-respondent was 19 years old, while the youngest was 16 years old, and 25 of the respondents were 18 years of age. Two of the student-respondents in public schools obtained a higher grade of 96 above. Only one of the student-respondents obtained the lowest grade of 75-80, and 26 of the studentrespondents had a grade of 86-90. While in private schools, two of the student-respondents obtained a higher grade of 96 above. Twenty-six of the student-respondents in public schools were female, and the rest were male, and most of the respondents were female. While in private schools, 29 of the student-respondents were female, and the rest were male, and most of the respondents were also female.
2. Based on the study, the private schools had higher English proficiency in terms of Grammar I than the public schools. Yet, it was also shown in the study that the public schools had higher English proficiency in terms of Grammar II than the private schools. The result also suggests that the public schools had a very high English proficiency in terms of Vocabulary. Further, it was depicted that the public schools had higher English proficiency in Reading Comprehension than the private schools.
3. The English proficiency of the student-respondents in grammar, vocabulary and reading comprehension had a significant difference whether they were in public or private school.
4. The English proficiency had a significant relationship to the type of school attended by the student-respondents.
5. The academic performance in English of the student-respondents had no significant relationship to their English proficiency in grammar and vocabulary. On the other hand, there was a significant relationship between student-respondents' academic performance in English and their English proficiency in terms of reading comprehension.
The findings of this study would give insights and input to the administrators, teachers, parents, and other stakeholders on how to enhance the English proficiency of the SHS students, especially those who belong to the STEM academic track. Since it was revealed that the type of school they attended, specifically the public schools, had a significant relationship with their English proficiency, it is important that the key officials and stakeholders in public schools would develop intervention schemes and/or mechanisms to improve STEM students' English proficiency in grammar, vocabulary, and most especially, reading comprehension.
As SHS students, their reading comprehension should have been very good already and not merely satisfactory, as this is the strong foundation that would back them up in their higher education journey and even when they land a job in the future. Hence, this study would guide the government education sectors to enrich further the English proficiency of public school students, to strengthen the quality of education in public schools -senior high schools at that -and be at par with or even beyond the quality performance of private schools.
Abbreviations: Science, Technology, Engineering, and Mathematics (STEM); Senior High School (SHS) Funding: The researcher received no funding from any academic organization nor from Samar State University, the institution where she was connected while completing this study. The article processing charge (APC) was shouldered by the author herself.

Conflicts of Interest:
The researcher hereby declares that there is no conflict of interest upon and throughout the conduct of this study. Publisher's Note: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. ORCID iD -https://orcid.org/0000-0002-6552-1611