








































English Language Teaching Educational Journal   ISSN 2621-6485 

Vol. 8, No. 2, August 2025, pp. 133-151  

        https://doi.org/10.12928/eltej.v8i2.13434        http://journal2.uad.ac.id/index.php/eltej/index         eltej@pbi.uad.ac.id  

A correspondence analysis of English proficiency and 

demographic factors among EFL students at Burapha 

University, Thailand 

Piyapohn Pohnsuriya 

Language Institute, Burapha University, 169 Long Had Bangsaen Rd, Saen Suk, Chonburi 20131, Thailand 

piyaporn.po@go.buu.ac.th  

 

A R T I C L E  I N F O 

 
 

ABST RACT   

 

 

Article history 

Received 15 June 2025 

Revised 17 July 2025 

Accepted 4 August 2025 

 The study aimed to determine the correspondence association between 
English proficiency and demographic factors of EFL students. The 
sample consisted of 385 non-English major students at Burapha 
University, Thailand. The English test scores and demographic factors 
were analyzed using descriptive statistical methods, the Chi-square 
test, and correspondence analysis. The results showed that English 
proficiency was not associated with gender. However, the English 
proficiency level corresponded with the age groups and faculties. 
Moreover, students from high-income families tended to have higher 
proficiency, while those from moderate-income families tended to 
have moderate proficiency. Parents’ education and occupations also 
correspond with the English proficiency level.  

 

© The Authors 2025. Published by Universitas Ahmad Dahlan. 

This is an open access article under the CC–BY-SA license. 

    

 

 

Keywords 

English proficiency 

BUU-CET U level 

Demographic 

Association 

EFL Learners 

 

 

 

 

How to Cite: Pohnsuriya, P. (2025). A correspondence analysis of English proficiency and demographic factors 
among EFL students at Burapha University, Thailand. English Language Teaching Educational Journal, 8(2), 
133-151. https://doi.org/10.12928/eltej.v8i2.13434   

1. Introduction  

English proficiency is a crucial skill for students in higher education, yet many non-English majors 
still struggle to develop these skills. A nationwide study on English receptive skills revealed that Thai 
undergraduates scored an average of 342.55 out of 990 on the TOEIC test, with significant differences 
observed across gender and major (Jehma et al., 2021). Despite Thailand’s ongoing English education, 
many non-English major students face challenges such as limited real-world practice, rote-based 
instruction, and inadequate exposure—especially in rural or under-resourced settings 
(Huttayavilaiphan, 2025). Similar to many other universities, Burapha University’s students face 
challenges in achieving English skills. However, there is limited evidence in this specific context, as 
most studies were focused on foreign students, high school students, or other institutions. As Burapha 
University students come from various backgrounds, demographic are factors are considered to affect 
their English proficiency. So, this study aims to investigate the factors that may influence the English 
language proficiency of students who are not majoring in English at Burapha University (BUU). As 
English has become an international language, encouraging language skills has become the primary 
goal in schools’ and universities’ efforts to teach and create a proper learning environment for their 
students. Over the years, English has become one of the critical languages that one should acquire as 
a survival skill. Government and private organizations commonly use the English score as a criterion 
for recruiting employees (Arisa JK, 2018). Higher English proficiency could promise career 
opportunities, high—level job security, and income (Prasobnet, 2018). Therefore, proficiency among 
university students, particularly those not majoring in English, should be a concern as they enter the 
workforce. English could guarantee their success in getting hired and receiving a reasonable salary. 

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134 English Language Teaching Educational Journal   ISSN 2621-6485 

 Vol. 8, No. 2, August 2025, pp. 133-151 

 Pohnsuriya, P. (A correspondence analysis of English proficiency and demographic factors among…..) 

The question is what factors could influence their English proficiency and shed light on how to 
effectively handle EFL students. 

Demographic factors, including gender, age, year of study, and faculty, were examined. They can 
play a crucial role in students’ educational outcomes by trying to understand how they influence 
academic performance for valuable insights. Gender is considered a significant factor that researchers 
focus on in many aspects of the academic field. In language acquisition, it has been found that men 
and women use language differently, with women generally being more proficient in language than 
men (Alotaibi, 2024), yet there were no appreciable differences in the autonomous English learning 
factors between students in the Art-English program and those in the Science-Mathematics program; 
students in the Art-English program were found to have higher autonomous English learning than 
students in the Science-Mathematics program (Preepool, 2017). However, the choice of faculty in a 
university can create distinct learning environments and expectations that influence the students’ 
English performance and scores (Azkiyah, 2018). 

Moreover, demographic factors about family status, including parents’ education, occupation, and 
family income, are also significant circumstances in language acquisition. Yahaya et al. (2011) 
suggested that parents provide two-language learning resources to make a bilingual child, which could 
be attributed to parental socioeconomic status. The languages in a family are associated with a child’s 
language proficiency and comprehension (Volodina et al., 2021). It was also suggested that the 
language outcome was influenced by the level of a parent's engagement with the children (Varghese 
& Wachen, 2015). However, the social cognitive theory argues that the importance of other parties in 
society also influences second language acquisition and language proficiency. Therefore, family status 
is highlighted as a significant factor influencing English proficiency in EFL Students.  

Understanding the key factors that affect language acquisition can lead to the adaptation of 
practical educational approaches and classroom interactions. There have been many studies that have 
realized the importance of Teacher cognition, which refers to the direct effect of the teacher’s attitude 
on teaching in the classroom (Zheng et al., 2022; Chen & Abdullah, 2022) as there were problems 
with the idea of a "one-size-fits-all" classroom, or the teaching that fits everyone without considering 
the diverse needs of learners (Chen & Abdullah, 2022). This concept is closely related to the 
Sociocultural Theory of Vygotsky (1978), which stated that learning is a social process, and a child's 
home environment provides the main "cultural toolkit" for their language development. Moreover, 
learning was not only an intrapersonal intellectual process but a process that occurs through social 
interaction via mediation (Hughes, 2021). Therefore, environmental factors also play a significant role 
in the acquisition of knowledge. 

In terms of the English proficiency test, BUU-CET U is an exit exam administered by Burapha 
University, as it is considered a standard test of the university that measures students’ English 
language skills upon entry and before graduation. BUU-CET U consists of two parts: the listening and 
the reading parts, allowing students to demonstrate their language comprehension at the collegiate 
level. The test score of BUU-CET U can also be equivalent to other standard tests, including the CEFR 
(Common European Framework of Reference for Languages) and the TOEIC (Test of English for 
International Communication). The score comparison table is shown in Table 1 (BUULI, 2025). 

Table 1.  Score comparison of BUU-CET U, CEFR Level, and TOEIC 

BUU-CET U Score BUU-CET U Level CEFR Level TOEIC Score 

1-20 Level 1 A1 120 

21-40 Level 2 A2~A2+ 170 

41-50 Level 3 A2+~B1 225 

51-60 Level 4 B1~B1+ 550 

 

Unlike other studies in the area, this research employs correspondence analysis to visually 
represent the multivariate relationships between language proficiency and demographic factors in a 
graphical format. This method provides a geometric representation of the rows and columns of a two-
way frequency table, aiding in the interpretation of similarities among category levels and the 
associations between variables (Greenacre, 2017). Moreover, it focuses specifically on non-English 
major students at Burapha University, reflecting the big picture of the EFL students in Thailand 



ISSN 2621-6485 English Language Teaching Educational Journal 135 
         Vol. 8, No. 2, August 2025, pp. 133-151 

 Pohnsuriya, P. (A correspondence analysis of English proficiency and demographic factors among…..) 

(Huttayavilaiphan, 2025). The findings of this study are expected to provide practical implications for 
the development and improvement of English teaching practices in similar educational contexts, 
thereby filling a research gap in the Thai university setting. These can fill in the research gap and 
develop the education. 

2. Method 

The respondents of this research were 385 non-English major undergraduate students at Burapha 
University. Taro Yamane’s formula was used to calculate the sample size with a margin of error of 
0.05, based on an estimated population of 10,000 students who had taken the BUU-CET U test in the 
past three years. The respondents were selected using a simple random sampling method.  

The instrument used in this study was a questionnaire to collect data, including English proficiency 
scores, students' BUU-CET U results, which they received upon completing the exam, and 
demographic background information: gender, age, year of study, faculty, family income, father’s 
education, mother’s education, father’s occupation, and mother’s occupation. The students majoring 
in English were excluded from the sample to ensure the focus on non-English majors. The validity of 
the instrument was validated by three experts, with a coefficient of more than 0.5. The reliability was 
confirmed through a pilot test with 30 non-English major students, with a coefficient of 0.88, which 
is considered acceptable.  

The study received ethical approval (HU085/2565(E2)) from the Human Research Ethics 
Committee of Burapha University. Data collection was conducted after students completed the CUU-
CET U exam, and they were invited to complete the questionnaire. The students were informed about 
the purpose of the research and asked to provide consent voluntarily.  

The data was analyzed using descriptive statistics, including frequency and percentage, to 
summarize the demographic data and English proficiency scores. Correspondence analysis, including 
the Chi-square test, was used to assess the associations between variables and to visually represent the 
relationships between variables, as it displays multidimensional associations in a biplot, facilitating 
the interpretation of the correspondence between factors and proficiency. 

3. Finding 

3.1. Demographic information of the respondents 

The data collected in this research were from a questionnaire completed by 385 students. The 
respondents were divided by gender, age group, year of study, and faculty (Table 2). 

Based on Table 2, the respondents comprised 122 male students (31.7%) and 263 female students 
(68.3%). There were 72 students (18.7%) lower than 20 years of age, 272 students (70.6%) 20-22 
years of age, and 41 students (10.6%) older than 22 years of age. The respondents in the 1st year were 
74 students (19.2%), in the 2nd year were 58 students (15.1%), in the 3rd year were 82 students 
(21.3%), in the 4th year were 157 students (40.8 %), and in the 5th and 6th year were 14 students 
(3.6%). Those respondents are from various faculties, including 18 students from Fine and Applied 
Arts (4.7%), 39 students from Business Administration (10.1%), 4 students from Tourism 
Management (1%), 59 students from Political Science (15.3%), 49 students from Education (12.7%), 
38 students from Humanity and Social Science (9.9%), 5 students from Music and Performing Arts 
(1.3%), 4 students from Geography and Geoinformatics (1%), 17 students from Science (4.4%) 31 
students from Logistics (8.1%), 18 students from Engineering (4.7%), 16 students from Informatics 
(4.2%), 36 students from Sports Science (9.4%), 38 students from Allied Health Science (9.9%), 8 
students from Pharmaceutical Sciences (2.1%), and 5 students from Nursing (1.3%). 

  



136 English Language Teaching Educational Journal   ISSN 2621-6485 

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Table 2.  Personal information of the respondents (n = 385) 

Characteristics Category Frequency Percentage 

Gender Male 122 31.7 

 Female 263 68.3 

Age Groups  Lower than 20 years 72 18.7 

 20 - 22 years 272 70.6 

 Higher than 22 years 41 10.6 

Year of Study 1st year  74 19.2 

 2nd year  58 15.1 

 3rd year  82 21.3 

 4th year  157 40.8 

 5th and 6th year  14 3.6 

Faculty  Fine and Applied Arts 18 4.7 

  Business Administration 39 10.1 

  Tourism Management 4 1 

Art Group Political Science 59 15.3 

  Education 49 12.7 

  Humanity and Social Science 38 9.9 

  Music and Performing Arts 5 1.3 

  Geography and Geoinformatics 4 1 

  Science 17 4.4 

Science Group 
Logistics 31 8.1 

Engineering 18 4.7 

  Informatics 16 4.2 

  Sports Science 36 9.4 

Health Science Group 

Allied Health Sciences 38 9.9 

Pharmaceutical Sciences 8 2.1 

Nursing 5 1.3 

 

Based on Table 3, most respondents (222 students) received the BUU-CET U Level 2, accounting 
for 57.7%. The other BUU-CET U levels received were level 3 (96 students), accounting for 24.9%; 
level 1 (38 students), accounting for 9.9 %; and level 4 (29 students), accounting for 7.5%, 
respectively. 

Table 3.  BUU-CET U level of the respondents (n = 385) 

BUU-CET U level Frequency Percentage 

Level 1 38 9.9 

Level 2 222 57.7 

Level 3 96 24.9 

Level 4 29 7.5 

 

Based on Table 4, the family income among the students was mainly 30,000 Baht or lower, 
accounting for 44.9% (173 students). There were 133 families of students who received 30,001-60,000 
Baht (34.5%), 56 families of students received 60,001-100,000 Baht (14.5%), and 23 families of 
students received More than 100,000 Baht (6%). 

According to the father's education, 242 students (62.9%) whose fathers’ educational degrees were 
lower than a bachelor’s, 123 students (31.9%) whose fathers received bachelor’s degrees, 17 students 
(4.4%) whose fathers had a master’s degree, and 3 students (0.8%) whose fathers had a Ph.D. 



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According to the mother’s education, there were 254 students (66%) whose mothers’ educational 
degrees were lower than a bachelor’s degree, 115 students (29.9%) whose mothers received bachelor’s 
degrees, 15 students (3.9%) whose mothers had a master’s degree, and one student (0.3%) whose 
mother had Ph.D. 

Based on the father’s occupation, 59 students (15.3%) had fathers who were business owners, 69 
students (17.9%) had fathers who were government officers, 80 students (20.8%) had fathers who 
were company employees, 124 students (32.2%) had fathers who were freelancers, 11 students (2.9%) 
had fathers who were househusbands, and 42 students (10.9%) were fatherless.  

Based on the mother’s occupation, 53 students (13.8%) had mothers who were business owners, 
44 students (11.4%) had mothers who were government officers, 77 students (20%) had mothers who 
were company employees, 132 students (34.3%) had mothers who were freelancers, 68 students 
(17.7%) had mothers who were housewives, and 11 students (2.9%) were motherless. 

Table 4.  Family status of the respondents (n = 385) 

Characteristics Category Frequency Percentage 

Family Income 30,000 Baht and lower (low) 173 44.9 

 30,001-60,000 Baht (moderate) 133 34.5 

 60,001-100,000 Baht (high) 56 14.5 

 More than 100,000 Baht (very high) 23 6.0 

Father’s Education Lower than Bachelor 242 62.9 

 Bachelor’s degree 123 31.9 

 Master’s degree 17 4.4 

 Ph.D. 3 0.8 

Mother’s Education Lower than Bachelor 254 66.0 

 Bachelor’s degree 115 29.9 

 Master’s degree 15 3.9 

 Ph.D. 1 0.3 

Father’s Occupation Business owner 59 15.3 

 Government/State officer 69 17.9 

 Company employees 80 20.8 

 Freelance 124 32.2 

 Househusband 11 2.9 

 Fatherless 42 10.9 

Mother’s occupation Business owner 53 13.8 

 Government/State officer 44 11.4 

 Company employees 77 20.0 

 Freelance 132 34.3 

 Housewife 68 17.7 

 Motherless 11 2.9 

3.2.  Correspondence association between demographic factors and the BUU-CET U level 

The study inspected the relationship between BUU-CET U level and demographic factors, 
including gender, age, year of study, faculty, family income, father’s education, mother’s education, 
father’s occupation, and mother’s occupation. The data were statistically analyzed by correspondence 
analysis, and the results were as follows. 

1) Correspondence association between the gender group and the BUU-CET U level  

The correspondence analysis results between the gender group, and the BUU-CET U level of the 
respondents showed no association, as indicated by the Chi-square test of correspondence analysis 
(Chi-square = 2.41, Prob = 0.492). This showed that the BUU-CET U score was not associated with 
the students’ genders. The contingency table and Chi-square test for the correspondence analysis of 



138 English Language Teaching Educational Journal   ISSN 2621-6485 

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the gender group and the BUU-CET U level are presented in Tables 5 and 6, respectively. It is noted 
here that the perceptual biplot map cannot be plotted if any dimension (in this case, gender) has only 
two groups. 

Table 5.  Contingency table of the gender group and the BUU-CET U level 

Gender group 
Frequency of BUU-CET U level 

Total Level 1 Level 2 Level 3 Level 4 

Male 16  68 28 10 122 

Female 22 154 68 19 263 

Total 38 222 96 29 385 

Table 6.  Correspondence analysis of the gender group and the BUU-CET U level 

Dimension Singular Value Inertia Chi-Square Prob. (df=3) 
Percent of Inertia 

Account for Cumulative 

1 0.079 0.006 2.41   100 100 

Total   0.006 2.41 0.492 100  

 

2) Correspondence association between the age group and the BUU-CET U level 

According to the correspondence analysis between age group and BUU-CET U level, illustrated 
in Tables 7 and 8, the Chi-square value equaled 10.75 (p = 0.096). It is implied that the null hypothesis 
was accepted with a statistical significance of 0.05. There was no correspondence between the age 
group and the BUU-CET U level. It was also found that dimensions 1 and 2 could explain the trend, 
accounting for 100% of the inertia (Table 8). Once the data were plotted into a biplot graph, the trend 
position of the association between the two variables, as shown in Fig. 1, indicated that the BUU-CET 
U level 4 tended to associate with the age group of more than 22 years. While the age group of 20-22 
years tended to closely associate with the BUU-CET U level 3, and the age group lower than 20 years 
tended to closely associate with the BUU-CET U level 1 (Fig. 1). 

Table 7.  Contingency table of the age group and the BUU-CET U level 

Age group 
Frequency of BUU-CET U level 

Total Level 1 Level 2 Level 3 Level 4 

Lower than 20 10 43 16 3 72 

20 - 22 years 27 154 72 19 272 

Higher than 22 1 25 8 7 41 

Total 38 222 96 29 385 

Table 8.  Correspondence analysis of the age group and the BUU-CET U level 

Dimension Singular Value Inertia Chi-Square Prob. (df=6) 
Percent of Inertia 

Account for Cumulative 

1 0.159 0.025 9.74    90.6 90.6 

2 0.051 0.003 1.01   9.4 100 

Total   0.028 10.75 0.096 100  



ISSN 2621-6485 English Language Teaching Educational Journal 139 
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Fig. 1.  Correspondence analysis biplot showing the association position of the age group and the BUU-CET 

U level 

3) Correspondence association between the year of study and the BUU-CET U level 

An analysis of the correspondence between the year of study and the BUU-CET U level of Burapha 
University students, as displayed in Tables 9 and 10, found that the Chi-square value equaled 37.19 
(Prob. = 0.0002). The results implied that the null hypothesis was rejected at a significance level of 
0.01, indicating a significant association between BUU-CET U level and the year of study. It was 
found that dimensions 1 and 2 could explain 90.02% of the inertia (Table 10). The biplot graph was 
plotted with dimensions 1 and 2 of the association position of the two variables. Fig. 2 stated that level 
4 corresponded most with 5th-year and 6th-year students, with a strong association. Level 3 had the 
most correspondence with 2nd-year students. Level 2 had the most correspondence with students in 
years 1, 3, and 4, exhibiting a weak association, as their positions were close to the origin (Fig. 2). 

Table 9.  Contingency table of the year of study and the BUU-CET U level 

Year of Study 
Frequency of BUU-CET U level 

Total 
Level 1 Level 2 Level 3 Level 4 

1st year 12 46 11 5 74 

2nd year 7 23 25 3 58 

3rd year 10 54 15 3 82 

4th year 9 94 40 14 157 

5&6th year 0 5 5 4 14 

Total 38 222 96 29 385 

Table 10.  Correspondence analysis of the year of study and the BUU-CET U level 

Dimension Singular Value Inertia Chi-Square 
Prob. 

(df=12) 

Percent of Inertia 

Account for Cumulative 

1 0.240 0.057 22.11    59.44 59.44 

2 0.172 0.030 11.37   30.58 90.02 

3 0.098 0.010  3.71   9.98 100 

Total   0.097 37.19 0.0002 100  



140 English Language Teaching Educational Journal   ISSN 2621-6485 

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 Pohnsuriya, P. (A correspondence analysis of English proficiency and demographic factors among…..) 

 

Fig. 2.  Correspondence analysis biplot showing the association position of the year of study and the BUU-

CET U level 

4) Correspondence association between the faculty group and the BUU-CET U level 

The study divided faculties into three groups: Art, Science, and Health Science. Art faculties 
included Fine and Applied Arts, Business Administration, Tourism Management, Political Science, 
Education, Humanities and Social Science, and Music and Performing Arts. Science faculties included 
Geography and Geoinformatics, Science, Logistics, Engineering, Informatics, and Sports Science. 
Health science faculties included Allied Health Sciences, Pharmaceutical Sciences, and Nursing. 
Therefore, in the correspondence analysis between the faculty group and the BUU-CET U level, as 
shown in Tables 11 and 12, it was found that the Chi-square value equaled 27.11 (Prob. = 0.0001), 
which rejected the null hypothesis at a significant level of 0.01. There was an association between the 
BUU-CET U level and the faculty groups. According to the correspondence analysis, dimensions 1 
and 2 could explain the relationship with 100% of the inertia (Table 12). When the biplot graph was 
plotted to show the association position of the two variables, as shown in Fig. 3, it was found that the 
Health Science faculty group had the most correspondence with the BUU-CET U level 4, with a 
significant association, since their positions were far from the origin. The Science faculty group had 
the most correspondence association with the BUU-CET U level 2. The Art faculty group tended to 
associate more with BUU-CET U level 1 since they both had an acute angle from the origin (Fig. 3). 

Table 11.  Contingency table of the faculty group and the BUU-CET U level 

Faculty group 
Frequency of BUU-CET U level 

Total 
Level 1 Level 2 Level 3 Level 4 

Art 24 119 56 13 212 

Science 14 81 21 6 122 

Health Science 0 22 19 10 51 

Total 38 222 96 29 385 

Table 12.  Correspondence analysis of the faculty group and the BUU-CET U level 

Dimension Singular Value Inertia Chi-Square Prob. (df=6) 
Percent of Inertia 

Account for Cumulative 

1 0.254 0.064 24.80    91.47 91.47 

2 0.078 0.006  2.31     8.53 100 

Total   0.070 27.11 0.0001 100  



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Fig. 3.  Correspondence analysis biplot showing the association position of the faculty group and the BUU-

CET U level 

5) Correspondence association between the family income level and the BUU-CET U level 

According to Tables 13 and 14, the results of the correspondence analysis between the family 
income level and the BUU-CET U level of Burapha University students showed that the Chi-square 
value equaled 12.30 (Prob. = 0.197), indicating that the null hypothesis was accepted. It was implied 
that there was no significant association between the student’s family income and BUU-CET U level, 
with dimensions 1 and 2 accounting for 98.51% of the inertia (Table 14). However, according to the 
biplot perceptual graph (Fig. 4), students from high-income families tended to have high BUU-CET U 
scores at level 4, and students from moderate-income families tended to have moderate BUU-CET U 
scores at level 2. 

Table 13.  Contingency table of the family income level and the BUU-CET U level 

Family income 

level 

Frequency of BUU-CET U level 
Total 

Level 1 Level 2 Level 3 Level 4 

Low  21 104 39 9 173 

Moderate  13 80 30 10 133 

High  2 28 19 7 56 

Very High  2 10 8 3 23 

Total 38 222 96 29 385 

Table 14.  Correspondence analysis of the family income level and the BUU-CET U level 

Dimension Singular Value Inertia Chi-Square Prob. (df=9) 
Percent of Inertia 

Account for Cumulative 

1 0.172 0.029 11.32  92.06 92.06 

2 0.045 0.002 0.79  6.45 98.51 

3 0.022 0.001 0.18  1.49 100 

Total  0.032 12.30 0.197 100  



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Fig. 4.  Correspondence analysis biplot showing the association position of the family income level and the 

BUU-CET U level 

3.2.6 Correspondence association between the father’s education level and the BUU-CET U level 

According to the results of the correspondence analysis between the father’s education level and the 
BUU-CET U level of students at Burapha University in Tables 15 and 16, it was found that the Chi-
square value equaled 29.04 (Prob. = 0.001), which meant that it accepted the alternative hypothesis 
with a significance level of 0.01. It was implied that there was an association between the father’s 
education and the BUU-CET U level, with dimensions 1 and 2 accounting for 99.95% of the inertia 
(Table 16). When the biplot graph was plotted to show the association position of the two variables, 
as shown in Fig. 5, it was found that students whose fathers had a master’s degree had the most 
correspondence with the BUU-CET U level 4. Those with a bachelor’s degree had the most 
correspondence with the BUU-CET U level 3. Those with education below a bachelor’s degree were 
most closely aligned with the BUU-CET U level 2 and level 1 (Fig. 5). 

Table 15.  Contingency table of the father’s education level and the BUU-CET U level 

Father’s education 

level 

Frequency of BUU-CET U level 
Total 

Level 1 Level 2 Level 3 Level 4 

Lower than Bachelor 27 146 57 12 242 

Bachelor’s degree 11 65 37 10 123 

Master’s degree 0 9 2 6 17 

Ph.D. 0 2 0 1 3 

Total 38 222 96 29 385 

Table 16.  Correspondence analysis of the father’s education level and the BUU-CET U level 

Dimension Singular Value Inertia Chi-Square Prob. (df=9) 
Percent of Inertia 

Account for Cumulative 

1 0.260 0.067 25.93  89.29 89.29 

2 0.090 0.008 3.06  10.66 99.95 

3 0.006 0.000 0.01     0.05 100 

Total  0.075 29.04 0.001 100  



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Fig. 5.  Correspondence analysis biplot showing the association position of the father’s education level and 

the BUU-CET U level 

6) Correspondence association between the mother’s education and the BUU-CET U level 

According to the results of the correspondence analysis between the mother's education and the 
BUU-CET U level of students of Burapha University, as displayed in Tables 17 and 18, it was found 
that the Chi-Square value equaled 18.12 (Prob. = 0.034), which meant that it accepted the alternative 
hypothesis with the significance level of 0.05. It was implied that there was an association between the 
mother’s education level and BUU-CET U level, with dimensions 1 and 2 accounting for 91.7% of the 
inertia (Table 18). When the biplot graph was plotted to show the association between the two 
variables, as shown in Fig. 6, it was found that students whose mothers held doctoral degrees did not 
correspond with any BUU-CET U level. However, those with a bachelor's degree had the most 
correspondence with the BUU-CET U level 1 and level 3, and those with a lower degree than a 
bachelor's degree had the most correspondence with the BUU-CET U level 2. It was also found that 
students whose mothers got master's degrees tended to associate with BUU-CET U level 2 (Fig. 6). 

Table 17.  Contingency table of the mother’s education level and the BUU-CET U level 

Mother’s education 

level 

Frequency of BUU-CET U level 
Total 

Level 1 Level 2 Level 3 Level 4 

Lower than Bachelor 28 149 60 17 254 

Bachelor’s degree 10 62 34 9 115 

Master’s degree 0 11 2 2 15 

Ph.D. 0 0 0 1 1 

Total 38 222 96 29 385 

Table 18.  Correspondence analysis of the mother’s education level and the BUU-CET U level 

Dimension Singular Value Inertia Chi-Square Prob. (df=9) 
Percent of Inertia 

Account for Cumulative 

1 0.187 0.035 13.48  74.43 74.43 

2 0.090 0.008 3.14  17.30 91.73 

3 0.062 0.004 1.50  8.27 100 

Total  0.047 18.118 0.034 100  



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Fig. 6.   Correspondence analysis biplot showing the association position of the mother’s education level and 

the BUU-CET U level 

7) Correspondence association between the father’s occupation and the BUU-CET U level 

According to the correspondence analysis between the father’s occupation and the BUU-CET U 
level of students at Burapha University, as shown in Tables 19 and 20, the Chi-square value was 21.33 
(Prob. = 0.127), indicating that the null hypothesis was accepted. It was implied that there was no 
association between the father’s occupation and BUU-CET U level, with dimensions 1 and 2 
accounting for 97.26% of the inertia (Table 20). However, according to the perceptual biplot in Fig. 7, 
it was revealed that students whose fathers were freelancers tended to associate closely with BUU-CET 
U level 2, while those whose fathers were company employees tended to associate with level 3. 

Table 19.  Contingency table of the father’s occupation and the BUU-CET U level 

Father’s occupation 
Frequency of BUU-CET U level 

Total 
Level 1 Level 2 Level 3 Level 4 

Business owner 7 27 20 5 59 

Gov./State officer 6 42 10 11 69 

Company Employee 8 42 26 4 80 

Freelancer 13 77 26 8 124 

Steward 1 8 2 0 11 

Fatherless 3 26 12 1 42 

Total 38 222 96 29 385 

Table 20.  Correspondence analysis of the father’s occupation and the BUU-CET U level 

Dimension Singular Value Inertia Chi-Square 
Prob. 

(df=15) 

Percent of Inertia 

Account for Cumulative 

1 0.193 0.037 14.40  67.52 67.52 

2 0.128 0.016 6.34  29.75 97.26 

3 0.039 0.002 0.58    2.74 100 

Total  0.055 21.33 0.127 100  



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Fig. 7.  Correspondence analysis biplot showing the association position of the father’s occupation and the 

BUU-CET U level 

8) Correspondence association between the mother’s occupation and the BUU-CET U level 

According to the correspondence analysis between the mother’s occupation and the BUU-CET U 
level of students at Burapha University, as shown in Tables 21 and 22, it was suggested that the Chi-
square value equaled 29.42 (Prob. = 0.014), which means that it accepted the alternative hypothesis at 
the significance level 0.05. It was implied that there was an association between the mother’s 
occupation and BUU-CET U level, with dimensions 1 and 2 accounting for 93.65% of the inertia (Table 
22). When the biplot graph was plotted to show the association position of the two variables, as shown 
in Fig. 8, it was found that students whose mothers were housewives had the most correspondence 
with the BUU-CET U level 2 and level 4, and those whose mothers worked for private companies or 
were business owners had the most correspondence with the BUU-CET U level 3. The BUU-CET U 
level 1 did not tend to correspond with any mother’s occupation (Fig. 8). 

Table 21.  Contingency table of the mother’s occupation and the BUU-CET U level 

Mother’s 

occupation 

Frequency of BUU-CET U level 
Total 

Level 1 Level 2 Level 3 Level 4 

Business owner 3 30 18 2 53 

Gov./State officer 3 32 6 3 44 

Company employee 5 39 27 6 77 

Freelancer 18 79 24 11 132 

Housewife 6 40 15 7 68 

Motherless 3 2 6 0 11 

Total 38 222 96 29 385 

Table 22.  Correspondence analysis of the mother’s occupation and the BUU-CET U level 

Dimension Singular Value Inertia Chi-Square 
Prob. 

(df=15) 

Percent of Inertia 

Account for Cumulative 

1 0.223 0.050 19.18  65.18 65.18 

2 0.147 0.022 8.38  28.47 93.65 

3 0.070 0.005 1.87     6.35 100 

Total  0.076 29.42 0.014 100  



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Fig. 8.  Correspondence analysis biplot showing the association position of the mother’s occupation and the 

BUU-CET U level 

4. Discussion 

4.1.  Gender 

According to the correspondence analysis, no association was found between the BUU-CET U 
level and the gender groups. The results agreed with the study by Rianto (2021) and Liu (2015), which 
found no gender difference in online English proficiency. In contrast, Rianto (2021) reported that 
female students used reading strategies more frequently and creatively than male students and adopted 
support strategies more often than males. Similarly, Pei & Pamintuan (2024) and Al-Saadi (2020) 
argued that females generally demonstrated better English proficiency than male students in speaking 
and writing. As this study found that this was not the case, it implies that teachers may not need to 
focus on gender as much. However, the probable reason for the results could be the balance of students 
in different faculties and the ratio of males to females in each. Therefore, the issue should not be 
dropped entirely when conducting research or designing a classroom.  

4.2.  Age 

The correspondence biplot for age and year of study clearly showed that the older students and 
those with a longer year of study had higher English proficiency. It is consistent with the study of 
Serquina & Batang (2018), who concluded that as age increases, proficiency progresses. The reason 
might be that the students had taken English courses throughout the program, enhancing their skills. 
A study confirmed that students’ English skills improved significantly during their freshman and 
sophomore years due to the intensive courses (Tsui, 2024). However, with a narrow gap in age and 
year of study, relevant research focusing on these issues was scarce, yet it was logical that this was 
the case. 

4.3.  Faculty groups 

According to the faculty group, it was highly associated with English proficiency. The Health 
Science faculty group was closely associated with high English proficiency. These results are in line 
with the study of Azkiyah (2018), who showed that the students in the Faculty of Medicine achieved 
the highest English proficiency among the 12 faculties, and another study supporting these results 
indicated that students from the Faculty of Medicine received the highest score (Azkiyah et al., 2023). 
However, Din & Saeed (2018) argued that the faculty did not have an effect on English proficiency, 
but instead only had an impact on academic achievement. As the Health Science faculty group is 



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highly competitive for entering the university in Thailand, students must achieve relatively high scores 
to be accepted into the major. Moreover, the textbooks used were generally in English. As a result, 
the students in the field might have been more familiar with the language than the Art faculty group 
students, and tend to acquire better English performance.  

4.4.  Family income 

According to the family income aspect, students from high-income families were closely associated 
with high English proficiency. As a result, the higher the family’s income, the higher the students’ 
English performance tended to be (Fortes et al., 2022; Nguyen et al., 2021), as the family’s income 
level could indicate how much parents can provide a suitable environment and support for their 
children (Baker, 2014). Language opportunities and the time involvement of both fathers and mothers 
are factors that shaped children’s language outcomes, and the family that supported, including 
providing an English environment, had influenced children’s foreign language learning 
(Triwittayayon & Sarobol, 2018). However, some believed that learning should not only start in a 
family but also at school and in the community (Nafrizam & Jamaluddin, 2023). This is where the 
teacher's role comes in. Despite their background, opportunities, and learning environment, the 
students must also be aware that they are the main factor in their learning progress. They must also 
find their own motivation to improve and succeed (Yen et al., 2019). This is where the teacher’s role 
steps in, helping and supporting students with positive attitudes, recognizing that there is no "one-
size-fits-all" classroom without considering the diverse needs of learners (Chen & Abdullah, 2022). 
The teacher can become the missing piece to help students fulfill their motivation and enhance their 
language skills.  

4.5.  Parental education level 

In this study, parental education level, particularly for the father, has an impact on students' English 
performance. Fortes et al. (2022) agreed with the results that the higher the parents’ degree, the better 
the academic performance and English proficiency of the students. Likewise, Baker (2013) and 
Duursma et al. (2008) confirmed that the father’s educational level influences the children’s literacy, 
and Pei and Pamintuan (2024) also found that the father’s education level has a more significant 
influence than the mother’s. This is the case because educated parents can create a language-rich 
environment by engaging in English conversations, reading English books, exploring vocabulary, 
assisting with homework, and supporting educational resources (Ntabwoba & Sikubwabo, 2024). 
Parents tended to encourage their children to pursue English when they recognized the importance of 
the language (Rahman, 2016). Thus, higher education could help them realize the importance of 
learning in general and the value of learning languages.  

4.6.  Parental occupation 

The results showed that the parental occupation was associated with English proficiency. Although  
the parental occupations did not show a significant difference in students at a lower level of education 
(Trebits et al., 2021), Fortes et al. (2022) supported that parents’ jobs in high social status positively 
affect their children’s language performance, as they recognize the importance of the English language 
as a tool to widen their world. Pratomo et al. (2016) suggested that children’s development is highly 
influenced by their mothers’ occupation, especially those who work as housewives, due to the amount 
of time spent with them, indicating that nurture plays a role in language development. This is 
consistent with the current study, which found that students whose mothers were housewives were 
associated with a high level of proficiency. Moreover, Farah (2018) suggested that occupations with 
high social status led to less financial stress for families and had a positive impact on children in the 
long run, which agrees with the result that students whose parents worked as company employees, 
which is considered to have good earnings, received relatively high proficiency levels in this study.  

Overall, as Vygotsky (1978) suggested, learning is a social process, and the home environment 
serves as a primary "cultural toolkit" for a child's linguistic development. Parents with higher levels 
of education or in certain professions may not only possess a more sophisticated vocabulary but also 
actively engage in their children's learning. So, the child would majorly benefit from their background. 
However, the improvement in a student's language proficiency at any level relies on the role of teacher 
cognition; a teacher's beliefs, knowledge, and practices are critical factors that can reinforce the effects 
of a student’s home background (Borg, 2006). For instance, a teacher who believes that a student's 
background is connected to their ability may unknowingly lower their expectations and create a 
compromising teaching method that fits, considering the diverse needs of learners (Chen & Abdullah, 



148 English Language Teaching Educational Journal   ISSN 2621-6485 

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 Pohnsuriya, P. (A correspondence analysis of English proficiency and demographic factors among…..) 

2022). By integrating these theoretical aspects, we can propose actionable strategies to improve 
English outcomes for EFL learners. 

4. Conclusion 

This study revealed that demographic factors affected the English proficiency of EFL students at 
Burapha University, Thailand. A perceptual map of the correspondence analysis displayed the 
closeness of each factor's level to students' English proficiency level, in addition to the general 
associations. Older age groups and higher years of study were associated with students achieving 
higher English proficiency levels. Students from high-income families tended to have the highest 
English proficiency level. Parental education and occupation were also found to be associated with 
English proficiency. This study is therefore helpful for teachers to anticipate students’ proficiency 
levels in relation to different demographic factors, enabling them to effectively plan teaching methods 
that suit the diverse needs of learners, and guide further development of EFL learners to achieve higher 
English language proficiency. This, in turn, will help fill a research gap in the Thai university setting 
and the broader educational field. 

 

 

Acknowledgment 

The researcher would like to thank the participating students for providing information for this 
research. I would also like to thank the staff and executives of the Language Institute at Burapha 
University for facilitating the completion of this research. 

 

 

Declarations 

Author contribution : Piyapohn Pohnsuriya is the sole author and is fully responsible for 
    this article. 

Funding statement : This research was not funded by any agency. 

Conflict of interest : The author declares no conflict of interest. 

Ethics Declaration        : The author confirms that this work is written based on the research 
 ethics principles and under the regulations of Burapha University 
 and received permission from the university during the data
 collection. I support ELTEJ in maintaining high standards of 
 personal conduct and practicing honesty in all our professional
 practices and endeavors. 

Additional information: No additional information is available for this paper. 

 
 

 

 
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