Evaluating Socioeconomic Influences on English Language Proficiency among Secondary School Students in Trivandrum

Socioeconomic status is a complex idea that refers to a variety of financial and social indicators reflecting both individual and group life styles. It plays a crucial role in everyday life, revealing the advantages and disadvantages of present conditions. SES is often determined by education, income and occupation, which have a significant impact on language learning. There is a solid relationship among SES and students’ proficiency in English, as it greatly influences their language learning experiences and vocabulary development [1].  

English is the third most spoken language globally, and its widespread teaching and use make it indispensable in today’s globalized world. It facilitates international communication, cultural exchange and access to higher education resources, as the majority of academic books are written in English. It is the language of innovation, science and technology, offering access to modern research and numerous employment opportunities [2].  Proficiency in English encourages global citizenship, encourages online participation, and improves travel and tourism experiences. Learning English is important to overcome academic challenges, specifically when it comes to refining students’ practical language skills. Language proficiency is essential for learners to advance in both life and the workplace. It provides individuals with higher social status and opens up a wide variety of job openings. In many countries, language proficiency is not only a key subject but also serves as a primary medium of communication for better personal and professional growth.

Socioeconomic background has a strong impact on students’ language proficiency. Kerala, which is known for its high literacy rates and emphasis on education, presents a unique landscape for examining the factors influencing English language proficiency. The Ministry of Education has placed a strong focus on increasing the proficiency of English language among secondary school students through a well-structured curriculum that develops their speaking, reading, writing and listening skills, and their understanding of grammar to ensure the proficiency [3]. Recent reports from the education department reveal that English language proficiency among students in Trivandrum district remains unbalanced due to the significant differences associated with socioeconomic factors. Students living in cities and urban areas tend to be more proficient in English due to their access to resources and opportunities for language practice. Their daily communication often reflects their status, which positively influences their fluency, pronunciation, and grammar. On the other hand, students from rural backgrounds often struggle with a lack of basic resources and opportunities for effective communication. As a result, their grammar and language development may lag, affecting their overall proficiency.    

Family is considered as the foundational environment for learning, where parents, peers and family members serve as the initial advisors and teachers, providing the foundation for character building and language acquisition. Effective parental communication in English improves students, grammar, pronunciation and accent while providing a supportive and engaging learning environment [4]. Strong verbal, written and oral communication skills are essential for effective language development. In today’s age of digitization and e-learning, online resources, digital classrooms and electronic devices significantly enhance the learning of language. Social media platforms, internet-based learning management systems (LMS), and various online tools make teaching and learning more accessible and flexible, providing students with various opportunities to improve their language skills [5]. If the students and teachers are not aware of these opportunities, they won’t be able to handle the difficulties of modern, digital learning and language acquisition. In order to overcome this situation, the study examines the socioeconomic factors that influence the proficiency of the English language among secondary school students in Trivandrum. The study aims to establish the relationship between various socioeconomic factors such as parental communication, urban accommodation, influence of digital and online resources, students grade level, academic performance and their SES. The study examines these variables and determines how they affected the language ability of the student. 

Abdul Hannan (2024) [6] performed a study to observe the relationship among the socioeconomic background of University students and their language pronunciation skill in tertiary education. Using a quantitative survey method, the primary and secondary data were gathered from 120 students at two private universities in Khulna. The study focused on parental influence, socioeconomic backgrounds, educational environments and motivation for learning a language. Analysis such as regression, correlation and descriptive statistics presented a strong relationship between socioeconomic factors and language proficiency. Students coming from rich families exhibited strong pronunciations and greater motivation to learn a language. The study emphasized substantial changes in language proficiency between students from various socioeconomic backgrounds, offering valuable information into the intricate process of language learning within academic environments.      

D’Elia et al. (2023) [7] investigated the effect of socioeconomic-cultural status (ESCS) on the English language ability of students from five macro areas of Italy. The study observed the information from the INVALSI English test, which was given to 8^th grade students concentrating on reading and listening skills. The study applied regression models for both descriptive and inferential analyses. The findings from the study presented that the impact of ESCS on the English test varied depending upon the type of test and the region. It was also discovered that students’ performances were impacted by their gender and immigration status. However, a limitation noted was that the examination performed at the macro-regional level failed to capture the impact of ESCS on specific regions. 

Vadivel et al. (2023) [8] investigated the relationship among socioeconomic background and academic performance of students. The research applied a descriptive survey of 50 students and their parents, which was nominated through random sampling process. The collection of data implicated group discussions, interviews and observation methods. Findings indicated that students from low socioeconomic backgrounds, whose parents had shown less interest in their education, often experienced poor academic performance. This led many of them to enter the labor market at an earlier stage.  The study highlighted the limitation that lack of parental awareness and inadequate school facilities hindered children’s school enrollment and retention. 

Aashiq et al. (2023) [9] carried out a study to determine the effect of SES on the academic achievement of students studying in the schools of Mansehra district in Pakistan. The study utilized a descriptive survey method to investigate all elementary level public sectors and a two-stage random sampling technique was applied to choose the sample. The research examined SES utilizing a questionnaire and the academic performance of the students through a 40-question math and English test. The instruments’ reliability was confirmed by strong Cronbach’s alpha values, which were 0.85 and 0.83 respectively. According to the study, students from families with an average financial background performed better than from families with a below average financial background. In addition, the parents of the students who had higher education scored higher than those with less education. The study emphasized the significant influence of SES and parental education on academic performance.

Sunarni (2023) [10] studied the relationship between parents’ SES, gender and English proficiency of students among eleventh grade students at SMKN 1 Selo Boyolali in Indonesia. The study sampled 64 students from different departments using a quantitative correlative research method. English proficiency data were gathered through documentation, while questionnaires were utilized to collect data on student’s gender and their parents’ socioeconomic background. The analysis conducted using Pearson-Product moment correlation showed a substantial change in English proficiency among male and female students with gender showing a high level of correlation. Conversely, the correlation between parents’ SES and students’ English proficiency indicates that socioeconomic variables had a moderate impact on students’ academic outcomes.    

Rahmayani et al. (2022) [11] conducted a study in Indonesia to find out the relationship among students' SES and their English proficiency. The study focused on 8th-grade students at SMP Muhammadiyah 1 Makassar, utilizing a sample of 29 students from class A. Information was assembled through a questionnaire, and the Pearson Product Moment Correlation was employed to observe the information. Findings exposed an important positive correlation between students' SES and their proficiency in English, signifying that SES has a prominent impact on students' capability to study English.   

Udayakumar et al. (2022) [12] examined at how socioeconomic factors influence the academic achievement of higher secondary students in Salem District. After observing the information from a sample of 764 students, it was observed that the education and occupation level of mothers had a significant impact on the academic achievement of their children when related to the education and occupation of their fathers. The research also found that the academic success of the students at the higher secondary level was notably influenced by the group of schools they studied and the medium of teaching they used to learn. The findings established a clear correlation between the socioeconomic factors and academic achievement, emphasizing the impact of family background and educational environment in forming the academic success of the student.

In order to recognize the role of education in a country’s economic growth and efficiency, Katoch et al. (2022) [13] investigated the relationship among academic performance and socioeconomic factors of school children aged 6-14 years. The academic achievement of the children was observed employing the marks or grades they obtained from the annual examination passed. Findings of the research obtained those socioeconomic factors such as higher birth order, absence of parental education and occupation levels, lower caste status and absence of pre-schooling through Anganwadi centers were associated with low academic performance. Also, children’s living in Kachcha houses, which have slight space for living, low school attendance, and a limited number of teachers, were more likely to perform poorly in their studies. The result from the study underscores that those socioeconomic conditions had a significant impact on children’s educational outcomes, emphasizing the challenges faced by students from poor backgrounds.  

The relationship between quality education and socioeconomic development was examined by Siraj Bashir et al. (2022) [14] from the Balochistan province of Pakistan. The study aimed to identify the factors preventing the progress of socioeconomic regions focusing on human capital, education, employment and infrastructure with a sample space of 103 respondents from various parts of Balochistan. The information collected was examined using regression analysis, frequency analysis and correlation matrix. The results from the study demonstrated that there was a positive relationship among education and socioeconomic growth highlighting the importance of high-quality education for improving human capital, infrastructure and employment in Balochistan.

Katami (2022) [15] explored how parents’ socioeconomic background influences students’ academic attainment in Nigeria. The research performed a simple random sampling process to gather information from 350 students out of a total of 4,466. Questionnaires were offered to the participants and the information gathered was evaluated employing regression analysis. The findings showed that the socioeconomic class and education of parents were substantial predictors of students’ academic performance in Sokoto Metropolis. The study emphasized the importance of parental socioeconomic factors, highlighting their influence on students’ academic success.

Ullah and Almani (2022) [16] studied the factors affecting the performance of secondary school students in the Makran division of Balochistan. The data were collected through questionnaires from a total of 650 students, 200 teachers, and 24 head teachers. The participants were selected using purposive sampling. The study employed Pearson Correlation Coefficient to examine the relationship between various independent variables and students’ academic achievement. Results showed a positive relationship between both school related and student related factors and students’ academic achievements, providing valuable information about the elements that support the success of students in secondary schools in Makran division.  

Abid et al. (2021) [17] studied the relationship among the socioeconomic factors and academic achievement of students in higher secondary schools from the District of Mardan. The study utilized purposive sampling to choose 150 students from three schools in Mardan. The data were collected by means of a structured questionnaire that employed a five-point Likert scale and examined using descriptive and inferential statistics. Results indicate that students' academic performance was positively and significantly associated with several factors such as parental education, income level, and parental support. However, the parents' occupation and their involvement in decision-making do not appear to have a significant effect on students' academic performance. Overall, the study highlighted a strong positive correlation among parents' socioeconomic factors and the academic achievement of their children.

Idris and Rufus (2021) [18] explored the effect of parents’ SES on the academic achievement of their children in selected senior secondary schools in Taraba State, Nigeria. A sample of 325 respondents, comprising 125 parents, 100 students and 100 teachers, was selected using random sampling and questionnaires were administered to collect primary data. The collected data were analyzed using simple percentages and tabulation. The results showed that parents’ SES had a major impact on their students’ academic achievement in senior secondary schools.       

The research conducted by Manchanayaka et al. (2021) [19] explored the relationship between parental education levels and students’ English language proficiency at the ordinary level examination. Utilizing a non-experimental cross-sectional methodology, the study examined data from 291 respondents from six schools in the western province. The data was collected using a Likert scale questionnaire, which was pilot tested with 74 respondents. The information collected was then examined using regression analysis. The research demonstrated that the English language proficiency of the student significantly increased with the educational level of father and mother.   

Pant (2020) [20] utilized a qualitative case study approach to examine the relationship among students’ academic achievement and parental SES. Purposive sampling was used to identify 15 informants for the study including parents, teachers and students. Data collection methods included in depth interviews, group discussions, and observations with thematic narrative analysis. The findings presented those students from low socioeconomic backgrounds exhibited poor academic performance. Also, parents with less economic status showed low interest in their children’s education, which leads to a focus on employment rather than studies. As a result, these students were more likely to obtain unskilled jobs in the labor market, highlighting the significant impact of socioeconomic factors on educational achievements.      

Ø To examine the effect of socio-economic factors such as communication in English, parental communication and urban accommodation on English language proficiency.

Ø To study the influence of digital and online resources on English language proficiency.

Ø To compare students’ English language proficiency based on their grade level, academic performance and socioeconomic status.

Ø Hypothesis 1: There is a significant difference in English language proficiency among secondary school students in Trivandrum based on Gender.

Ø  Hypothesis 2: There is a significant difference in English language proficiency among secondary school students in Trivandrum based on school type.

Ø Hypothesis 3: There is a significant difference in English language proficiency among secondary school students in Trivandrum based on the number of years students have been learning English.

Ø Hypothesis 4: There is a significant difference in English language proficiency among secondary school students in Trivandrum based on academic performance.

Ø Hypothesis 5: There is a significant difference in English language proficiency among secondary school students in Trivandrum based their socioeconomic status.

Research Design

The study employs a quantitative research design to analyze the socioeconomic factors that impact the English language proficiency between secondary school students in Trivandrum. Employing a cross-sectional survey method, the study aims to collect and analyze information from various participants including students, head teachers and SST to analyze the influence of socioeconomic factors on English language proficiency. The research design enables a thorough examination of the relationship between independent variables and dependent variables using a statistical method to identify significant differences and correlations.

Population and Sample

The study consists of secondary school students, head teachers, and SST from eight schools in the Trivandrum district. The study included a total of 416 participants, with 32 head teachers, 64 SST and 320 students. A cluster random sampling approach is employed to confirm an illustrative sample from both urban and rural zones. This process collects information from various schools and demographic groups, making sure that the sample accurately shows the diversity within the target population.

Data Collection

The study performs data collection in a systematic manner through a structured questionnaire distributed to the students, head teachers and SST in the respective schools. The questionnaires are designed to collect data on demographic variables, SES, communication practices in English, use of digital and online resources and English language proficiency. It includes questions formatted with values given: Strongly disagree (SDA)=1, Disagree (DA)=2, Undecided (UD)=3, Agree (A)= 4 and Strongly agree (SA)= 5.

Variables Used

In this study, key variables have been identified to examine the influence of socioeconomic factors on English language proficiency among secondary school students in Trivandrum. The independent variable used in this study is socioeconomic status, which includes factors such as parental communication, accommodation in urban and big cities, reading English books, interaction with peers and playmates and having access to digital and online resources as shown in Figure 1. The dependent variable in the study is English language proficiency which includes the skills of students in writing, speaking and understanding English. All these factors are examined individually for their potential impact on English language proficiency.

Figure 1: Conceptual framework of the Study

Data Analysis

The data analysis is performed utilizing quantitative data measures such as descriptive statistics and inferential statistics. Descriptive statistics summarize the demographic features and distribution of responses. Inferential statistics including, t-tests and ANOVA are employed to identify significance in English language proficiency based on gender, school type, years of English language learning, academic performance and socioeconomic status. The SPSS Statistics 2022 software is utilized to perform percentage, frequencies, mean, standard deviations and significance.

Demographic Distribution

Demographic distribution describes the statistical analysis and visual depiction of different characteristics of a population. The study utilized the cluster random sampling method to gather data from respondents from 8 different schools in Trivandrum district. The representation consists of various factors such as location, gender, head teachers, SST and students, as shown in Table 1 and Figure 2.

Table 1. Demographic Distribution

The demographic distribution depicted in Table 1 shows that respondents from both urban and rural areas are evenly split, with 50.48% in rural and 49.52% in urban areas. Gender distribution also shows the same with 51.68% of male participants and 48.32% of female participants. Head teachers from the male schools of rural areas constitute 31.25%, while those from the urban male schools show 28.12%. Female head teachers are less with 18.75% in rural and 21.88% in urban settings. SST are distributed slightly with a higher concentration in male schools both rural (28.13%) and urban (26.56%) while in the rural regions the female SST make up 21.8% in rural and 23.44% in urban areas.  

          Figure 2: Demographic Distribution of Respondents

Descriptive Statistics

The respondents were asked to identify how much they agreed to select the statements about how socioeconomic statuses affect their ability to speak in English, which is depicted from Table 2 to Table 8 by using a scale of 1 to 5 were 1= SDA, 2= DA ,3= UD, 4= A and 5= SA. Also, other subsequent notations are F: Frequency shows how many people choose each response, (%): Percentage shows the distribution of responses relative to the total number of respondents, M: Mean and SD: Standard Deviation.

Table 2. Communicating in English improves language learning

Table 2 shows how communication in English impacts the English language proficiency. The study shows that about 1.6% of respondents strongly disagree with the statement. Based on the information collected, 64.1% of participants agree and 34.4% of participants strongly agree with the statement that communicating in English improves the learning of English. The mean score, indicated by 4.29, shows a positive perception among the respondents, while the standard deviation is 0.634, reflecting some variability in the responses.

  Table 3. Living in big cities facilitates better language learning

Table 3 demonstrates that living in big cities improves better learning in language. None of the participants strongly disagree with the statement, also respondents with 14.1% disagree and 8.7% are unsure about the statement. According to the data, 57.8% agree and 19.3% strongly agree that living in big cities enhances the learning of English. The mean score of 3.83 shows a positive view on the statement with a standard deviation of 0.882 reflecting some variation in the responses.

  Table 4. Urban Accommodation enhances language learning

Table 4 shows how living in an urban area increases the possibility of learning English. The data reveals that 1.5% of the participants strongly disagree with the statement, followed by 9.3% who disagree and 15.6% are unsure about the aspect. A majority of 62.5% of respondents agree to the statement that living in an urban area improves the quality of learning languages, while 10.9% strongly agree. The mean score of 3.71 indicates a strong perception and the standard deviation of 0.844 shows some variation in the responses. 

  Table 5. Communication of parents at home supports language learning

Table 5 shows how communication between parents at home facilitates language learning. According to the data, 1.5% of the respondents strongly disagree, 4.6% disagree and 1.5% are unsure about the statement. On the other hand, a significant majority of 31.3% agree and 60.9% strongly agree that parental communication is beneficial for learning language. They have a positive impact, as specified by the mean score of 4.45, while a standard deviation of 0.871 indicates variability in responses.

Table 6. Reading English books apart from the curriculum improves language learning

Table 6 demonstrates that reading English books out of the curriculum improves language learning. Based on the data gathered, 4.3% of participants disagree with the statement, 1.5% are unsure and none of the participants strongly disagree with it. A substantial majority of 46.8% agree and 47.1% strongly agree with the statement that additional English reading promotes language development. The mean score of 4.36 shows a positive view on the impact of extracurricular reading, with a standard deviation of 0.742 reflecting some variation in the responses. 

Table 7. Utilization of Digital and Online resources enhance language learning

Table 7 shows that utilization of online and digital platforms enhances language learning. According to the information, 3.1% of respondents disagree with the statement, while 6.2% are unsure. No respondents strongly disagree with it. A majority of 64.1%, agree and 26.5 strongly agree that using digital and online resources helps people in learning languages. The mean score of 4.14 indicates a strong positive perception of the impact of these resources, with a standard deviation of 0.660 showing some variation in responses.

Table 8. Interactions with playmates and peers enhances language learning

Table 8 illustrates that social interaction with playmates and peers improves language learning. According to the data, 4.6% of respondents disagree and 6.2% are unsure about this statement, but none of the respondents strongly disagree. A significant majority, 40.6% agree and 48.4% strongly agree that engaging with friends and peers positively influences language development. The mean score of 4.32 reflects a strong positive view on the impact of these interactions, with a standard deviation of 0.797 indicating some variability in responses. SES significantly affects English language learning, as evidenced by factors such as living environments, parental involvement, reading of English books, access to digital resources and social interactions.

Inferential Statistics

Inferential statistics play a crucial part in understanding the factors that influence the language proficiency among secondary school students in Trivandrum. The t-test examines the effects of gender and school type on English language proficiency, revealing substantial changes that underscore the effect of these variables. The ANOVA test examines how English learning, academic performance and SES affect language proficiency. Frequently notations used are N: Sample of students, M: Mean, SD: Standard Deviation, Std. Error Mean: SEM, SQ: Sum of Squares, MS: Mean Square, df: Degrees of Freedom, F: Ratio of Variance and Sig: Significance. 

Table 9. T-test based on Gender

The findings of the t-test based on gender, as depicted in Table 9, reveal a statistically significant difference in English language learning between males and females. Given that the t-value is 2.30 and a p-value of 0.021, which is below the significance level of 0.05. Therefore, the analysis indicates that gender has a substantial impact on the proficiency of the English language. The mean score for male students is 45.25, which is comparatively higher than the mean score of 44.88 for female students.

Table 10. T-test based on School Type

The t-test results based on school type, as demonstrated in Table 10, show a statistically significant difference in English language learning. The study indicates that the type of school has a significant impact on English language proficiency with a t-value of 2.45 and a p-value of 0.015, both of which are below the significance level 0.05. Private school students have a higher mean score of 44.50 compared to 43.88 for public school students.

Table 11. ANOVA Test on Students learning English

The ANOVA test results on the duration of students learning English from Table 11 reveal a statistically significant difference in English language proficiency across different groups based on the years of learning.  The proficiency of students in English is significantly affected by the number of years spent learning the language, with an F value of 2.75 and a significance of 0.045, which is below the threshold of 0.05. Students who have been learning English for more than 15 years have the highest mean score of 48.00, while those who have been learning English for 0-5 years have the lowest mean score of 42.50.

Table 12. ANOVA Test of Students’ Academic Performance

The ANOVA test results based on students’ academic performance, as depicted in Table 12, show a statistically significant difference in English language proficiency across different performance levels. The study indicates that academic performance has a substantial influence on English language learning, with an F value of 3.50 and a significance level of 0.034. The students with above-average academic performance show the highest mean score of 47.50, while those with below average performance have the lowest mean score of 40.00.

Table 13. ANOVA Test based on Students’ Socioeconomic status

The ANOVA test results based on students’ socio-economic status shown in Table 13, reveal a statistically significant difference in the English language proficiency among students from different socioeconomic backgrounds. SES had a substantial effect on learning English, with an F-value of 3.25 and a significance level of 0.048, both below the threshold value of 0.05. Students from high socioeconomic backgrounds have the highest mean score of 47.50, while those from low socioeconomic backgrounds have the lowest mean score of 43.  

The study aimed to examine how socioeconomic factors affect the English language proficiency among secondary schools’ students in Trivandrum. The results show clear differences in students English proficiency depending on a number of factors such as SES, living in a rural or urban area and other variables. SES significantly impacts English proficiency, with students from higher socioeconomic backgrounds showing strong proficiency. The findings of ANOVA (F=3.25, sig=0.048) indicate significant differences in proficiency levels. Students from high socioeconomic backgrounds score the highest mean of 47.50, while those from poor backgrounds score the lowest mean of 43.

Urban students exhibit higher English proficiency compared to rural students. The mean score for those who live in big cities is 3.83, while the score for those who reside in urban areas is 3.71. According to the findings, living in an urban area improves language acquisition for 57.8% of respondents, with 19.3% strongly agreeing. This improvement is attributed to the more frequent use of English in daily life and better access to resources. Parental communication in English significantly impacts language learning, with a high mean score of 4.45. A majority of respondents (60.9%) strongly agree that communication between parents at home facilitates language learning. Digital and online resources significantly enhance English proficiency with a mean score of 4.14. A majority of respondents, 64.1% who agree and 26.5% who strongly agree believe that these resources improve, language learning highlighting their role in making education more accessible and flexible.

Academic performance and duration of English learning are strongly correlated with language proficiency. ANOVA results show significant differences based on academic performance (F= 3.50, p= 0.034) and duration of learning English (F= 2.75, p = 0.045). Students learning English for more than 15 years and those with above average academic performance score higher with a mean of 48.00 and a mean of 47.50 respectively. The study also finds significant differences based on gender and school type. The male students have a higher mean score (45.25) compared to female students (44.88), indicating a gender-based difference in proficiency. However, students from private schools have a higher mean score (44.50) compared to those from public schools (43.88).    

The study examines the impact of socioeconomic factors on English language proficiency among secondary school students in Trivandrum. Students from higher socioeconomic backgrounds demonstrate better English proficiency compared to their peers from lower backgrounds, highlighting the significant role of resources and opportunities in shaping language learning outcomes. Also, students from urban zones expresses stronger language skills than those from rural zones. The study also identifies that active parental communication in English significantly influences children’s capability to study the language, highlighting the significance of a supportive home environment. The use of digital and online resources improves language proficiency, emphasizing the benefits of integrating technology into education. Language proficiency is positively correlated with academic performance and the amount of time spent in learning English. More years of learning English and academic performance are connected with higher language proficiency in students. These findings highlight the requirement for targeted interventions to support students from low socioeconomic backgrounds, such as improving resource availability, increasing family involvement, and increasing educational opportunities. The findings of the study specify that majority of participants agrees SES significantly effects English language learning.