Expoloring the impact of Socioeconomic Background on English Language Proficiency among school students in Kerala

English is the third most language spoken globally.  After Spanish and Mandarin and it becomes the official language for 67 countries. It is widely taught and essential in the modern globalized environment. It serves as a lingua franca that facilitates worldwide communication and promotes cultural exchange. Furthermore, it is the language for innovation, science and technology giving access to employment opportunities and modern research [1]. Proficiency in the English language encourages online participation, global citizenship and enables travel and tourism. Learning English is important because of the academic demands, specifically in modifying students’ conventions of the language and their practical knowledge. English Proficiency is considered to be important for learners to develop in life and the workplace since it gives them higher social status and job openings. English has a substantial role, particularly in regions like Kerala, where a lot of schools use it as their language of instruction. Kerala, known for its high literacy rates and emphasis on education, presents a unique landscape for examining the factors influencing English language proficiency [2].

The Ministry of Education in Kerala has positioned a strong emphasis on improving the English language proficiency among secondary school students through a well-organized syllabus to develop students’ skills in reading, speaking, listening and writing as well as their knowledge of grammar. Recent reports from the Kerala State Education Department reveal that English language proficiency among students in Kerala schools remains unbalanced due to the significant differences associated with socioeconomic factors [3]. The students coming from low-income families and those with limited parental involvement often struggle with the English language affecting the overall academics of the student. 

The socioeconomic characteristics of the students and their background in English language proficiency play a vital part in determining their academic achievements. The support and inspiration that a child receives from their home is an important factor.  Each family member acts as a perfect model for the child, influencing their learning and growth. It is through their support and care that the academic life of the child and its future outcomes are shaped. Children from families that energetically take part in their education and provide improved resources and moral support are more likely to win educationally. For example, a child is more likely to act better in school, especially in learning English, if their parents are energetically taking part in their education and making sure that they have access to the education materials and mental support.

There are many students who struggle academically in various subjects due to their insufficient talent in the English language. The English language occupies an essential and crucial role in education [4]. It is the only language that is used as a medium of teaching in the entire schools of the nation, right from the early education to tertiary education. Developing literacy and language is an ongoing process that takes place in the classroom throughout the day, both inside and outside.  It is important to identify that the development made by each child in learning these skills are different. 

The purpose of the research is to recognize how numerous factors of socioeconomic background affect the proficiency of English language among students in grades 10 and 12 in Kerala. The purpose of the study is to identify the relationship between the family background consisting of the location of the family, education level of the parents and siblings, economic status of the family and the language of communication used in the family. The study examined these variables and determined how they affected the English language proficiency of the student. A mixed method approach that integrates the qualitative and quantitative data is utilized.  It provides a thorough examination of how socioeconomic factors affect the student’s English language proficiency.

Firangi and Naami (2024) [5] conducted a thorough examination on the relationship between political, social and linguistic elements in a multilingual environment. The study comprised of 200 Iranian preschoolers aged from 5 to 6. These toddlers were determined employing a multi-stage stratified sampling method from four different language and cultural groups such as Arab, Kurd, Turk and Fars. The children took part in the basic English language sessions and their effect on television were carefully recorded. The proficiency of language was evaluated using Language Sample Analysis (LSA) considering factors such as words, new words and noises produced by the children. The study applied regression analysis, t-test and Analysis of Variance (ANOVA) for the examination. Findings from the research showed that bilingual children find better than multilingual children. The study underlined the significance of considering the socio-economic backgrounds in making decisions about education and promoted the integration of the mother tongue in the curriculum.

Using a descriptive survey design, Eniya and Woleru (2024) [6] investigated the impact of parent socio-economic position on the academic performances of students in government-owned schools in Abia State. The population of the study consists of 1,343 principals and teachers, with a sample size of 269 chosen through simple random sampling. A questionnaire with a 4-point Likert scale was used to gather the information and the reliability of the questionnaire was confirmed utilizing the Cronbach Alpha method. T- test was used to examine the hypothesis. The findings from the test showed that students’ punctuality was influenced by their parents’ income. Further analysis revealed no significant difference between the mean ratings provided by principals and teachers in this case. Similarly, level of parental education had a significant impact on students’ study habits. However, the mean ratings from the head teacher and teachers showed no significant change regarding this impact.

Using a convergent parallel design and a mixed method technique, Ntabwoba and Sikubwabo (2024) [7] explored how family background influences the proficiency of English language between scholars in 9- and 12-Years Basic Education (YBE) programs in Musanze district. 10 schools were nominated for the study, which consists of a population of 9,321 subjects from which a sample of 390 individuals was recognized. Data collection techniques included structured questionnaires, paper review guide and interview guide. Findings showed that the socio-economic factors of students had a considerable effect on the proficiency of the English language.

Anigbogu et al. (2023) [8] observed the effect of social and linguistic environments on the proficiency of the English language in secondary schools in Owerri, Nigeria. Utilizing a questionnaire to collect answers from English instructors, the research employed Pearson Product Moment correlation analysis and a normal P-P plot for regression residual standard to observe the information. The findings evidenced that social and linguistic factors substantially influence the English language proficiency. The results highlighted the importance of these factors, showing that they play a critical role in language achievement at the secondary school level.

Yousif et al. (2023) [9] conducted cross-sectional descriptive research to identify the factors influencing students’ academic performance. The study involved 208 participants aged 21 and 23 and emphasized the role of socioeconomic status (SES) and academic performance in shaping students’ educational paths. The findings underscored the need to understand the factors that influence academic success in order to enhance the quality of students’ academic experiences and their overall educational journey.  

Nguyen et al. (2023) [10] conducted a study to explore the role of self-directed learning in the English language development of students at Vietnam National University. The study involved 539 students and utilized a self-directed learning scale to assess their English language proficiency. Findings showed that most of the scholars attained a better level of English proficiency through self-directed learning. It also showed that improving English grades significantly influences the learning activities which are the essential elements of self-directed learning.  The study suggested that the SES of the family have a role in enhancing the student’s English language acquisition and self-directed learning.

In their study, Masood et al. (2022) [11] investigated the factors affecting the English language proficiency among the students at University of Pakistan. In order to determine the main contributors to language proficiency, the research utilized a mixed method approach. A survey conducted with four English language professors through a semi structured interview which provides valuable information to evaluate the factors that impact their proficiency. The findings of the study showed that SES, educational background, parental influence and media exposure were strong predictors of successful language proficiency outcomes. The study underscored the importance of English literacy as a main communication tool for Pakistani students, offering useful information to educators and decision makers to remove the barriers and create a supportive learning environment.

Islam and Moon (2022) [12] concentrated on the psycho-sociolinguistic factors of learning foreign language conducted at the University of Dhaka and the University of Science and Information Technology. The research studied the attitude of students towards foreign language learning and the factors behind it. It also clarified the issue of social influences in language acquisition. The results revealed that motivation was a crucial component for learning a second language. This study provided valuable information for social and motivational factors that influence students’ language acquisition. One of the drawbacks of the study was that the tool used to collect the data leads to misunderstandings or subjective interpretation.

Brown and Putwain (2022) [13] studied the influence of SES and gender on academic achievement through the lens of Expectancy-value theory. 396 students from the final year of upper secondary education were utilized. The results suggested that education of parents was directly linked to academic attainment.  However, SES and gender were indirectly connected to student grades, subjective task value (STV) and their communication. Educated parents of male scholars from wealthy backgrounds performed better in their exams. The study found that psychological factors partially explain the differences in academic achievement between gender and SES.

Chen et al. (2022) [14] examined the effect of learning English in early childhood on English and Chinese attainment among 892 children in mainland China. The samples were balanced according to the demographic, parent child interaction and SES factors utilizing coarsened exact matching (CEM) and propensity score matching (PSM). The study presented that learning English at a very young age positively influenced the later English and Chinese language achievement. The results determined that early exposure to English does not affect Chinese learning and emphasized the importance of predicting interest and motivation in English from an early age. However, the study was limited by using letter grades as an indirect indicator of English achievement and it examined only the effect of early childhood education on lower elementary grades.

Barrios and Lopez-Agudo (2021) [15] observed how SES affected the expectations of University students for using English in their future jobs and their views on the importance of English language proficiency as a specialized skill. The study involved 108 students from the University of Malaga. Regarding expectations and opinions of English proficiency, the analysis on ANOVA showed that there were no substantial changes among the SES groups such as: lower SES group, moderate SES group and High SES group. However, descriptive statistics showed that the students from low SES group showed lesser expectations on English language. These results suggested that students with low SES were likely to enroll in the English taught courses that could potentially affect their career in the field where English is a dominant language.

Masic and Becirovic (2021) [16] studied the impact of high school students in learning English as a foreign language (EFL). In order to collect the information, students from a Bosnian high school were sampled in four grades and the data were gathered using a questionnaire. The results of MANOVA indicated that students’ attitude was influenced by their age, gender, GPA in English and GPA. The results underscored the importance of understanding the learner’s attitude in order to assist curriculum developers and teachers to design activities that enhance the student’s level of English proficiency.

Ekanayake et al. (2021) [17] studied the impact of family background on English speaking skills of students in grade six in Kandy district. The purpose of the research was to identify the connection between parents’ educational level and SES with students’ ability to speak English. Data were collected from students, parents and teachers through observations, questionnaires and group discussions. Based on the educational background and SES of parents, there was a significant difference in the student’s English-speaking skills. Students from higher socioeconomic and educational backgrounds performed better in English, while those students with the least socioeconomic and educational backgrounds showed less support and confidence in their English communication. The study highlighted the importance of parental background in the language proficiency of children. In their study, Rashid and Rahman (2020) [18] focused on six schools in the Chittagong district to evaluate the sociocultural impact on learning EFL curriculum in Bangladesh. Data were gathered from 120 randomly selected students in both rural and urban government primary schools through class observations and structured questionnaires. A mixed method approach was used for analysis. The study found that socio-cultural environments had a substantial impact on learning English language, even though the curriculum, textbooks and instruction medium were uniform. The research identified socio-cultural challenges related to teaching and learning English, and provided valuable information for policymakers and EFL stakeholders, including students, parents and teachers. Socio-cultural influences have an impact on both qualitative and quantitative analysis. The study also supported the hypothesis about these impacts on primary level learning.

In their study, Attig and Weinert (2020) [19] examined the significance of SES by examining the influence of home learning environment (HLE) on the language skill development of two-year-old children. The research collected the data from 2,272 families in the German National Educational Panel Study (NEPS). The study examined structural factors like maternal education and household income in addition to factors like mother responsiveness, simulation behaviour and joint picture reading. The language proficiency was evaluated by using a standardized parent report instrument including vocabulary and grammar. Findings of the study revealed that all three HLE processes were associated with SES and almost all the qualities predict children’s language skills across assessment weaves. The study highlighted the influence of SES and HLE on early language development and also recognized the difficulty of conducting standardized tests with young infants.

Ø To study the impact of educational backgrounds of siblings ‘and parents on the English language proficiency among students in 10^th and 12^th grade schools in Kerala.

Ø To evaluate the impact of location of family on students’ English language proficiency in 10^th and 12^th grade schools in Kerala.

Ø To study the influence of economic status of family on students’ English language proficiency in 10^th and 12^th grade schools in Kerala.

Ø To examine how the language used for communication within the family affects English language proficiency among students in 10^th and 12^th grade schools in Kerala.

Ø H1: There is a substantial relationship between parents’ educational background and the proficiency of English language in students in 10^th and 12^th grade schools in Kerala.

H0: There is no substantial relationship between parents’ educational background and the proficiency of English language in students in 10^th and 12^th grade schools in Kerala.

Ø H2: There is a substantial relationship between the family location and the proficiency of English language in students in 10^th and 12^th grade schools in Kerala.

H0: There is no substantial relationship between the family location and the proficiency of English language in students in 10^th and 12^th grade schools in Kerala.

Ø H3: There is a substantial relationship between the family economic status and the proficiency of English language in students in 10^th and 12^th grade schools in Kerala.

H0: There is no substantial relationship between the family economic status and the proficiency of English language in students in 10^th and 12^th grade schools in Kerala.

Ø H4: There is a substantial relationship between the communication in family and the proficiency of English language in students in 10^th and 12^th grade schools in Kerala.

H0: There is no substantial relationship between the communication in family and the proficiency of English language in students in 10^th and 12^th grade schools in Kerala.

Research Design

A mixed method technique is used with a convergent parallel design to study the impact of family background on proficiency of the English language among students in 10^th and 12^th grade schools in Kerala. This approach allows to collect information at a single point in time to examine the connection among interested variables. It integrates the benefits of both quantitative and qualitative methods. The quantitative research highlights the collection of data and study of these data allowing variable analysis. While qualitative research focuses on the descriptive data, provides specific and detailed understanding of the phenomenon.  By integrating these approaches, the study offers a better understanding of how family background factors such as educational level of siblings and parents, economic status, family location, and language of communication in the family impact students’ proficiency in the English language.       

Population and Sample

The sample size for the study is obtained from 8 schools in Kerala with 10^th and 12^th grade students. The purpose is to develop effective methods, programs and guidelines that address the requirement of individuals considering the vital role of parents in encouraging the learning of the English language. The study population comprises 9,320 individuals, where a sample size of 384 respondents is selected, including 100 parents, 225 students, and 59 teachers. Random sampling is used to select students and purposive sampling is used to select parents and teachers. Yamane’s formula is used to compute a suitable sample size for the given population as given as:

                   (1)              

Where n stands sample size, N for population and e for sampling error, which is equal to 0.05.

Data Collection

The research utilized an interview guide and structured questionnaire to gather quantitative data on students’ English language proficiency and numerous socioeconomic factors. The questionnaire includes only closed-ended questions, formatted using a 5-point Likert scale with values allocated are given: strongly agree (SA) =1, Agree (A) =2, Neutral (N) =3, Disagree (DA) =4 and Strongly disagree (SDA) =5. In order to obtain secondary data, the study utilizes a documentary review.  

Variables

In this study, key variables are identified to examine the effect of socioeconomic background on Proficiency of the English Language among school students in Kerala as shown in Figure 1. English language proficiency is the dependent variable used, which includes the skills of students in writing, speaking and reading English. The independent variables include parent’s educational background (level of education attained by the students’ parent’s) family location (whether it is urban or rural), family economic status (income and occupation) and the family language of communication (primary language spoken within the family). All these factors are examined individually for their potential impact on English language proficiency.  

Figure 1: Conceptual Framework of the Study 

Pilot Study

The validity and reliability of the data collected are determined through a pilot study. Validity is verified through expert judgment techniques, while reliability is examined using both pilot study and the Cronbach alpha reliability coefficient. In this study, the questionnaire is given to 25 learners and obtained their responses.

Table 1. Reliability findings

The reliability results for the factors evaluated in the study are shown in Table 1. The Cronbach alpha values for each variable are as follows: Educational level of parents and siblings (0.921), economic status of family (0.897), language of communication in family (0.802) and family location (0.895). These values suggest that the measurement instruments used were sufficiently reliable. With an overall Cronbach’s Alpha value of 0.876, all variables exhibit satisfactory reliability. The findings suggest that the instruments used to measure these variables are consistent and reliable, ensuring that the data collected is dependable for the analysis. 

Data Analysis

This study examines quantitative and qualitative data. The qualitative data analysis involves questionnaires and classifying data to recognize patterns and themes. In contrast, analysis of quantitative data employs statistical methods such as regression analysis, descriptive statistics, and inferential statistics to examine numerical data and verify the hypothesis. The IBM SPSS Statistics 2022 software program is utilized to perform percentage, mean (M), frequencies, regression analysis and standard deviation (STD).  

Demographic Distribution

Demographic distribution refers to the statistical analysis and visual representation of different characteristics of a population. The study utilizes random sampling and purposive sampling to collect data from respondents across different schools in Kerala.  The representation considers multiple factors, including gender, age, educational level and professional experience, as shown in Figure 2 and Table 2.

Table 2: Demographic Distribution

The demographic distribution presented in Table 2 provides a comprehensive overview of the participants' characteristics across key variables: gender, age, education, and professional experience. The gender distribution shows a higher representation of females, with 229 participants compared to 155 males, which may be significant when analyzing potential differences in English proficiency between genders. In terms of age, the respondents are categorized into four groups: 60 individuals are under 15 years old, 40 are between 15 and 20 years, 84 are between 20 and 25 years, and a majority of 200 participants are above 25 years. The age distribution indicates a wide range of life stages, which may have an impact on English proficiency based on the educational and professional experiences associated with each group. The educational background of the participants is varied, with 55 individuals having no formal education, 45 having completed primary education up to grade six, 80 in Senior Three, 90 in Senior Six, 43 holding an Advanced A1 diploma, 36 with an Education A0, 10 with a Postgraduate Diploma, and 25 holding a Master’s degree or higher. This distribution reflects various educational attainment levels, which are crucial for understanding their impact on English proficiency. Regarding professional experience of teachers, the total sample size is 59. The sample is categorized into four groups: 14 participants have less than one year of experience, 15 have three years, 13 have five years, and 17 have professional experience for more than 5 years. This difference in professional experience is possible to effect English proficiency, as participants with more work experience may have had more chances to use and progress their English language skills in professional settings. Overall, these factors highlight the impact of socioeconomic conditions on English language development.

Figure 2: Demographic Distribution of Respondents

1.1 Descriptive Statistics

Respondents are asked to indicate how much they agree with the statements about their impact of their family’s language on their English-speaking skills, using a 5-point Likert scale.

Descriptive Statistics of Language used for Communication in Families

Table 3. Descriptive statistics of language used for communication in Families

The descriptive statistics presented in Table 3 illustrate the impact of different family languages on the English language proficiency of school students. The mean score indicates that the Malayalam language has a significant impact on English proficiency, with a mean of 4.5021 and STD of 0.8621 suggesting strong agreements among respondents. Similarly, languages like Tulu and Kodava exhibit high influences with a mean of 4.0523 and 4.4632 respectively and comparatively low STDs indicate consistent responses. English spoken at home shows a notable impact with a mean of 4.3123 and STD of 0.9125 indicating moderate agreement and some variability in responses. Also, Tamil, Hindi and Kannada languages show significant influence with a mean of 4.4234, 4.3012, and 4.4125, respectively. However, Kannada has a high standard deviation of 1.0078 indicating more different responses. The sign language used by families has a significant impact on English language proficiency with a mean of 4.3521 and STD of 0.7421 indicating a strong agreement and less variability among respondents. The overall mean score of 4.4086 with a STD of 0.8792 indicates the respondents agree to the statement that the languages spoken at home influence students’ proficiency of the English language in 10^th and 12^th grade schools in Kerala.

Descriptive Statistics of English Language Proficiency   

Table 4. Descriptive statistics for language proficiency in English

The data obtained from Table 4 reveals that respondents’ levels of English language proficiency vary. The average score for reading and writing English texts is 3.05, which indicates a moderate level of proficiency. The STD is 0.75, which is relatively low indicating consistent responses among participants. Communicating verbally in English with proper vocabulary and grammar shows a lower mean of 2.92, which indicates some difficulties in verbal communication with a STD of 0.79 indicating variability in experiences. The capacity to convey opinions and thoughts evidently in written English has a mean of 2.94 with a STD of 0.84 highlighting areas for improvement in written expression. There is a considerable range of vocabulary which includes both common and technical terms averages at 3.01, with a low STD of 0.61, show a moderate range of vocabulary with less variability. The efficiency in understanding and implementing English grammar principles shows a better mean score of 4.00 with a STD of 0.69. Pronunciation of English words and sounds has a mean of 3.70 and a STD of 0.72 reflecting a good level of pronunciation ability. Similarly, with idioms and expressions scores a mean of 3.55, with a STD of 0.81 indicates a moderate understanding of common expressions. Finally, the ability in organizing ideas and thoughts coherently in both writing and speech has a mean of 3.76 and STD of 0.90. The overall mean proficiency is 3.36 with a STD of 0.76, determines that the respondents tend to not agree with the statement associated to proficiency in English language in 10^th and 12^th grade schools in Kerala.

Inferential Statistics

Inferential statistics uses sample data to make generalizations about a large population, help researchers to estimate population parameters, test hypotheses and determine relationships between variables. In this study, it analyzes data from students, parents and teachers to draw broader conclusions. Methods such as regression analysis and hypothesis testing reveal significant relationships and provide valuable information on how socioeconomic factors influence English language proficiency.   

Table 5. Model Summary: Impact of Family Language and Proficiency in English Language

Table 5 shows a substantial correlation between English language proficiency and family language. The linear connection among the independent and dependent variable, are signified by the R² value. The R² value is 0.961, that is 96.1% of the change in the proficiency of English language can be described by the family language. This model fits the data as well as demonstrated by the adjusted R² value of 0.961.  The estimated std. error is 0.164, which measures the typical distance that the values observed fall from the regression line. A low std. error shows a better fit of the model. Therefore, the std. error is comparatively small, suggesting that the English proficiency scores predicted are near to the actual scores.

Table 6. Analysis of Variance: Impact of Family Language and Proficiency in English Language

The “mean” of three or more groups can be compared using the ANOVA statistical approach to check if there is any substantial difference between them. It helps to differentiate whether changes occurred in the data are due to random chance or actual differences between the groups.  ANOVAs’ findings from Table 6 show that the regression model has a sum of squares of 64.875, with a mean square of 64.875 and an F-value of 2450.123, which is statistically important with a p-value of 0.000. This indicates that family language and English proficiency are strongly correlated.  Therefore, it has been determined that family language has a substantial influence on the students’ English language proficiency in Kerala schools by accepting the alternate hypothesis and rejecting the null hypothesis. 

Table 7. Regression Coefficients: Family Language of Communication and Proficiency in English Language

Table 7 shows that the language of communication used in families has a significant impact on proficiency in English, with a standardized beta coefficient of 0.982. The language of communication for the family and the English proficiency of students are positively correlated, as indicated by the high positive beta value. Specifically, for each one unit increase in the language of communication used by the family, the proficiency in the English language is expected to increase the value by 1.532 units, thereby keeping other independent variables constant. The findings underscored the importance of family language in shaping students’ English language skills and suggest that creating a positive family language environment can greatly improve students’ proficiency in English language.     

Ordinary Least Square Regression: Impact of Family Background on Learner’s English Language proficiency

Ordinary least squares (OLS) regression is a statistical technique that evaluate the relationship between one or more independent variables and a dependent variable, by reducing the total of the squared differences between predicted and observed values. It determines the variations in the independent variables and changes in the dependent variable. The study shows that the results of an OLS regression analysis show the influence of how the 4 independent variables together affect the students’ English language proficiency in 10^th and 12^th grade schools in Kerala.

Table 8. Model Summary: R² for Family Background

The summary of the model from Table 8 specifies a strong connection between the four independent variables and the English language proficiency, with an R value of 0.987 and an R² value of 0.974. This high R² value indicates an excellent fit with the model covering nearly 97.4% of the variance in the English language proficiency. The R² value adjusted to 0.973 confirms the model’s accuracy after considering the number of predictors and the std. error of the estimate at 0.12645, shows the smallest variation between the expected and the actual scores. The study tests the hypothesis that the predicted variables positively influence the dependent variable, showing their significant impact on students’ English language proficiency.  

Table 9. ANOVA: Family Background

The effect of family background on English language proficiency is examined using an ANOVA as shown in Table 9. It shows that factors related to the family background have a substantial effect on the dependent variable. The regression model explains a significant portion of the variance with a sum of squares of 64.795 and a mean square of 16.244, which results in a high F value of 1055.123. This significant F value, with a p value of 0.000 determines that the model substantially enhances the prediction of English language proficiency when compared to a model with no predictors.  The residual sum of squares is 1.276 with a mean square of 0.003, showing limited variance.

Table 10. Regression coefficients: Impact of Family Background

The findings presented in Table 10 determine that a number of family background factors have a substantial effect on students’ proficiency in the English language in schools in Kerala, pursuing 10^th and 12^th grade. The educational level of parents and siblings has a significant impact, with a standard beta coefficient, which are the coefficients of the variables after standardization, given as 0.970. This means that while other factors remain constant, the B value which indicates the variation in the independent variable for a one-unit variation in the independent variable boosts the English proficiency by 1.185 units. The variable family location, with a beta coefficient of 0.983 leads to an increase of 1.397 units in English proficiency for each unit change. The family’s economic situation has a substantial influence on proficiency, as indicated by a beta coefficient of 0.981, which results in an increase of 1.210 units for each unit change. Additionally, the language used within the family also has a strong positive effect, with a beta value of 0.984, leading to an increase of 1.547 units in English language proficiency for each unit change. These findings underscore the crucial role that family background plays in shaping students’ English language proficiency. According to the results shown in Table 10, the regression model can be expressed as follows:

L=1.532+ 1.185M₁+1.397M₂+ 1.210M₃+1.547M₄      (2)

where L represents the changes in English language proficiency, M₁ denotes education, M₂ refers to family location, M₃ indicates family economic status and M₄ pertains to family language communication.

The study explored the impact of socioeconomic background over proficiency in English language between students in 10^th and 12^th grade schools in Kerala. The research addressed 4 primary objectives and tested the corresponding hypothesis to examine the impact of the independent variables over the dependent variables. The study found a strong correlation between the English language proficiency of students and their parents and siblings educational backgrounds. The regression analysis showed a standardized beta coefficient of 0.970, with a Cronbach’s alpha value of 0.921. This shows that a one-unit rise in this factor boosts English proficiency by 1.185 units. The findings support the hypothesis that the higher educational level of both parents and students positively influences students’ English language skills.

The analysis revealed that the location of the family plays a significant role in students’ English proficiency, with a Cronbach alpha of 0.895 indicating high reliability. The analysis showed a beta coefficient of 0.985, indicating that students from urban areas tend to have higher English proficiency. Specifically, for a one-unit increase in the urbanization of family location, there is an increase of 1.397 units in English proficiency. This supports the hypothesis that students in urban areas generally excel more in English, probably due to greater access to opportunities and educational resources. The economic status of a family was found to significantly affect students’ proficiency in English. This was confirmed by a Cronbach alpha of 0.897, indicating strong reliability of the results. The analysis revealed a coefficient of 0.981. This indicates that for every one-point increase in family economic status, English language proficiency improves by approximately 1.210 points. This finding supports the idea that higher family income and better job status provide students with more educational resources, which in turn enhances their English language skills.

The language used for communication within the family is identified as a significant predictor of English language proficiency. Regression analysis reveals the beta coefficient of 0.984 and the Cronbach alpha value of 0.802 indicates accurate measurement. This shows that a one-unit rise in the use of English or a similar language at home increases students' English proficiency by 1.547 units. Descriptive statistics supporting the languages Malayalam, Tulu, and Kodava showing high mean scores show their strong influence on English proficiency.  This confirms the hypothesis that, primary language speaks at home significantly influences students’ English language skills. The overall Cronbach alpha value of the study, 0.876 across all variables, demonstrates high reliability. The descriptive and inferential statistics provide strong evidence that the socioeconomic factors identified significantly impact the student’s English language proficiency. The R² values of the regression models determine that these factors explain a substantial proportion of the variance in English proficiency among students.

The study examined the relationship between various socio-economic factors that impacts the English language proficiency among 10 and 12 YBE students in Kerala schools. A mixed method approach is employed in the study that integrates both the quantitative and qualitative data. It examined the impact of parents and siblings’ educational levels, economic status, language spoken at home and family location. The results indicate that these socio-economic factors have a significant impact on students’ English proficiency. Specifically, students from families with a stronger educational background, those living in urban areas, those with higher economic status, and those families using English or related languages show higher levels of English proficiency. This highlights how socioeconomic background shapes the language skills of students and the specific educational interventions and support required for improving the English language learning in a variety of socioeconomic circumstances.