The impact of vocabulary selection ability on EFL students’ communication skills

ABSTRACT

Through vocabulary selection ability, students are able to express feelings, ideas, or information in various ways without changing the meaning. For example, students may say "fresher" instead of "new graduation" in a job interview context. In addition, in phoneme selection, the sound of "fresher" and "fresh air" refers to different things. Therefore, vocabulary awareness is the basis of all language use. It is like the raw building blocks to build a mix of thoughts and ideas, information, and personal relationships. In the worst situation of learning English, understanding is still possible with little knowledge of grammar. In addition, Agustiawati (2022) also claims that vocabulary is essential in foreign language learning as the meanings of new words are very often emphasized, whether in books or classrooms. To put it simply, the more vocabulary to know, the easier students can improve their language skills. However, communication skills are more complex because they involve the students' soft skills to manage a well-flowing conversation (Wardana et al., 2022). As a result, it will help them to understand words from their context, naturally expanding their vocabulary and improving their language skill without needing to spend more time looking the words up in a dictionary or asking someone for an explanation.
There have been many studies investigating the vocabulary and language skills of EFL students (Soliman, 2014;Alshumaimeri & Alhumud, 2021;Miralpeix & Muñoz, 2018). However, the present study explores whether the tenth-grade students of a private vocational high school in Badung, Bali have great performance in vocabulary selection and whether their ability is statistically correlated with communication skills. This study investigates how English communication skills might be dependent on the student's ability to recognize and use the correct words. A study of He and Godfroid (2019) introduces a stepby-step approach for materials writers, curriculum designers, and teaching professionals to identify word groupings in a potential list of target words, using a combination of objective and subjective data, with the prospect of creating more effective and more efficacious vocabulary learning materials. In addition, another study of Yorkston et al. (1989) reveals that standard vocabulary lists may be considered a necessary but not sufficient aspect of vocabulary selection. Therefore, this study addresses the significant impact of English vocabulary selection ability on communication skills. From having correct selection of vocabulary, students are The impact of vocabulary selection ability on EFL students' communication skills

Communication skill
Communication is a process conducted among humans as they interact with one another, which is an important aspect of them. In relation to this, human communication is a connector for society in the process of relaying information or news and broadcasting important announcements. According to Dale et al. (2013), human communication is a subtle set of processes through which people interact, control one another and gain understanding. Communication in society is basically needed in face-to-face interaction or direct conversation which requires both speaking skill and listening skills.
Communication skills are the abilities you use when giving and receiving different kinds of information. Some examples include communicating new ideas, feelings, or even an update on your project. According to Crichton (2009), students need to actively use the language to give them confidence and to feel its communicative value. As a university student who is getting ready to start their chosen career, he or she should take the opportunity in any activities that develop communication skills in a wider and complete aspect so that communication skills can be fully developed. Iksan et al. (2012) claim that in our globalized world, university students need to master communication skills in different cultural contexts. Communication skills involve listening, speaking, observing, and empathizing. It is also helpful to understand the differences in how to communicate through face-to-face interactions, phone conversations, and digital communications like email and social media. Communication skill also means having the ability to convey information and ideas effectively.
Moreover, Trosborg (1987) states that people frequently fail to communicate effectively because they do not express themselves clearly enough. Indeed, in every conversation, each party needs to express what they talk or discuss about. Mastering communication skills will help them a lot in doing an effective conversation. The effectiveness of communication will be achieved when the person that is involved in communication understands each other. That being said, communication skills are necessary for students to master.

Listening skill
Listening can be considered the fundamental skill to speaking because without understanding the input at the right level, any learning cannot begin. Along with speaking skill, listening skill also allows people to communicate effectively (Tilwani et al., 2022). Listening is not a passive skill but an active process of constructing meaning from a stream of sounds. Having good listening comprehension makes people able to decipher and interpret the meaning of a certain context while doing communication. Based on , listening receives little attention in language teaching and learning, because teaching methods emphasize productive skills, and listening was characterized as a passive activity. In the teaching and learning process, the view of listening has changed the role of the listener from someone who was thought to passively receive the spoken message to an active participant in the act.
People are able to hear what the other person says by only focusing their hearing toward the person which is called "hearing", while listening to it, not only about hearing yet people need to understand the context well. Brownell (2002) states that listening is the process of receiving, constructing meaning from, and responding to spoken and/or non-verbal condition of a phenomenon with a correlation research design to compare two or more variables in a single group.
The population of the study was 80 tenth-grade students at vocational high school students in Badung, Bali, Indonesia. However, 40 students were selected as samples of the study. Some steps in selecting the samples included (1) preparing four pieces of paper and writing the name of the class, (2) folding and putting them into a glass, (3) showing the glass, (4) determining the sample of this research from the selected papers, and (5) conducting the research.
In the present study, the researcher used a note-taking test that was focused on student vocabulary selection ability and listening skills. In this case, the researcher prepared a voice recording that contained several vocabularies. There was a voice recording of the researcher which stated 10 vocabularies included five groups of words belong to core vocabulary, relates to the most commonly used words and consists mostly of verbs, pronouns, descriptors, prepositions and few nouns and five group of words belong to Fringe vocabulary, refers to topic-, environment-, or person-specific vocabulary that is unlikely to be used across environments. The students needed to listen to the words in the vocabulary carefully and then write down what vocabulary was heard by them in the form of note-taking. To take the vocabulary selection ability test result, the researcher provided a platform which was a WhatsApp group. The researcher provided 10 minutes for the students to do their work. Then, the students took a photo of their work and sent it via WhatsApp group.
Besides, in the present study, the researcher used oral proficiency scoring categories which are adapted from Brown (2014) consisting of three adapted aspects, i.e., fluency, comprehension, and grammar. However, Brown's oral proficiency criteria score consists of six aspects: vocabulary, pronunciation, fluency, comprehension, grammar, and task. The scoring rubric was adapted in the present study only on the three aspects based on the student's level and condition in the teaching and learning process.
In the present study, the data was collected by administering several topics as a theme for the students' role play as the research instrument. The test was constructed by giving a topic that students need to discuss with their partner to make a dialogue by inserting some vocabulary that was determined before. Then, after the research instrument was constructed, the test had to be considered valid and reliable. The test was constructed based on the crucial terms of validity and reliability. The 40 students were divided into 15 groups which each consisted of 2 students. They were given 20 minutes to construct their dialogue with their partners. They were required to construct a simple conversation by using the determined vocabulary as a theme of their conversation. Finally, students performed their conversation in front of the class and then were scored through a scoring rubric.
In addition, data analysis is the process of modeling the data to obtain specific information that can be applied in formulating the conclusion, prediction results, and scientific and social knowledge. In this present study, the researcher used authentic listening tasks in the form of notes and role-play tests to measure students' English vocabulary selection ability and communication skills.
The normality test aimed to determine whether the sample was from the population and had a normal distribution or not. In the present study, the normality test with Liliefor's Significance Correction by Kolmogorov Smirnov in (KS-Z) of SPSS 25.0 was analyzed. In  Table 1 shows the result of the normality test, while the program showed that the normality test for English vocabulary proficiency was 0.010 and for communication ability was 0.076. This means that the data were normal, while English vocabulary proficiency was 0.010 > 0.05 and communication ability was 0.076 > 0.05.
The homogeneity test is performed to test two or more sample data sets derived from the sample population variant. Homogeneity tests are performed to determine whether the data has homogeneous variance or not. In this homogeneity test, the minimum standard of 0.05 is the same as in the normality test. The result of the homogeneity test can be [represented in Table 2. From the calculation in Table 2, the significance of the student's English vocabulary proficiency and communication skills is 0.011 > 0.05, which means that the variances were homogeneous and not different. The hypothesis tests were calculated using the SPSS 25.0 version for Windows. In addition, the hypothesis test consisted of a Pearson product-moment t-test. In summary, these two analyzes were essential. The hypothesis can be formulated as follows.
1. Alternative hypothesis (Ha): There is a positive and significant correlation between proficiency in English vocabulary and the communication of the tenth-grade vocational high school students in Badung, Bali. 2. Null hypothesis (H0): There is a negative correlation between the mastery of English vocabulary and the communication skills of the tenth-grade vocational high school students in Badung, Bali.
The first analysis of the hypothesis tests performed in the present study was done by applying Pearson's product moment. In the present study, the Pearson's product-moment was used to measure the linear relationship. The method was used to find the correlation I. K. Wardana The impact of vocabulary selection ability on EFL students' communication skills between the study variables, students' proficiency in English vocabulary, and their communication skills. The significance of the correlation coefficient was determined by comparing the data when the significance value is less than 0.05. Data are classified as significantly correlated if the correlation coefficient is less than 0.05. On the other hand, the data can be classified as not significantly correlated if the coefficient correlation is greater than 0.05. In summary, Pearson's product-moment correlation coefficient was a simple way to assess the correlation between two variables. The product-moment correlation index can be seen in Table 3. The t-test is performed after the data are normally and homogeneously distributed. The t-test was used to test the hypothesis. The t-test assumes that both groups were normally distributed and had relatively equal variances. Also, the t-statistic is distributed on a curve based on the number of degrees of freedom. An alternative hypothesis is accepted if the significance value is greater than the significance level (0.05). Conversely, if the significance value is less than the significance level (0.05), the hypothesis is rejected. Additionally, in the present study, the investigator used SPSS 25.0 in a computer program to compare the means of two variables to determine if there was statistical evidence that the associated population had significant differences.

Findings and discussion
Students' proficiency in English vocabulary was an independent variable, referred to as variable X, and student's ability to communicate was a dependent variable, referred to as variable Y. To determine the correlation between these two variables, the researcher conducted a vocabulary test in which an audio recording contained 10 vocabulary words that students had to hear and write down. In addition, the researcher conducted a communication skills test, which was a role play that required students to incorporate the vocabulary they had previously heard into their conversation. A descriptive analysis of students' English vocabulary selection ability and communication skills is presented in Table 4. The impact of vocabulary selection ability on EFL students' communication skills Table 4 demonstrates the result of the English vocabulary proficiency test and the result of communication ability showed that the mean for communication ability is 70.80. The standard deviation is a numeric index that expresses the average variability of the score, or in other words, it is the distance from the mean. From the table above, the standard deviation for students' proficiency in English vocabulary is 13.679, while for students' ability to communicate is 12.237. The smallest value of the variable is called the passing score, while the passing score for the student's proficiency in English vocabulary is 50 and the passing score for the student's communication ability is 47. On the other hand, the largest value of the score is called the maximum score. The maximum score for proficiency in English vocabulary is 90 and the maximum score for communication ability is 93. Both mean scores of the word selection ability and communication skills were compared by the Pearson's product-moment test presented in Table 5.  Table 5, the correlation value of the coefficient (r) was 0.589, meaning that there was a positive correlation between word selection ability and the ability to communicate. Furthermore, based on Table 3, the correlation between them was moderate correlation while the (r) value was between 0.40 and 0.60. The value of (r) product moment for 40 samples with 5% degrees is 0.312. In addition, the r-count was greater than the r-table, which was 0.589 > 0.312. It means that the correlation between word selection ability and the ability to communicate is significant.

Informed in
Further, the t-test was the final analysis of the hypothesis test as the last step in the correlative research design. In calculating the t-test, the researcher also used SPSS 25.0 to calculate the correlation r-product moment when testing the study hypothesis. The result of the calculation of the correlation r product moment is presented in Table 6. The impact of vocabulary selection ability on EFL students' communication skills Table 6 reveals the result of the t-test, whereas the t-counted was -0.294. Furthermore, the df was 39 and the t-table of df 39 at α = 0.05 (5%) was 2.023. The t-counted was bigger than the t-table (-2.294 > 2.023). It means that the correlation between students' English vocabulary selection ability and students' communication skills was significant and the hypothesis was accepted. To sum up, the correlation coefficient (r-counted) of 0.589 could be used to represent the whole population of 40 samples.
The aim of this study was to examine whether or not there was a significant impact of students' vocabulary selection ability observed from listening towards their communication skills. To find the causal-impact correlation, the researcher constructed several steps to collect the data. As a first step, the researcher administered the English vocabulary selection ability test and then proceeded to the communication ability test. This test aimed to determine the correlation between students' proficiency in English vocabulary and students' ability to communicate.
In addition, based on the data analysis performed with the SPSS 25.0 program, calculations are made at the 0.05 level. The normality score for proficiency in English vocabulary was 0.10 and the normality test for communication skills was 0.76. Both data were normal as values were greater than 0.05 (>0.05). The next is the calculation of the homogeneity test. The significance of students' English vocabulary and communication skills was 0.11 > 0.05. It showed whether the variances were homogeneous and not different, or in short, had the same variant. Based on the results of these analyses, the researcher also performed hypothesis testing using Pearson's product moment. From the data on students' knowledge of English vocabulary and communication skills, it was found that r = 0.589. There was a positive and moderate association between students' proficiency in English vocabulary and their ability to communicate. In summary, there was a positive correlation between variable X (knowledge of English vocabulary) and variable Y (communicative ability).
After performing the Pearson's product moment test, the researcher used the pairedsample t-test to test the hypothesis. The result of the above calculation data shows that the alternative hypothesis (Ha) was accepted since the Pearson test shows correlation R = 0.589. This means that there was a moderate correlation. The result of the t-test was -2.294 > 2.023. It indicates that the data was clearly accepted. In other words, the correlation between students' proficiency in English vocabulary and students' ability to communicate was moderately accepted and the hypothesis was accepted.
The results supported the study conducted by Franscy (2016) which aimed to determine the English proficiency of the students and to determine whether there is a connection between the mastery of vocabulary and pronunciation. Based on the discussion of the study, there was a significant correlation between vocabulary selection ability and pronunciation ability with the ability to speak English. There was a positive and significant correlation between vocabulary selection ability and pronunciation ability. However, the research did not give clear information about the population and the sample of their research. Also, finding the population and the sample is confusing. Hence, the unequivocal grade of the students for the basic population and sample in the present study.
This study, likewise, is consistent with the findings of research conducted by Agustiawati (2022), there is a correlation between vocabulary selection ability and speaking ability when describing people. In addition, the study data analysis showed that there is a significant