EFL Learners’ Big Five Personalities, Language Learning Strategies, and Speaking Skills

Accommodating learners’ individual differences including personalities and language learning strategies is important in implementing the learner-centred instruction. This current research investigated the correlation of EFL learners’ Big Five personalities, language learning strategies, and speaking skills. It tried to answer the questions if there is (a) any correlation between the EFL learners’ Big Five personalities and speaking skills, (b) any correlation between the EFL learners’ learning strategies and speaking skills, and (c) any correlation between the predictor variables (EFL learners’ Big Five personalities and language learning strategies) and the criterion variable (speaking skills). This present study involved 357 students from 3 senior high schools in Pontianak, West Kalimantan, academic year 2018/2019. The data were obtained through questionnaires and speaking test. The data were analysed using statistical analysis through correlational and regression tests to answer the research questions. The results revealed that there was no significant correlation found between the EFL learners’ Big Five personalities and speaking skills (Sig. (2tailed)=0.464>alpha level 0.05), between the learners’ language learning strategies and speaking skills (Sig. (2tailed)=0.575>alpha level 0.05), and between the predictor variables and criterion variables (Sig. (2tailed)=0.712>alpha level 0.05). These results showed that other Dea Venda Marpaung & Agus Widyanotoro 74 Indonesian Journal of EFL and Linguistics, 5(1), 2020 variables outside personality and language learning strategy might correlate to the learners’ speaking skills.

treatment to all learners will not make them learn optimally since they do not learn according to their personal references. It means that the learners" individual differences, including personalities and learning strategies are not accommodated in the learning process. Learners do not get the chance to know themselves in the learning process. They also do not get the chance to explore and find the best learning strategies to use. Moreover, denying individual differences can disadvantage particular party, and at the same time benefits the other (Carrel, 1995;Pietrzykowska, 2014).
Some studies on the relationship and/or interaction between personality and language learning has shown conflicting results. For example, Suliman (2014) found that there was a positive correlation between personality and speech skills. On the other hand, another study conducted by Diaab (2016) argued that there is no connection between the learning process of personality and language learners, particularly speaking skills. This is similar to the correlation between learning strategies and speaking skills. However, most work on learning strategies focuses on its association with other factors, such as learning achievement. For instance , Nisbet, 2005 successfully demonstrated the connection between the application of language learning strategies, in particular metacognitive strategies with higher proficiency. Nonetheless, a number of research studies have shown that there is no connection and/or association between learning strategies for language learning and speaking skills. One of them is the work carried out by Pietrzykowska (2014). She revealed that there was no strong and positive correlation and/or between the learners" language learning strategies and their speaking skills. The present study, therefore, aims to answer these research questions: a. Is there any correlation between the EFL learners" Big Five personalities and speaking skills? b. Is there any correlation between the EFL learners" learning strategies and speaking skills? c. Is there any correlation between the predictor variables (EFL learners" Big Five personalities and language learning strategies) and the criterion variable (speaking skills)?

The Big Five Personality
The Big Five personality model was first introduced by Costa & McCrae in 1992. Empirically, the Big Five personality model has been shown to be valid and relatively stable over the years (Biedrön, 2011;Dörrenbächer & Perels, 2016). The Big Five Personality Model refers to a personality model that identifies and explains basic behavior of individuals through factor analysis (Feist & Feist, 2009;Cervone & Pervin, 2013). It is called The Big Five Personality Model because it refers to a large number of the five main components of its construction, namely: openness to experience, awareness, extroversion, kindness, and neuroticism, which is more familiar with the acronym OCEAN (Cervone & Pervin, 2013). Cloninger (2004) described each of the factors in the Big Five personality model. First of all, openness (to experience) describes artistic, imaginative and intellectual interests. Second, conscientiousness is typified by hard work, orderliness, and self-discipline. Third, extroversion refers to sociability, gaiety, and activity. Fourth, kindness reflects friendliness and respectful personality. Last, Neuroticism describes negative emotions. John, Naumann, & Soto (2008, p. 119) said that these five dimensions "represent personality at a very broad level of abstraction; each dimension summarizes a large number of distinct, more specific personalities." In short, The Big Five Personality Model is an empiric concept that identifies and explains basic individual personality traits within five general and bipolar dimensions through factor analysis.
The writer believes that the personality does have correlation with aspects in educational context. The writer believes that personality can lead to different behaviour in the language learning process. As Ortega (2013) argues that in learning speaking, there are two types of learners. The first is known as monitor over-users. These learners, when learning speaking, are easily nervous, scared to make mistakes, and afraid of being criticized. This, in the end fail them to speak up their ideas or thoughts, even though they may have practised for many times before standing up in front of the audiences. Meanwhile, there are also some students who are able to speak up their mind regardless the mistake they may make, namely monitor under-users. This type of learners just speak in English confidently, even with grammatical errors and lack of vocabulary knowledge. Therefore, personality contributes to the learners" learning process.

Language Learning Strategies
Learning strategies are "specific actions taken by the learner to make learning easier, faster, more enjoyable, more self-directed, more effective, and more transferable to new situations" (Oxford, 1990, p. 1). Hall (2001, p. 92) describes learning strategies as "goal-directed actions that are used by learners to mediate their own learning." Learning strategies are one of the most crucial factors that determine the success of language learning (Oxford, as cited in Chostelidou, Griva & Tsakiridou, 2015). In other words, learning strategies are particular plan or method learners choose and use to help them achieve particular goal in language learning. Oxford (1990) elaborated twelve functions of learning strategies. Two of them are related to learner-centered instruction and speaking skills. The first function is greater self-direction for learners. Language learning strategies encourage better self-directed learning for learners. Self-management is crucial for language learners themselves, as they will not always be close to their teachers to guide and assist them in the learning process, especially outside the classroom. Self-direction is needed to enable learners to actively develop their language skills. For this reason, learners need to realize that they need to make more effort to rely on themselves and use the appropriate learning strategy. This means that the implementation of language learning strategies is actually in line with the implementation of learner-centered instruction in the learning process. The second function states that communicative competence is the main objective of language learning strategies. All language learning strategies are geared towards the goal of communicative competence. Language learning strategies are therefore expected to assist foreign language learners to participate actively in authentic communication using a meaningful and contextualized language. In fact, each learning strategy has its own influence on learners ' language learning, which stimulates the growth of communicative skills. The growth of communicative competence can be seen in a number of ways, one of which is the language skills of the learners. Oxford (2017) presented an updated taxonomy of language learning strategies. It is called Strategic Self-Regulation (S2R) Model. This S2R model consists of four categories of strategy: metacognitive strategies (part of a larger set of "metastrategies"), cognitive strategies, affective strategies, and social-interactional strategies. The first is cognitive domain, in which Oxford (2017) referred as "the domain in which learners remember information and process new ideas, sounds, and experiences." There are two types of strategies under the cognitive domain, namely metacognitive strategies and cognitive strategies. The second is motivational domain.
This domain covers metamotivational strategies and motivational strategies. These strategies enable the learners to control and discover different pathways of learning and improving their confidence and providing direction in completing various language learning tasks. The third is social domain, which consists of metasocial strategies and social strategies. These strategies emphasize on the sociocultural nature of L2 learning and of life itself. These strategies elaborate the interrelationships among communication, culture, and identity. The last is affective domain. This domain consists of meta-affective strategies and affective strategies. These strategies encourage learner to regulate the emotional self (meta-affective and affective learning strategies) toward the positive.
These literatures strengthen the writer"s belief that language learning strategies give contribution to the learners" language learning process. Moreover, the language learning strategies have been developed to fulfil language tasks" requirements so that the learners are able to complete the tasks successfully (Oxford, 1990;2017). However, some research found that language learning strategies does not have correlation and/or relationship with language learning process or achievement (Lioa and Chiang, as cited in Pietrzykowska, 2014;Pietrzykowska, 2014;and Tilfarlioglu, 2005). This means that the issue is still open for further research and discussion.

Speaking Skills
Speaking is one of the productive language skills in the form of verbal interaction. Speaking requires not only the transmission of a message from the speaker to both the listener and the interlocutor, but also the ability of the speaker to cooperate and manage the turn of speaking. Speaking is spontaneous, face-to-face, generally unplanned, dynamic and context dependent (Hughes, 2011). It takes place in real time and has little time to plan (Thornbury, 2005). Further, speaking in foreign language concerns with accuracy and fluency (Brown, 2000). To summarize, speaking is an activity to convey message between speaker and interlocutor which requires one"s capability to take part in the interaction accurately and fluently. One is said to be able to speak in English if one is able to carry on a conversation reasonably competently (Brown, 2000). Speaker should be able to not only interact within the appropriate context, but also focus on the content. There is a demand for speakers to monitor and understand the other speaker(s), to think about one contribution, to make that contribution, to monitor its effect, and others (Celce-Murcia, 2001). In other words, mastering foreign language means one has the capability to use a foreign language in the real-life communication through interactive speech with the other speakers of the language.
Speaking covers a number of micro-and macro-skills that form the assessment criteria. Microskills refer to the production of smaller parts of the language, such as phonemes, morphs, words, collocations, and phrasal units. Meanwhile, the focus of the speakers is on broader aspects of fluency, discourse, function, style, cohesion, non-verbal communication and strategic options. Both speaking micro-and macro-skills have a total of 16 different objectives to be assessed in speech (Brown, 2003).
Based on the applied curriculum (Curriculum 2013) for the eleventh graders in Indonesia, this present study focuses on 7 microskills as the foundation of the scoring rubric of the speaking assessment. The 7 microskills are: (1) producing stress patterns in English, stressed and unstressed words, rhythmic structure, and in-national contours., which is suitable to pronunciation aspect in the speaking scoring rubric, (2) using an adequate number of lexical units (words) to achieve pragmatic goals, which is suitable to vocabulary aspect in the speaking scoring rubric, (3) using grammatical word classes (nouns, verbs, etc.), systems (e.g. tense, chord, pluralization), word order, patterns, rules, and elliptical forms, which is suitable to the grammar aspect in the scoring rubric, (4) producing fluent speech at different delivery rates, which is appropriate for the fluency of the aspect in the scoring rubric, (5) appropriately performing communicative functions in different situations, correspondents, goals, (6) using appropriate registers, implicature, pragmatic conventions, and other sociolinguistic features in face-to-face conversations, and (7) using facial features, kinesics, body language, and other nonverbal cues along with verbal language to convey meanings, which are suitable to the comprehension aspect in the scoring rubric (Brown, 2003).

Research Design
The present study used a correlation study to measure the degree of association (relationship) between two or more variables using a statistical correlation analysis procedure (Creswell, 2012). To answer the research questions, this research examined the correlation among EFL learners" Big Five personalities, language learning strategies and speaking skills.

Population and Sample
The population of this study were the students grade eleven coming from three state senior high schools academic year 2018/2019 in Pontianak, West Kalimantan. The three-state senior high schools were chosen from ten state senior high schools in Pontianak, West Kalimantan based on a number of strata, in this case was final examination average score in the latest 3 years from 2015 to 2017. The number of total population of this study was 636 students. Further, the sample of this study were chosen by administering probability sampling through stratified sampling strategy. Thus, the number of sample of this study was 357 students, which consisted of 144 male participants and 213 female participants. The writer had accepted permission from all schools and consent from all the participants who took part in this study.

Instruments
The main data collection instruments were in the forms of questionnaires and an English-speaking test. To reveal the learners" Big Five personalities, the Big Five Inventory (BFI) questionnaire was administered. This instrument was based on the concept of A Five-factor Theory developed by McCrae and Costa (2003). It consists of 44 statements in which individuals" each personality facet is measured based on the Big Five personality dimension. The learners" language learning strategies were revealed through the Strategy Inventory for Language Learning (SILL) questionnaire developed by Oxford (1990). This instrument consists of 50 statements in which individuals" each language learning strategies is revealed.
To test the English-speaking skills, the learners did a speaking test in the form of group role play. A scoring rubric adapted from Brown (2003) was employed to score the learners" speaking. In addition, inter-rater scoring was applied to make sure that the scoring process was objective, consistent and reliable. There were two scorers, the writer herself and an English teacher (from another senior high school outside the three subject schools). This scoring rubric covers 6 aspects in speaking, namely grammar, vocabulary, comprehension, fluency, pronunciation, and task. The researcher then adapted the scoring rubric to focus on only 5 aspects; grammar, vocabulary, comprehension, fluency, and pronunciation to adjust to the micro skills scored in this present study. Besides, for task aspect, it can be considered more suitable to be used in long-term scoring process. Each aspect was scored using score range from 1 (poor), 2 (meagre), 3 (moderate), 4 (good) and 5 (excellent).

Data Analysis Procedures
To answer the research question, the responses and data were computed through the SPSS (Statistical Package of Social Sciences) version 21 to obtain inferential statistics results. The Pearson Product Moment Correlation was administered to investigate the correlation among three variables: EFL learners" Big Five personalities, language learning strategies, and speaking skills. If the significance value (Sig. 2 tailed) was less than alpha level=0.05, this means that the correlation between independent and dependent variables exists.
For the validity of this study, the writer conducted an expert judgment for both Big Five Inventory (BFI) and Strategy Inventory for Language Learning (SILL) questionnaires. The validity tests trough expert judgments were done by the experts from English Education Department and Psychology Department appointed by Graduate School of Yogyakarta State University. Further, the writer also administered Cronbach"s Alpha (α) using SPSS version 21 to investigate the reliability of each scale in the instruments. The instruments are considered reliable if the coefficient is 0.5 to 0.6. The coefficients for Big Five Inventory questionnaire range from 0.969 to .971, while the coefficients for Strategy Inventory for Language Learning questionnaire range from 0.972 to 0.974. In addition, a pilot-test was also conducted by the writer to assess the readability of both Big Five Inventory (BFI) and Strategy Inventory for Language Learning (SILL) questionnaires. Ten students outside the sample joined a small group to answer and give judgment whether or not each statement along with the options were clear and comprehensible. The result revealed that all learners agreed that all items in both Big Five Inventory (BFI) and Strategy Inventory for Language Learning (SILL) questionnaires were clear and unambiguous. Last, the inter-rater reliability was conducted to make sure that the scoring process of the speaking test is consistent and reliable.

FINDINGS
This research was conducted to get accurate data to answer the research questions regarding the correlation among EFL learners" Big Five personalities, language learning strategies, and speaking skills. The data collected then were analyzed through several statistical analyses using SPSS version 21. After conducting the research and analyzing the data, further description of each statistical analysis is presented as follows. The following table aims to show the mean score and standard deviation of each dimension of the learners" Big Five personalities. According to the table below, Extroversion had the highest mean score that was 3.0318 compared to the other dimensions, with the standard deviation value was 0.46548. The next was Agreeableness with mean score was 2.9525 and the standard deviation value was 0.52936. Then followed by Openness with its mean score that was 2.9389 and standard deviation value that was 0.43476. For Conscientiousness, the mean score was 2.8399 and the standard deviation was 0.49546. The last was Neuroticism with mean score was 2.4350 and the standard deviation value was 0.60932. To sum up, both Table 1 and 2 showed that the most dominant personality dimension of the correspondents in this present study was Extroversion and the least dominant dimension was Neuroticism.

Result of Strategy Inventory for Language Learning (SILL) Questionnaire
The table below presents the percentage of each strategy. It is revealed that the majority of the research correspondents use metacognitive strategy (organizing and evaluating learning) with 28.9% or 103 students. In the second rank was social strategy (learning with others) which took 24.6% of the total number of correspondents, or 88 students. The third was compensation strategy (compensating for missing knowledge) with 24.4% of the total number of correspondents, or 87 students. For memory strategy (remembering), it took 9.2% or 33 students of the total number of correspondents. Affective strategy (managing emotions) was applied by 8.4% or 30 students of total correspondents, while the rest, 4.5% or 16 students of total 357 correspondents applied the cognitive strategy (mental process). The following table shows the mean score and standard deviation of each type of the learners" language learning strategy from the data analysis. It can be seen that metacognitive strategy (organizing and evaluating learning) had the highest mean score that was 2.7981 compared to the other dimensions, with the standard deviation value was 0.49838. Then followed by social strategy (learning with others) with mean score 2.6750 and standard deviation value 0.51348. For the compensation strategy (compensating for missing knowledge), the mean score was 2.6478 and the standard deviation value was 0.51214. The next, the mean score and standard deviation value of memory strategy (remembering) were respectfully 2.5203 and 0.45014. For affective strategy (managing emotions), the mean score was 2.5051 and the standard deviation value was 0.43853. Last, for cognitive strategy (mental process), the mean score was 2.3300, while the standard deviation value was 0.49153. Based on the result of the descriptive analysis, it appeared that from all correspondents in the present study, the majority of the students applied the metacognitive strategy (organizing and evaluating learning), while the least used language learning strategy was cognitive strategy (mental process).

Result of English-Speaking Test
The dependent variable, that is speaking skills, was measured using a speaking test in the form of group role play. The result of the speaking test is displayed in the table below. The highest speaking score was 96 with 0.3% or 1 student only, while the lowest was 28 with 0.6% or 2 students of the total 357 correspondents. The rest of the speaking score consist of; 80 with 4.5% or 16 students, 76 with 6.2% or 22 students, 72 with 10.1% or 36 students, 68 with 16% or 57 students, 64 with 15.1% or 54 students, 60 with 10.9% or 39 students, 56 with 11.8% or 42 students, 52 with 9.2% or 33 students, 48 with 6.2% with 22 students, 44 with 3.6% or 13 students, 40 with 3.1% or 11 students, 36 with 1.7% or 6 students, and 32 with 0.8% or 3 students of the total 357 correspondents. Thus, the majority of the correspondents in this present study, which was 16% got 68 which was actually lower than the standard score set in the curriculum. The Table 6 below shows the mean score and standard deviation of the learners" speaking score. According to table, it was found that the mean score of the total score was 61.11, and the standard deviation was 11.133.

Research Questions (1) Is there any significant correlation between EFL learners' Big Five personalities and speaking skills? (2) Is there any significant correlation between EFL learners' language learning strategies and speaking skills?
The multiple correlation was administered in order to find out whether or not there was any among the variables in the present study. The result of Pearson Product Moment answered the first research question regarding the correlation between EFL learners" Big Five personalities and speaking skills. According to the following table, the obtained level of significance was Sig. (2tailed)=0.464, which was higher than alpha level of 0.05. This result shows that there was no correlation between EFL learners" personality and speaking skills. Besides, the obtained coefficient range of Pearson Correlation was 0.039 which could be considered as no correlation based on range -1 to 1. Thus, this present study found that there is no correlation between the EFL learners" Big Five personalities and speaking skills.
The same case happened to the result of Pearson Product Moment correlation analysis between EFL learners" language learning strategies and speaking skills. According to the table below, it can be seen that the Sig. (2tailed)=0.583, which was higher than alpha level of 0.05. Therefore, it is statistically believed that there is no significant correlation between EFL learners" language learning strategies and speaking skills. Moreover, the obtained coefficient range of Pearson Correlation showed 0.029, which means that based on range -1 to 1, there was no correlation between language learning strategy and speaking skills. As the result, this study found no correlation between the EFL learners" learning strategies and speaking skills. More specifically, another Pearson Product Moment was administered in order to investigate the correlation between each personality dimension of the learners and their speaking skills. It can be seen in Table 8 that the obtained level of significance for speaking skills and Openness was Sig. (2tailed)=0.015, which was lower than alpha level of 0.05. This indicated there was a correlation between Openness and speaking skills. For Conscientiousness, the obtained level of significance which was the obtained level of significance was Sig. (2tailed)=0.583, which was higher than alpha level of 0.05. This showed that there was no correlation between Conscientiousness and speaking skills. For the the obtained level of significance for speaking skills and Extroversion was Sig. (2tailed)=0.275, which was higher than alpha level of 0.05. This indicated that there was no correlation between Extroversion and speaking skills. For Agreeableness, the obtained level of significance for speaking skills and Agreeableness was Sig. (2tailed)=0.047, which was lower than alpha level .05. This showed that there was a correlation between Agreeableness and speaking skills. Lastly, for Neuroticism, the obtained level of significance for speaking skills was Sig. (2tailed)=0.583, which was higher than alpha level 0.05. This showed that there was no correlation between Neuroticism and speaking skills. In conclusion, from five dimensions of Big Five personality model, only Openness and Agreeableness had correlation with speaking skills, while the other three, Conscientiousness, Extroversion, and Neuroticism did not. Another Pearson Product Moment was administered to reveal the correlation between each type of language learning strategies of the learners and their speaking skills. It can be seen in Table 9 that the obtained level of significance for memory strategy (remembering/A) and speaking skills was Sig. (2tailed)=0.982, which was higher than alpha level of 0.05. This showed that there was no correlation between memory strategy and speaking skills. For cognitive strategy (mental process/B), the obtained level of significance was Sig. (2tailed)=0.178, which was higher than alpha level of 0.05. This indicated that there was no correlation between cognitive strategy and speaking skills. The obtained level of significance for compensation strategy (compensating for missing knowledge/C) and speaking skills was Sig. (2tailed)=0.581, which was higher than alpha level of 0.05. Thus, there was no correlation between compensation strategy and speaking skills. Next, the obtained level of significance of metacognitive strategy (organizing and evaluating learning/D) and speaking skills was Sig. (2tailed)=0.151, which was higher than alpha level of 0.05. This meant that there was no correlation between metacognitive strategy and speaking skills. The obtained level of significance for affective strategy (managing emotions/E) and speaking skills was Sig. (2tailed)=0.090, which was higher than alpha level of .05. This showed that there was no correlation between affective strategy and speaking skills. The obtained level of significance of social strategy (learning with others/F) and speaking skills was Sig. (2tailed)=0.694, which was higher than alpha level of 0.05. This indicated that there was no correlation between social strategy and speaking skills. This concluded that there was no correlation between each type of language learning strategy and speaking skills.

Research Question (3) Is there any correlation between predictor variables (EFL learners' Big Five personalities and language learning strategies) and criterion variable (speaking skills)?
The linear regression analyses were conducted to reveal the correlation between the predictor variables (EFL learners" Big Five personalities and language learning strategies) and the criterion variable (speaking skills). According to Table 10 below, the significance value was 0.712 which was higher than significant level 0.05. It indicated that the independent variables (personality and language learning strategy) did not predict the dependent variable (speaking skills). In addition, the following table presents the model of regression analysis for factor predicting speaking skills. The R Square value was 0.002. This indicated that the predictors (learners" personalities and language learning strategies) explained 0.2% of the learners" speaking skills. This means, the learners" speaking skills in the present study could be explained only 0.2% by the variables of personality and language learning strategy, while the other 99.8% might presumably explained by other variables which were not observed in this study. Based on the results from both tables, it can be concluded that there is no correlation among the EFL learners" personalities, learning strategies, and speaking skills.

DISCUSSION
Accommodating learners" individual differences including personalities and language learning strategies is important to implement the learner-centred instruction. The purpose of this study was to investigate the correlation among EFL learners" Big Five personalities, language learning strategies, and speaking skills in Pontianak, Indonesia. Based on the data statistical analyses and the findings, this study appeared to find no correlation among the variables. Furthermore, the findings also suggested that there was no significant correlation between the predictor variables (EFL learners" Big Five personalities and language learning strategies) and the criterion variable (speaking skills).
Firstly, the correlational analysis revealed that there was no correlation between EFL learners" Big Five personalities and speaking skills. This result indicates that even without accommodating the learners" personalities in the classroom activities, they can still learn optimally. It means that no matter what the learners" personalities are, they have the same chance to master English speaking. This finding, therefore, support the findings from previous studies (e.g., Busch, 1982;Biedroń, 2009;Diaab, 2016). Busch (1982) through her research on the correlation between Japanese EFL learners" personality (extrovert and introvert) and their English-speaking proficiency found that there was no correlation between both variables. In addition, she argued that introversion-extroversion itself could not be sufficient to account for much of the variance in English proficiency. She then emphasized that a certain combination of a number of specific factors is likely to affect one's language learning process.
Similarly, the research findings by Biedroń (2009) revealed that there was no significant evidence found that proved the correlation between cognitive and personality factors. She added that the other factors such as motivation, effort, and good organization of work play huge roles in learning new language. Another explanation for the lack of significant correlations between the personalities of the learners and their speaking skills is that the other factors that influence the learning process of the learners are internal or external factors. Likewise, Diaab (2016) in his research on speaking difficulties, reported that the difficulties in speaking faced by EFL learners might not because of the internal factor, such as personality, but mainly due to the external factors, such as learning environment and teaching style. His research findings revealed that learners were overloaded with reading comprehension, vocabulary memorization, and grammar patterns while speaking skills themselves were almost neglected. In addition, his research correspondents argued that poor speaking activities and opportunities contributed to the difficulties of mastering speaking English.
In contrary, the findings of the present study show different perspective with several research findings (e.g., Suliman, 2014, andKhoiriyah, 2016). Suliman (2014) in Libya proved that there was significant and positive correlation between students" personalities and language acquisition process. She mentioned that extroverted students could easily communicate in English classes compare to the introverted students. She found that the extrovert learners use the second language to interact without inhabitation, to talk more fluently, to take action with less reflection, to work better in groups and to excel during classes with a high level of activity. However, extroverted students might not produce accurate output. On the other hand, introverted students tend to talk less and reflect more before speaking, like being quiet, like working independently or with one or two other people. They tend to be more passive than actively social. Suliman stated that the students who were introverted are obsessed towards producing grammatically accurate sentences. Briefly, she agreed that students who are extroverted are more successful in second-language communication.
Another research by Khoiriyah (2016) in Malang, Indonesia, also revealed that extroverted students spoke English better than introverted students. Her research findings found that extroverted students were very enthusiast having a test, which was in the form of an interview, because they could practice speaking in English. This means that extrovert students have high motivation and good attitude to learn English. Based on the students" performances, even though their pronunciation was unclear, it was revealed that extroverted students spoke English without hesitation. Meanwhile, introverted students tend to process their ideas before speaking, sometimes avoiding linguistic risk-taking in conversation. They tried to speak slowly, and were hesitate to speak up because they were scared to make mistakes. However, the introvert students were good at grammar. The introverted students corrected their grammar mistake and were worried if the listener (the researcher) did not get their point. In conclusion, introverted students had better pronunciation and understanding than the extrovert students did.
An interesting result can be seen in Table 8. Two dimensions of the Big Five personality, namely Openness and Agreeableness had correlation with speaking skills, even though the number was statistically low. These results support the research findings by Verhoeven & Vermeer (2002) which revealed that learners with openness to experience are most likely to strongly correlate with most measures of attained communicative competence, which can be considered as having good productive skills. Agreeableness dimension, however, showed a bigger number related to its correlation to learners" speaking skills. In line to this result, the research done by Komarraju, Karau, Schmeck, and Avdic (2011) agreed that agreeableness traits are friendly, trustworthy, and cooperative in which they are expected to prefer group work and be willing to ask for help whenever they need it. These traits presumably contribute to the existence of correlation between the learners" Agreeableness dimension and speaking skills.
Secondly, this present study also found that there was no correlation between EFL learners" language learning strategies and speaking skills. This result indicated that the use of language learning strategies does not the only aspect in mastering English speaking. Thus, this supports the findings from previous studies (e.g., Lioa & Chiang, as cited in Pietrzykowska, 2014, andTilfarlioglu &Yalçın, 2005). The study carried out by Lioa and Chiang (as cited in Pietrzykowska, 2014) revealed that there was no correlation between the learners" learning strategies and speaking skills. Similarly, Tilfarlioglu and Yalçın (2005) in their study examining the interdependence between strategies and language proficiency in the Turkish educational context has shown that there was no significant correlation between the language learning strategies and learning achievement. Another research conducted by Pietrzykowska (2014) on the relationship between learning strategies and speaking performance found that there was no strong and positive correlation between the English Department students" language learning strategies and their speaking skills. This result shows that the improvement of the learners" speaking skills is not related to their use of learning strategies. Instead, it revealed that there were negative correlations between memory, metacognitive, affective, and social strategies and speaking skills. This means that using these groups of strategies in high frequency lead to lower level of speaking performance. Nevertheless, there is a positive relationship found between cognitive and compensation strategies and speaking. The whole result then indicated that applying language learning strategies could help improving speaking proficiency especially for aspect grammar and accuracy. Cognitive strategies seem to give positive influence not only on upgrading the learners" grammar but also enriching their vocabulary. Compensation strategies appear to facilitate the learners in improving their fluency. Memory strategies seem to be the least helpful in speaking in general, considering its components.
Contrary with the present result, several scholars (e.g., Bremner, 1999;Green & Oxford, 1995;Huang, 2001;Phillips, 1991;Sheorey, 1999;Takeuchi, 1993;& Wharton, 2000) managed to find a correlation between the use of language learning strategies and language performance in general. Bremner (1999) conducted his research on investigating a relationship between language learning strategies and language proficiency in Hong Kong. The result indicated the existance of association between the use of language learning strategy and language proficiency. Likewise, Green and Oxford (1995) through their research investigating about learning strategies, second language proficiency, and gender found out the existence of significant relationship between the use of language learning strategy and successful language learning.The research result by Phillips (1991) on learners" strategy use and ESL proficiency revealed something intriguing. It found out that the frequency of strategy uses and range increased as the learners became more proficient learners. Similarly, Sheorey (1999) through her research found that students who use learning strategies more often are those with higher proficiency in English. Wharton (2000) agreed, saying that students with good and fair proficiency were found to be using learning strategies more frequently than those with poor proficiency.
Lastly, the linear regression analysis showed that there is no correlation between the predictor variables (EFL learners" Big Five personalities and language learning strategies) and the criterion variable (speaking skills). In other words, even though the learners" personalities and language learning strategies were not accommodated in the language learning process, it did not hinder the leaners" language process, especially in learning speaking. As Diaab (2016) mentioned in his research on speaking difficulties, that rather than from inside factors, the difficulties in speaking faced by EFL learners might come from external factors, such as learning environment, teaching style, poor speaking activities and opportunities. Similarly, Pietrzykowska (2014) also noted through her research that applying a variety of strategies inappropriately to a task would not maximize learners" learning efficiency. Rather, the learners need to recognize the most suitable strategies to employ on different aspects based on their own learning style or preference, comprehend how to own the learning process by maximizing the use of the learning strategies, thus they would be better language learners and users (Chamot, 2004;Pietrzykowska, 2014).
Nevertheless, this result does not mean that both personality and language learning strategies contribute nothing to learners" speaking skills. Rather, this result means that it takes more than only those two variables for the learners to learn and master speaking. There are many other variables which correlate to the learners" speaking skills positively, and/or even predict speaking skills more than the two predictor variables in the present study. Numerous research have tried to investigate various factors that may have correlation with, and at some extent predict the learners" speaking skills (e.g. Afshar & Rahimi, 2016;Afshar, Sorabi & Mohammadi, 2015;Bergil, 2016;Boonkit, 2010;Dutton, Van der Linden, Madison, Antfolk, & Menie, 2016;Fricke & Herzberg, 2017;Karatas, Alci, Bademcioglu, & Ergin, 2016;Zeinivand, Azizifar, & Gowhary, 2015;Çağatay, 2015). Based on those researches, it can be seen that the factors are varied. There are affective factors, such as personality, anxiety, self-confidence, or willingness to communicate (WTC) or cognitive factors, such as critical thinking, learning strategies, learning styles, and others.

CONCLUSION
It appears that there is no correlation found neither between the EFL learners" Big Five personalities and speaking skills, nor between the EFL learners" language learning strategies and speaking skills. The results also suggest that there is no correlation between the predictor variables (EFL learners" Big Five personalities and language learning strategies) and the criterion variable (speaking skills). These suggest that there are other variables outside personalities and language learning strategies that contribute to learners" speaking skills. The limitation of this study is that it did not provide qualitative analysis. Thus, future research might necessarily provide qualitative analysis to explore this issue deeper. Hopefully, the result of this research can give the insightful discovery and open another door for deeper exploration concerning this issue.