FACTORS AFFECTING ENGLISH LEARNING OUTCOMES -APPLYINGSTRUCTURAL EQUATION MODELING (SEM)

This study aims to present an overview of researches on factors affecting the results of students learning foreign languages, especially English, from previous studies. The results of retrospective analysis of documents and studies have shown the gaps of research methods in analyzing the factors affecting English learning outcomes of students and recommended the use of structural equation modeling methods (SEM) to predict students' English learning outcomes based on both subjective and objective factors.


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Alkaff (2013) implemented a research with science and art students to determine students' attitude towards Englishlearning. The research has shown that most students have a positive attitude, and they strive to improve their English although there arefew chance of practice. Omar (2013) investigated whether students' attitude was influenced by the nationality of teachers or not. The results have shown that the majority of students have a positive attitude towards learning English, and that the teacher's nationalitydonot impact on the positive orientation towards their English language. Ahmed (2015) conducted a study with amateur English learners in Malaysia to explore their attitudes towards English learning and what may have hindered their learning. The outcomes have shown that their attitudes towards learning and using English are extremely positive.
Regarding to studies conducted in Thailand, Chaihiranwattana and Sirikun (2011) conducted a survey to determine the attitude towards English learning of 388 university students who did not specialize in English from the University of Siam . The results have shown that most of the students have a positive attitude while Thadphoothon (2001) has found that undergraduates from Dhurakij Pundit University have a neutral attitude towards learning English. In theresearch conducted by Nuchnoi (2008), the findings have indicated that graduates from Rangsit University arehighly motivated and findlearning English enjoyable, necessary and beneficial. However, this should not come as a surprise as these Rangsit University graduates are majoring in English. Although some researchers investigated whether Thai students had a positive attitude towards learning English or not, one of the areas that is still under-explored is whether Thai students who are in the field of science and technology also share a positive attitude towards English. Additionally, previous studies did not target the use of English outside the educational contexts. Therefore, the present study aims to fill this gap and also to discover if there are significant differences in proficiency between students from six different faculties and if there is a correlation between users and the use of English in five different contexts.
Al-Bustan and Al-Bustan (2009) investigated the attitudes and interests of non-English-major ESL students towards learning English at Kuwait University. The results of the study implied that the majority of students recognized the importance of learning English, and most of the participants agreed that they had difficulty in the four skills (reading, writing, speaking and listening). Students' preferable learning methods include discussion, multimedia tasking, and computer-based tasking.

Motivation
It is undeniable that motivation plays an important role in learning a foreign language. There are many studies which have shown that motivation is one of the predominant factors determining the success of language learning (Bradford, 2007;Dörnyei, 1998;Engin, 2009).Motivation is an essential part of learning. (Brewer & Burgess, 2005). Particularly,in language learning, the learner must wish to achieve or do something to achieve it. Cook (2000) said that language learning processsaw a progress when students are motivated in a language learning context. Whereas, Ellis's observation (1994) indicated that there was a proportion of students learningwith inner motivation and that it triggered the learning process. He also mentioned that language instructors acknowledged the importance of learners' driving force, but did not explain their own sense of failure about their students' disincentive.
According to Ditual (2012), learners are highly motivated with a positive attitude towards learning English. There are internal and external motivation. Moskovsy and Alrabai (2009) argued that internal motivation plays a more important role than external motivation in learning English. Other findings of this study indicated that inner motivation is more consistent with learning English.

Teacher -student relationship
Students who have a constructive relationship with teachers will be inspired to study. Students are more engaged in the learning process when they have a supportive relationship with teachers; they tend to work harder in the classroom, be more consistent, accept criticism, better cope with stress and pay more attention to the instructor (Little and Kobak, 2003). Furthermore, according to Hughes et. al. (2006), the typical level of support form teachers can also be considered one of the aspects of the classroom environment. The classroom environment has a strong impact on students.
Consequently, the significant effect of the change in the student-teacher relationship on students' academic achievements deserves more attention -given the quality and dynamic nature of these relationships. Mental supportand academic guidance from instructorswere critical to improve students' academic success (

Anxiety
The effects of anxiety on reading comprehension in foreign languages such as Spanish, Japanese, Russian, French, English (Sellers, 2000;Saito et al, 1999;Oh, 1990) have indicated that the fear of learning a foreign language affects the reading comprehension performance of students at intermediate and advanced levels.
MacIntyre (1995) showed that anxiety about learning a foreign language has a negative relationship to one's selfawareness of abilities,which leads to a decrease in learning performance. Academic success in a foreign language class requires learners to be fluent in that language. In fact, not all language learners are good at foreign languages. As a result, low ranking can lead to anxiety among incompetentlearners, who are skeptical about theirperformance in the language class.
Concern about learning a foreign language has also been found to affect academic accomplishment in foreign language classes. Aida (1994) studied the relationship between language anxiety and the academic performance of 96 second year American students who used Japanese as a second language. The results revealed a moderately significant inverse correlation, suggesting that the higher the students' anxiety level, the lower their scores. An equally interesting result obtained from this study was that the mandatory group, consisting of students taking Japanese classes to meet university language requirements, showed higher levels of anxiety compared to those with pleasure.

Testing and assessment
Evaluation is an integral part of a teaching and learning system. It is therefore not surprising that researches haveshown that assessment has the greatest impact on both learning effort and learning quality. Feedback on student performance (how students' performance are related to learning objectives) is necessary to help them keep on track and adapt to course requirements (Nicol & Macfarlane-Dick, 2006, p. 205). First yearstudents must have a clear understanding of the academic requirements. That perception can be built up through on-going assessments. Formative assessments can help reflect the objectives and provide feedback to students, so they know how to proceed to meet the requirements (Nicol, 2009). Indeed, studies have shown that feedback improves learning, and the achievement is among the greatest educational reported ones. Correspondingly, the use of classroom assessment provides teachers with data on teaching effectiveness and students' comprehension. Assessment from teachers does affect learning results, especially in foreign language teaching. Karemera (2003) found that students' learning outcomes were significantly correlated with the satisfaction with the learning environment and facilities, including libraries, computer labs, etc. in schools. For the primary variables, he found a positive effect of high school performance and university performance, but no statistical evidence of a significant correlation between family income levels and academic outcomes. Robert and Sampson (2011)recognized that educating board members would have positive impact on schools, as long as students do their job. That students actively participate in the learning process are found to be positively correlated with learning outcomes. Student learning efforts and proper use of school-provided facilities will lead to a good fit between a student's learning style and a progressive student's performance (Ali et al., 2009). Saenz et al. (1999), held the view that students' performance is related to library use and the educational background of their parents. Library use positively affects student learning outcomes. The education background of the father obviously has a relationship with the academic environment for a student (Kirmani & Siddiquah, 2008).

Communication
Hijazi and Naqvi (2006) realized that the most important factor that positively influences a student's achievement is their English proficiency. If students have strong communication skills and strong English skills, they will increase their learning efficiency. Students' learning outcomes are affected by communication skills; communication can be considered a variable that can be positively related to student performance in open learning. One major difference of this study compared to previous ones is that it focuses on open learning (Abdullah, 2011). (Haenlein & Kaplan , 2004). Multiple relationships between variables can be represented in a series of single and multiple regression equations. Linear structural modeling technique uses a combination of quantitative data and correlation (causeandeffect) assumptions into the model. With SEM, researchers can visually examine the relationships that exist between the variables of interest to prioritize resources to better serve customers. The fact that potentially difficult to measure variables can be used in SEM makes it ideal for solving business research problems. SEM is a powerful statistical technique to meet the following requirements: 1. Analyze numerous multiple regression models simultaneously; 2. Analyzeregression with multi-collinearity problem; 3. Analyzethe path of analysis with many dependent variables; According to Bollen (2011) (Tharenou, Latimer and Conroy, 1994). In the field of education, many researchers also exploit this model to analyze the factors that affect learners' learning outcomes.

Structural Equation Modeling (SEM) Structural Equation Modeling (SEM) is a second generation statistical analysis technique developed to analyze multidimensional relationships between multiple variables in a model
As a consequence, when studying the model of factors affecting academic achievement in general and factors affecting English learning outcomes in particular, it is necessary to use structural equation modeling to realize the effectiveness. and predict students' learning outcomes.

Recommended research method:-
Based on previous studies on factors influencing students' English learning performance, we find that the studies that preceded mostly use qualitative research methods through interviews. Some studies used quantitative research methods through descriptive statistical analysis and ANOVA testing. However, we have not seen structural equation modelling (SEM) analysis used to predict the factors that affect students' English learning outcomes. Therefore, we recommend this model to predict the factors that affect English language learning outcomes and uncover direct and indirect relationships. The proposed model is as follows: 915

Conclusion:-
From the studies reviewed above, we notice that there are many factors that affect students' English learning performance at university level. These factors may be internal but also external ones. However, in order to understand these linear relationships, we not only use unilateral descriptive statistics to account for learning results, but we also need to have inference statistics using linearmultivariable regression. Many previous studies have indicated this relationship but only use qualitative research and some descriptive statistics. Therefore, from the research reviews, we propose an analytical model of factors affecting English learning outcomes using structural equation model (SEM), which is suitable for predicting how the factors affect English language learning outcomes.