STUDENTS’ MOTIVATION TO ACQUIRE ENGLISH THROUGH VIRTUAL LEARNING MIDST COVID-19 PANDEMIC

This research aimed to find out students’ motivation to acquire English as a foreign language through virtual learning midst Covid-19 pandemic. It involved 202 students spread throughout Indonesia. Data were collected by means of motivation questionnaires adopted from the Situational Motivation Scale (SIMS) of students’ motivation, i.e., instrumental motivation and integral motivation. The data were analyzed with descriptive statistics and Pearson’s Correlation on SPSS 22. The result shows that the students have a low level of motivation both for integrative and instrumental motivation to acquire English. The statistical calculation reveals that there is a correlation between the students’ motivation and virtual learning activity as shown by the level of significance 0,000<0,05 with the coefficient Pearson’s correlation of 0,282. There is no correlation between the students’motivation and the Covid-19 pandemic as depicted by Pearson’s correlation of 0,062 with the significant level of 0,382>0,05. The research implies a need for a more innovative instructional design for virtual language learning to better improve students’ motivation to learn English during the Covid-19 pandemic.


INTRODUCTION
Motivation is an influential factor in learning a second or foreign language. It is confirmed as the key to success or failure in second language learning (Moroz et al., 2018;Hong & Ganapathy, 2017;Smith & Loewen, 2018). Motivation serves as the support system for shaping learning persistence to achieve learning goals. In the learning process, students' motivation has different types based on their personal goals. Two types of motivation, called integrative and instrumental motivation, play an important role in language learning (Carrio-Pastor & Mestre, 2014;Gardner, 2010;Rahardjo & Pertiwi, 2020;Rozmatovna, 2020;Smith, Briggs, Pothier, 2018;Yu, 2019;Zanghar, 2012).
This research focuses on investigating students' instrumental and integrative motivation. It aims to identify and investigate students' motivation in learning English through virtual learning midst Covid-19 pandemic. These findings of the investigation are expected to inform and motivate teachers or practitioners to make the interactive instructional design by taking into account students' instrumental and integrative motivation. In this pandemic situation, students' motivation can be lifted by choosing the appropriate virtual learning. The teachers are supposed to define uncommonly virtual learning as the lessons with visual aids and engage learning facilities (Marutschke et al., 2019;Tomas et al., 2019).
Hudson (2000) has defined instrumental motivation as the direction to get practical benefits to gain language proficiency. He has stated that instrumental motivation reflects learners' recognition of interest to perceive the actual benefits of learning the language. Such recognition has efforts to understand benefits of language learning such as having a better job or a good salary as a consequence of mastering L2 (You & Dornyei, 2016;Tileston, 2010). Instrumental motivation indicates desire to study a foreign language in order to achieve a practical reason and to gain language mastery for a utilitarian objective such as reaching future employment opportunities (Rahardjo & Pertiwi, 2020). On the other hand, integral motivation is learners' desire to integrate the second language culture into part of society and to participate in the target language group (Saville-Troike, 2006). Integrative motivation is characterized by learners' attitudes towards their desire to interact with the target language communities (Qashoa, 2006). Integrative motivation is the desire to interact with native speakers as well as that to develop a positive attitude towards the factors underlying interests and intake for second language acquisition. Motivational intensity, attitude towards learning English, and student's perception of the quality of the English course are found to be the predictors of achievement (Cocca & Cocca, 2019;Hoey, 2017).
Recently, education systems around the world are placed in chaotic situations due to Coronavirus (Covid-19) pandemic. The data reports that over 60 million students have temporarily out of school during the Covid-19 infection in Indonesia (UNESCO, 2020). They have conducted a survey which shows the most significant trouble for students who study at home is the lack of internet access and electronic devices. In cases of study at home, the influential factor for students to acquire a second language learning English is internal motivation. Li (2020) has indicated that the learner's success in second language learning is formed from the ability to act on their own motivation through actively utilizing the resource and affordance in the education environment.
The situation of the education system was changing in the second half semester of 2020 when the first medical patient of coronavirus Covid-19, was infected. This virus has infected 61.963.422 people worldwide, the last report on November 2020. For the year 2020, 68 million students in over 530.000 schools from pre-primary through tertiary level have decided to have closed. In this situation, some universities and schools are remained not allowed teaching-learning process at schools (Murphy, 2020). The school lockdown has challenged teachers, students, and parents to confront new conditions (Huber & Helm, 2020). Alqahtani and Rajkhan (2020) have said that educational institutions are shut down all over the world, which impacts over 60% of students and causes massive disruption of the educational systems since the Covid-19 pandemic.
The government gives an alternative solution to move traditional learning becomes virtual learning.
They call it kelas daring or study at home, which developed in learning platform namely Rumah Belajar. Abidah et al. (2020) have stated that the traditional learning that emphasizes the interaction of student-teachers inside the classroom should shift to distance learning because of the significant impact of Covid-19. Virtual platform has changed the traditional learning to the modern like artificial intelligence (Di Vaio et al., 2020). A virtual learning platform provides a sustainable, high-quality educational infrastructure that fosters participation and collaboration (Almarzooq, Lopes, & Kochar, 2020;Hussain et al., 2018). However, Selwyn et al. (2018) have found that English teaching practices still rely much on offline classroom activities or use old-fashioned and predigital teaching methods.
Based on the research by Yanti, Kuntarto, and Kurniawan (2020), the teachers expect that the learning process is varied, contextual, attractive, fun, and efficient although done in e-learning. E-learning is a learning process supported by electronic technology to access courses outside the classroom (Ngampornchai & Adams, 2016). Beluce and Oliveira (2015) have mentioned the kinds of e-learning, e.g., Virtual Learning Environment (VLEs), such as online learning; and Virtual Learning Model as one solution to motivate students in order to keep their learning process. The characteristics of e-learning are the geographical distance between students and teachers, the need to involve students' skills for using the internet access, and the flexibility in study timetable (Filcher & Miller, 2000;Quevedo, 2011;Testa & Luciano, 2010).
The purpose of distance learning is to encourage communication review through online resources available for students' needs (Leszczyński et al., 2018;Schneider & Laurin, 2020). Kareal and Klema (2006) have compared the particular feature of some open-source virtual learning systems and effective education. It is implied that the biggest obstacle of virtual learning is adaptability and motivation. In accordance with virtual learning to motivate students, the research by Kim & Frick (2011) has shown that virtual learning is a great positive factor to change students' motivation in language learning proved on students' achievement.
Related research has found that the students in Georgia confirm that the fast transition from the traditional to the virtual education form and the gain experience can be used in the next educational system after pandemic occurrence (Basilaia & Kvavadze, 2020). Differently, Adnan and Anwar (2020) have argued that the perspective of students in Pakistan who learn through the virtual platform cannot afford to create successful learning. The students have difficulty to access the internet due to financial issues and lack of motivation to learn since face-to-face interaction stopped.
Based on these explanations and research, it can be concluded that the motivation of students can be affected by some factors, such as virtual learning and the students' condition during the Covid-19 pandemic in Indonesia. This research aims to (1) find the level of students' motivation on L2 acquisition, (2) analyze the correlation between students' motivation to learn English and virtual learning, and (3) analyze the correlation between students' motivation to learn English and the urgent situation of Covid-19 pandemic.

METHODS
This research uses the quantitative research method. The participants in the research are 202 students from junior high school, senior high school, undergraduate, and post-graduate students' levels. They participate in the course using virtual learning. The classes take place in various districts in Indonesia which are affected by Covid-19 in 2020. The research is evaluated by the Situational Motivation Scale (SIMS), developed by Guay, Vallerand, and Blachard (2000), and Degang's (2020) Likert scale. The data analysis uses the Likert scale of agreement or disagreement to interpret the types of learning English Motivation (Table 1). The data are collected from the student participants through an online survey for five months, from July to November 2020. The first stage is undertaken from the participation of university students in a public higher education institution. In the second stage is students from senior and junior high school who assign the questioner. They fill in the educational background level based on their circumstances.
The participants receive a link sent using the link system of Google form provided by the researcher. In this way, the participants are able to access the instrument by clicking on a link provided on the first page of students' motivation types adopted from Hong and Ganapathy (2017), i.e., Instrumental Motivation and Integral Motivation. This instrument is also ever adopted by Rozmatovna (2020). The indicators of the questioners, together with the research results, are shown in Table 3.
The data analysis aims to answer the research objective to identify the students' motivation on the virtual education platform or learning model during the Covid-19 pandemic. The data collected are organized in spreadsheets in SPSS Statistic 22 and are subjects to descriptive statistical analysis. The data rate has required detail to the frequency, mean, maximum, minimum score, and standard deviation of the variable investigated. Pearson's correlation is applied to meet the data. Then, the level of significance can be seen in Table 2.

RESULTS AND DISCUSSIONS
The results of data analysis are processed through IBM SPSS Statistics 22. The research involves 20 question items with a twelve-point indicated students' motivation, a four-point indicated virtual learning model, and a four-point has shown pandemic situation. The research results are shown in Table 3. The highest score of 4,39 is shown in question item number 13, implying that the students prefer doing traditional learning models to virtual learning models. This probably relates to the opportunity for accessing e-learning, which is still difficult based on students' perceptions (Hong & Kim, 2018;Mamattah, 2016;Victoria, Mislinawati, & Nurmasyitah, 2018).

I n P r e s s
The questioners that describe instrumental motivation in the research are built with four indicators. In comparison, integral motivation with five indicators can be seen in Table 3. The data obtained related to the student's motivation are in Table 5. The rates of instrumental motivation indicate a minimum score of 14; a maximum score of 30; a median of 6 question items on numbers 3,7,8,9,15, and 20 is 22,00 with the rank of standard deviation in Table  5 is 3,144. On the other hand, the rates of the median score on an integral motivation are 17,00; a maximum score of 29; a minimum score of 6; and the rank of standard deviation is 3,916. The overall mean score and average mean scores for instrumental motivation (22,19) and integrative motivation (16,83) fall in the low motivational level (see Table 1).
The superiority of instrumental motivation over integratively motivation has also been found in some previous research done by Al-Ta'ani (2018); Galea and Muftah (2013); Hong and Ganapathy (2017); Masum (2016); and Rozmatovna (2020). Students instrumentally motivate to acquire English for a practical reason to pass the English subject school exam on virtual learning midst Covid-19 pandemic. Participants who are highly motivated to acquire English show there have difficulties and complex problems with virtual learning. The closure of e-learning during a pandemic may result in students spending less time learning, stress symptoms, a change in the way they interact, and a lack of learning motivation (Pietro et al., 2020). Although, Catálan, Catalán, and Vázquez (2018) have found that the platform of e-learning or virtual learning increases students' confidence, reduces stress, and enhances empathy, but it is not proven by this research. It is completed by Arkorful and Abaidoo's (2015) research that there are advantages and disadvantages of implementing e-learning in higher education.
Based on responses to question number 20, the participants consider that doing virtual instruction is more important than learning English. As seen in Table 3, the score of 4,36 means the participants show a strong agreement with the question item. It coincides with Sujarwo et al.'s (2020) research that shows the students' participation in online learning positively impacts the midst of the Covid-19 pandemic. It is because students are interested in accessible and flexible classes. However, their motivations to acquire a second language during Covid-19 need more improvement. Verawardina et al.'s (2020) research proves that innovation in language learning is fully needed to support the development of the educational system.
Although the fact shows that the students do not have a better experience and master competencies during the online learning midst pandemic Covid-19, the research indicates that teachers are not in line with students' need to learn a second language. Similar to results from other studies, they reinforce the students but not their proficiency (Luong-Phan & Effeney, 2015;Syauqi, Munadi, & Triyono, 2020). The investigation constructs that the teacher's role can perform as a factor for student satisfaction activity undertaken on e-learning (Al-Rahmi et al., 2019;Cidral et al., 2018;Quevedo, 2011;Sankar, 2018;Selvaraj, 2019;Xie, Durrington, & Yen, 2011;& Yulia, 2020). Diagnosing students' needs and aptitude is necessary to make virtual learning successful. The decision to fulfill the students' needs is important to prevent social inequality among students (Eickelmann & Gerick, 2020).
The data relevant to the second research question indicate the correlation between the students' motivation and virtual learning. Table 6 lists the correlation value found between students' motivation and the virtual learning model. The correlations imply the ability to predict the value of students' motivational value based on another. The significance value (p-value) is the probability of error in the correlation. At most, the 5% probability of error is accepted to consider a correlation significant. With Table 6, the researcher can find a significant correlation at 0,01 (1%) and 0,05 (5%) of the significant level. The df value is obtained from the following formula; df= n -K (n-3). N represents the number of samples, while K represents the number of independent variables. With n sample amount 202, and three independent variables are used in this research, the df equals 199. So, based on the table 3 r-table is 0,1164 (5%), and 0,164 (1%). If the r-correlation higher than r-table (r-correlation > r-table), it means the correlation is significant, however, if the r-correlation less than r-table (r-correlation<r-table), the correlation is not significant.
The rate of Pearson's correlation between the dimension of students' motivation and the dimensions of virtual learning yields a positive correlation with p (value) ≤ 0,01 (0,000 ≤ 0,01). Sign** on SPSS calculation means that it is significant at the 0,01 (1%) level, which implies the confidence level is 99%. If p ≤ 0,01, it means that the null hypothesis (Ho) is rejected and the alternative hypothesis (Ha) is accepted (Invokavit, 2017). Based on the r correlation and r-table, the correlation of students' motivation and virtual learning mode show 0,282 > 0,164 (r correlation > r table) at the 1% level of significant. The result shows that the correlation between students' motivation and virtual learning is significant.
In line with Pearson's correlation formula on the correlation between students' motivation and Covid-19 pandemic, Covid-19 pandemic shows the level of significant 0,05 (5%). Sign* on Table 7 calculation means that is significant at 0,05 (5%) level, which shows the confidence level of 95%. The result of statistical analysis on this dimension indicates the data (p-value) ≤ 0,05 (0,382 ≥ 0,05) and the Pearson's correlation of r correlation and r table shows 0,062 < 0,116 (r-correlation > r-table) at the 5% level of significant. It can be concluded that the dimension of student motivation and Covid-19 pandemic has no significant correlation. Thus, only the correlation between students' motivation and the virtual learning model has a significant correlation. It is supported by Harandi's (2015) research that says there is a relationship between students' motivation and virtual learning in higher-level education.
Regarding the previous finding that investigates students' motivation when they participate in the virtual learning model during the Covid-19 pandemic, the result also presents an insignificant correlation between them. It is worth discussing that the value is achieved through the data analysis that there is a significant correlation found between students' motivation and virtual learning, but students' motivation and the situation of the Covid-19 pandemic has no correlation.
These levels of Pearson's correlation are shown to be appropriate, especially in the extent of the online class. It is given that the characteristics of these virtual learning inside the educational environment require higher involvement and autonomy of students' motivation in their learning (Beluce & Oliveira, 2015;Filcher & Miller, 2000;Strike, 2018). It is direct evidence that the outcome of the education system is the crucial factor that discovers the quality of end-users from the educational product or called the platform of virtual learning (Elumalai et al., 2020). Virtual learning, or in Indonesia called the online class (kelas daring), has an extensive correlation with building students' motivation for acquiring English through the instructional process. Based on previous research, Adnan and Anwar (2020) have stated that online classes cannot produce the desired result in undeveloped countries, where a vast majority of students have difficulties in accessing the internet. This case has indirectly occurred in Indonesia. Not a few students have difficulties accessing virtual learning models using internet access due to social-economic power.
The problems of virtual learning in the midst of the Covid-19 pandemic have spotted the teachers' inability to access technology, definite school facilities, the difficulties in explaining the material virtually, the limitation of internet access for students, students' economic background, and the patented support system. It is proven on several research by Allo (2020) and Lestiyanawati and Widyantoro (2020). The scholars who understand virtual learning know it has significant challenges for support teamwork, i.e., the students, teachers, and parents (Bond et al., 2018;Jones & Sharma, 2020;Liao, Chen, & Shih, 2019). Furthermore, the stronger need for an education system midst the Covid-19 pandemic is the fastest adaptation of new instructional models and strategies in the teaching-learning process (Toquero, 2020). Therefore, it may be expected that the government is more concerned with technical problems experienced by the students during the Covid-19 pandemic.

CONCLUSIONS
Regarding the result that is investigated, the student's motivation to learn English, the virtual learning model, and the urgent situation of the Covid-19 pandemic are presented on the data finding and discussion. It can be concluded that from 202 participants consisting of 146 female students and 56 male students, the age group with the highest degree of interest in the government's virtual learning platform is the junior high school group. This research has reported some important findings of students' motivation types with percentage and required detail to the frequency, mean, maximum, minimum score, and standard deviation of dimension investigated. The data readily process from the result of respondents' G-form survey around five months in 2020.
The suitable indicators to emphasize the results found from the analysis which ascertain a low category of students' motivation are instrumental motivation and integral motivation. The result also proves with some previous research that the superiority of instrumental motivation over integral motivation. The students require to acquire English on virtual learning is primarily used to attain students' assignment and accomplish the optimal score in English subject. The second research question statistical calculation reveals that there is a correlation between the students' motivation and virtual learning activity as shown by the level of significance 0,000 < 0,05 with Pearson's correlation of r-correlation and r-table (0,282 > 0,164) at the level sig. 1%. It is noteworthy that such a result is predicted the quality of the virtual learning model that can improve students' motivation to acquire English, especially in the Covid-19 pandemic. However, there is no correlation between the students' motivation and the urgent issue of the Covid-19 pandemic as depicted by Pearson's correlation of 0,062 with the significant level of 0,382 > 0,05.
The previous explanation shows that the results imply identifying the motivational contribution of students' motivation to acquire English midst Covid-19 pandemic. The researcher suggests that teachers and parents may have intensive attention to educational systems during Covid-19 included making up suitable virtual learning for students to acquire English appropriate for their real condition. The government also should to take more concern in technical problems experienced by the students during Covid-19 pandemic. In this perspective, the students still have difficulties with virtual learning, such as trouble accessing the online class and the level of students' motivation implied in a low level. The researcher considers the investigation of instrumental motivation and integral motivation that future studies should seek more qualitatively and give more contribution to the educational development system in an urgent situation. I n P r e s s