ONLINE LEARNING READINESS OF JUNIOR HIGH SCHOOL STUDENTS IN DENPASAR

The Covid-19 pandemic has caused learning to be carried out online. Not all students, however, are ready for online learning. This study aims to examine the level of readiness of eighth-grade students at a junior high school through an explanatory sequential mixed method design consisting of quantitative and qualitative phases. Student readiness for online learning in this study was reviewed from five dimensions: self-directed learning, motivation for learning, computer/internet self-efficacy, learner control, and online communication self-efficacy. The Online Learning Readiness Scale (OLRS) survey proposed by Hung (2010) with a five-point-Likert scale was used to collect quantitative data. The data were analyzed quantitatively, and the level of readiness was measured utilizing the e-learning readiness assessment model suggested by Aydin and Tasci (2005). Follow-up interviews were then held to support the quantitative data. The results showed that the majority of students entered the level of "ready but needs a few improvements". However, there was one item in the dimension of self-directed learning that was included in the level of "not ready needs some work". The implication of this study is the need to encourage students to actively communicate in online learning, especially for shy students.


INTRODUCTION
Covid-19 pandemic has affected all sectors of life, especially after social distancing policies limited the people's physical interaction. It results in the emergence of the petition of work from home to minimize the spread of the Covid-19 virus. All sectors that can work from home are expected to do so, including the education sector (Kementerian Pendidikan dan Kebudayaan, 2020). The teaching learning process should be done online, where the students must learn from home, and teachers teach from home. In online learning, the course is done through web-based learning and textbooks. Besides, the teachers still teach the students via online conferencing systems or email (Cheawjindakarn, Suwannatthachote, & Theeraroungchaisri, 2012). Online learning is learning supported by the internet where the internet provides the learning material including YouTube videos, PowerPoint, e-book, audio, etc. (Jeffrey et al., 2014), as well as the access for the interaction of teachers and students (Bakia, Shear, Toyama, & Lasseter, 2012).
However, a sudden change from face-to-face learning to online learning does not give students time to adjust to online learning, so not all students are ready for online learning. The fact is that online learning is different from face-to-face learning in which face-toface learning allows human psychological contacts in the learning process (Lalima & Dangwal, 2017) and from direct social interaction which is happening in the classroom (Shand & Farrelly, 2017) that helps students to build their knowledge in learning (Hurst, Wallace, & Nixon, 2013). Although online learning has the advantage of providing flexible learning in terms of time and place as long as they are connected to the internet (Lu & Vela, 2015;Luo, Pan, Choi, & Strobel, 2017;Stone, 2018;Vanslambrouck, Zhu, Lombaerts, & Philipsen, 2018), online learning cannot provide a sense of this direct psychological and social interaction.
Curriculum 2013 emphasizes student-centered learning, where students become the center of learning activity and the teacher only acts as a facilitator. Online learning requires students" independence in learning and structured learning materials to easily understand the lesson (Damayanti, Fauzi, & Inayati, 2018). Therefore, the students' readiness to take an online learning class is crucial for the success of online learning. Besides, it is agreed that students" readiness to participate in online learning affects their academic success differently (Gay, 2018). Students" satisfaction and motivation Self-directed learning is a learning in which the students actively set their learning, including planning, monitoring, and evaluating the learning process (Lee, Tsai, Chai, & Koh, 2014). Besides, self-directed learning is a learning where the students or the learners have their own pace in understanding the lesson (Periya & Sebihi, 2017). Students who possess great self-directed learning can plan their tasks, set their learning goals, check their understanding and time (Jansen, Leeuwen, Janssen, Kester, & Kalz, 2017). Moreover, in terms of timemanagement, the students can adapt their time management in face-to-face learning to online learning (Zimmerman & Kulikowich, 2016). Chee, Divaharan, Tan, and Mun (2011) proposed eleven indicators of selfdirected learners, including: (1) identifying, determining, and stating his/her learning goals; (2) identifying learning tasks to reach the learning goals; (3) planning the learning processes; setting the standard for learning goals achievement; managing and monitoring his/her learning; (5) formulating relevant question; (6) investigating the probability in making decisions; (7) managing the time by himself/herself; (8) doing self-reflection by considering the feedback from teachers and peers to reach the goal; (9) applying the knowledge to the context; and (10) utilizing the skills learned to explore the knowledge beyond the curriculum contents. In brief, self-directed learning is needed in online learning because it requires students" independence in learning.
In the same way, motivation also has an important role in learning. Motivation encourages and maintains learning behavior. Hence, understanding learners" motivation is notable (Huang & Hew, 2016). Motivation determines the activeness of students in the learning process. Logically, students who have high motivation to learn will certainly tend to participate in the learning process. In contrast, students who have low motivation have less participation (Widjaja & Chen, 2017). Motivation is divided into two types, intrinsic motivation and extrinsic motivation (Lin, Zhang, & Zheng, 2017;Ryan & Deci, 2000). The basic difference between the two types of motivation is that the source of the motivation itself. Intrinsic motivation comes from inside  (Reiss, 2012;Ryan & Deci, 2000). Cognitive Evaluation Theory (CET) is the variable that influences intrinsic motivation, while external regulation, introjection, identification, and integration are the types of extrinsic motivation (Reiss, 2012).
On the other hand, online learning allows students to control their learning. Learner control gives students their own authority to control the learning instruction, including sequence, pace, flow, amount, and review of the learning instruction (Simsek, 2012). Learner control provides the students the freedom to set their learning, such as their duration to learn or accomplish a particular task. Moreover, learning control is limited to controlling the learning surrounding and increasing the communication happened in the learning process (Taipjutorus, Hansen, & Brown, 2012). Online learning needs good learner control. When using the computer or mobile for learning online, there will be some distractions as students can open other programs such as social media, electronic games, listening to MP3, or access not-relevant web and sources (Taylor, 2002). In brief, online learning requires student independence because students must have good control so they can control their own learning.
Furthermore, online learning requires the student"s ability to use the internet and computer effectively. Therefore, the internet and computer self-efficacy, including students' beliefs about their capabilities in managing and performing online courses, is important (Hsu & Chiu, 2004;Teo & Koh, 2010). Students with high computer/internet self-efficacy will likely make an effort to solve the task by utilizing the internet application (Kim & Glassman, 2013;Teo & Koh, 2010).
On the contrary, low computer/internet self-efficacy students tend to have low performance related to computer and internet activity (Teh, Chong, Yong, & Yew, 2010;Teo & Koh, 2010). Fortunately, students nowadays have been accustomed to technology and the internet to help them in online learning (Hung, Chou, Chen, & Own, 2010).
Communication is also necessary for the learning process, both in face-toface and online learning. Consequently, to be ready to undergo online learning, students should possess online communication capability and a good perception of their online communication. The student"s perception about their capability to communicate and express themselves in an online environment is called online communication selfefficacy (Yılmaz, 2017).
Some studies have been done to explore students' readiness in online learning in higher education settings. Hung, Chou, Chen, and Own (2010) found that the students' readiness was considered high in terms of computer/Internet self-efficacy, motivation for learning, and online communication self-efficacy and was low in terms of learner control and selfdirected learning. On the other hand, Gigdem and Ozturk (2016) found that students" motivation for online learning was higher than their computer/Internet self-efficacy and self-directed learning. It was also found that computer/internet self-efficacy, self-directed learning, and learning motivation were significantly positive relationships with learning achievement. However, only selfdirected learning was found to be the predictor of their achievements, while the other dimensions did not predict the students" achievements.
Furthermore, Kırmızı (2015) revealed that out of the five online readiness dimensions, motivation was the most influential dimension on students" satisfaction while self-directed learning was the most crucial predictor of students" success towards the student satisfaction and success. Another research also indicated significant positive correlations between students" online learning readiness in technical competencies and both types of autonomous motivation (identified and intrinsic motivation). Additionally, the students who had low online learning readiness were likely unmotivated in learning (Bovermann, Weidlich, & Bastiaens, 2018). Additionally, another research revealed that online learning motivation readiness as the most conclusive factor of students" emotional intelligence, followed by self-directed learning, learner control, online communication self-efficacy, and computer/internet self-efficacy (Buzdar, Ali, & Tariq, 2016).
Previous studies were about students' readiness online that were only done in the higher education context. Simultaneously, the impact of Covid-19 has caused online learning to be implemented at all levels, including IJEE (Indonesian Journal of English Education), 7 (2), 2020

177-188
http://journal.uinjkt.ac.id/index.php/ijee | DOI: http://doi.org/10.15408/ijee.v7i2.17773 P-ISSN: 2356-1777, E-ISSN: 2443-0390 | This is an open access article under CC-BY-SA license the middle school level. Furthermore, a preliminary interview was done with an English teacher in SMP Pelangi Dharma Nusantara Denpasar which revealed that at the beginning of online learning, eighth-grade students at SMP Pelangi Dharma Nusantara were not ready to learn via online learning. However, students had to quickly adapt to sudden changes from face-toface learning to online learning. In their implementation, some obstacles often came from students. Students were less motivated to participate in online learning, and students could not complete the assignments.
Accordingly, this study examined the students" readiness, which was seen from the five dimensions, namely selfdirected learning, motivation for online learning, learner control, self-efficacy of the computer and internet use, and selfefficacy of online communication and the level of online readiness. Furthermore, different from the previous studies, which examined the students" readiness for online learning in the higher education setting; this study will explore the students" readiness in a secondary education institution. Therefore, the research questions are formulated as follows: 1. How is the students" readiness for online learning? 2. What is the level of students" readiness for online learning?.

Research design
The study was designed as an explanatory sequential mixed method design. The research was done in two phases: the quantitative phase to collect quantitative data and the qualitative phase to collect the qualitative data to support and elaborate the quantitative data (Creswell, 2012). The online learning readiness survey was conducted for the quantitative phase and interviews were done in the qualitative phase.

Population and sample
The study population was 60 eighth grade students in SMP Pelangi Dharma Nusantara Denpasar in the academic year 2020/2021. There were 2 intact classes with 60 students altogether in the population. Finally, 35 students out of 60 students filled the survey. Besides, there were 4 students from the two classes as the participants for the interview.

Data collection and analysis
The quantitative phase employed an online survey in Google Form to gather the 5 dimensions of online learning readiness as the variables: self- There were eighteen statements in the survey. Three statements were for measuring the students" readiness in terms of Computer/Internet selfefficacy. The statements were about their confidence in performing the basic functions of Microsoft Office programs (MS Word, MS Excel, and MS PowerPoint), knowledge and skills in managing software for online learning, and confidence in using the internet for gathering information. Five statements were used to measure the students" selfdirected learning. The statements included their independence in planning their study, seeking help when facing the learning problems, managing time, setting learning goals, and setting learning performance expectations. Moreover, there were three statements to measure students" online learning control, including their control of their learning progress, their focus on learning, and their control to repeat the learning materials.
On the other hand, four statements were designed to measure motivation, including their motivation for accepting new ideas, motivation to learn, motivation to learn from their mistakes, and motivation to share ideas with others. Additionally, three questions aimed to measure students" online communication self-efficacy. The statements included the students" confidence in using online communication tools, expressing themselves through text, and posting questions in online discussions.
Moreover, the five-point Likerttype scale was employed for the scoring. The scales consist of "Strongly Disagree", "Disagree", "Neutral", "Agree", and "Strongly Agree" (Ary, Jacobs, & Sorensen, 2010). Moreover, the instruments were tried-out before they are used to do the content validation. The question items were validated to ensure readability, reliability, validity, item difficulty, and item discrimination. Moreover, to support the quantitative data, interviews were done to have elaborative answers for the OLRS survey.
The survey data were analyzed in a descriptive quantitative analysis by using SPSS 25 to see the students' online learning readiness. The result of the analysis was then connected to the E-learning assessment model suggested by Aydın and Tasci (2005) to measure the online learning readiness level. The  Moreover, three qualitative analysis procedures proposed by (Miles & Huberman, 1994), namely data reduction, data display, and conclusion drawing/verification, were used to analyze the data qualitatively. The data from interviews were converted into transcription, select, simplified, and selected for the associated answers in data reduction. In the data display, the data were displayed in the finding and discussion section. In conclusion drawing and verification, the data was verified by connecting them with theories and previous research.

FINDINGS AND DISCUSSION
The findings of OLRS (online learning readiness scale) survey showed that the grand mean score was 3.71. It was higher than the expected level of readiness suggested by Aydın and Tasci (2005) in which the students are considered ready for online learning if the mean score is or higher than 3.4. Furthermore, the findings were described in detail according to the five dimensions of online readiness namely, computer/internet self-efficacy, selfdirected learning, learner control, motivation for online learning, selfefficacy of the computer and internet use, and online communication selfefficacy.

Findings on computer/internet selfefficacy
The findings in terms of computer/internet self-efficacy were displayed in Table 1 below. Besides, the students were also confident to use online learning programs. In this case, Google Classroom and WhatsApp Group were used as the online learning platforms. However, at the beginning of the use of google classroom, Student 3 and Student 4 said that they were a bit confused to join the class since it required the class passcode. In terms of the use of the internet, the students felt confident. All students said that surfing on the internet was not a new thing for them. They were already accustomed to that.
Overall, the students were ready in terms of the use of computers and the internet. The students might get accustomed to technology and the internet since they grow up in a technology era that would help them to deal with online learning (Hung, Chou, Chen, & Own, 2010). Accordingly, this high-level of computer and internet self-efficacy would help them to utilize technology and improve their learning performance (Teh, Chong, Yong, & Yew, 2010;Teo & Koh, 2010).

Findings on self-directed learning
Self-directed learning defined student independence in their learning. The findings on self-directed learning were showed in Table 2. From Table 2, it can be concluded that only one item that did not pass the expected level of readiness. The overall mean score was 3.78. Generally, the students were not ready to plan their own learning. It was in the same line with the statement from Student 3 who said: However, the students were quite active in seeking help when they had problems with their learning as the mean score passed the expected mean score (M=3.40). The interview results revealed that when facing a problem, the students seek help from the teacher, the internet, and friends. Student 1 stated: "When I have something I do not understand, I will ask the teacher through WhatsApp group. However, if the teacher does not give a fast response reply, I will search for the answer on the internet. If the internet cannot help too, I will ask my friends." In managing the time, the mean score of the survey passed the expected mean score. It showed that students generally did not have any problem with it. The interview showed that Student 1, Student 2, Student 3, and Student 4 did not have any problems in managing school time through online learning and time to do house chores. The students did not have problems managing their time in online learning. This was because the students transfer their time management skills from traditional learning to online learning, so it is not difficult for students to manage their time (Zimmerman & Kulikowich, 2016). Furthermore, in general, the students set their own learning goals as the survey's mean score was higher than the expected mean score of online learning readiness. However, the result of the interview indicated that they did not set their learning goal. Student 1, Student 3, and Student 4 said that they do not set their learning goal by themselves. They only followed the teacher. Meanwhile, Student 2 stated that sometimes she set her learning goals for the topic that she liked.
The result of the survey and the interview revealed that the students had high expectations for their learning. Student 4 stated:

"I have high expectations toward my learning and get disappointed if I cannot reach my expectation."
Regarding the grand score of the self-directed learning dimension, it can be said that the students were ready for online learning. However, if it was seen separately, their readiness in planning their own study still needed improvement. Furthermore, to be considered as high self-directed learning, students should be able to plan their study and set their learning goals, monitor their understanding and time (Jansen, Leeuwen, Janssen, Kester, & Kalz, 2017), and have high expectation toward their learning outcomes (Kırmızı, 2015).

Findings on learner control
Online learning requires selflearning control from the students since the teachers cannot control the students directly. The result of the dimension of learner control was presented in Table  3.  Table 3 displayed that students were ready to face online learning in the dimension of learner control. Moreover, the grand score for this dimension was 3.52. Thus, it could be said that students generally could direct their own learning. Student 3 said: In conclusion, the students had good learner control to ignore the distractions in online learning such as social media, electronic games, MP3 music, and other not relevant sites and materials, by contrast, they remained focus on the learning (Taylor, 2002).
Besides, sometimes, the learning materials were hard to be understood and need to be comprehended repeatedly. Related to this, based on the survey, the students had enough control to repeat the learning materials. The interview result indicated that the students repeated the material when they did not understand it yet. They repeated the materials until they understand.

Findings on motivation for online learning
Motivation is also important as the basis to develop online learning readiness.   Table 4 showed that the all the mean scores of the survey of motivation for online learning passed the expected mean score of online learning readiness (M=3.40) with the overall mean score was 3.81.
The results of the survey displayed that the students were open to new ideas. The interview also resulted in the same. Student 1 said: "If other students have different ideas with me, I will accept it if the ideas accepted by most students." Students also motivated to learn through online learning. Student 2 stated: "I have a high motivation to learn in online learning because I love English. Therefore, I am always motivated to study and try to master the materials." On the other hand, students also learned from their mistakes. The mean score of this item was the two highest scores. It meant that students mostly learned from their mistakes. All student 1, Student 2, Student 3, and Student 4 agreed that they should learn from their mistakes to make improvements. Student 1 stated: "I always learn from my mistakes, so I will not repeat the same mistakes" Students also had a willingness to share their ideas with other students as the mean score for the item was 3.63, higher than the expected mean score. From the interview, Student 4 stated: "I like to share my ideas, especially when it is a group work." In contrast, Student 4 said: "I do not like to share my ideas with others because I am a shy person." Nevertheless, if it was seen from the total mean score of motivation for online learning, it could be concluded that the students possessed high motivation for online learning. Additionally, the mean score was the highest mean score compared with the other four dimensions. The high motivation for online learning would encourage students to actively participate in online learning (Widjaja & Chen, 2017).  Table 5 showed that the grand mean for the online communication self-efficacy dimension was 3.72. The mean score of the first item OCS1 indicated that students already pass the standard of readiness in using online tools (email, discussion) to communicate with others. All Student 1, Student 2, Student 3, and Student 4 agreed that they were good in utilizing the online tools to have effective communication Additionally, students felt confident to use text to express themselves. The mean score was 3.74 and it passed the expected mean score. Moreover, the result from the interview revealed that all Student 1, Student 2, Student 3, and Student 4 were confident to speak through text. They even felt more confident to communicate via text than face-to-face.

Findings on online communication self-efficacy
Related to asking questions in online discussions, the result of the survey showed that the students generally students were ready for asking questions in online discussions. On the contrary, the result of the interview with Student 3 showed that he did not confident to ask questions in online discussion. Student 3 said: "I never asked in an online discussion. I avoid being the center of attention because I am a shy person. If I have questions, I will search them on the internet or ask my friends if I cannot find the answers on the internet." Even though the students were ready in terms of online communication in general, some students might avoid being involved in communication due to their personality.
Overall, if it was sorted, the dimension that had the highest mean score is the motivation dimension for online learning (M = 3. self-efficacy (3.66), and learner control (3.52). A recent study found that the dimension of motivation got the highest mean score. This finding was consistent with Gigdem andOzturk (2016) study andBuzdar, Ali, andTariq (2016). However, Hung, Chou, Chen, and Own (2010) found that computer/internet self-efficacy obtained the highest mean score. Regarding the level of readiness, all the five dimensions were ranged between 3.4 and 4.2 which was considered in the level of "ready but needs a few improvements".

CONCLUSION AND SUGGESTION
This recent study investigated the level of students" online learning readiness according the five dimensions including computer/internet selfefficacy, self-directed learning, learner control, motivation for online learning, self-efficacy of the computer and internet use, and online communication self-efficacy. The result showed that generally, the students were ready for online learning, in which the grand mean score (M=3.71) passed the expected mean score of online learning readiness and was in the level of "ready but needs a few improvements". Specifically, the mean score of each dimension also passed the expected mean score of readiness and in the level of "ready but needs a few improvements". However, one item of self-directed learning dimension related to the plan your own studies was still in the level of "not ready needs some work". Additionally, the dimension of online communication self-efficacy was in the level of "ready but needs a few improvements". This study implied that the improvement was needed to encourage the students to communicate in online learning, especially for shy students.