Is There a Relationship between Motivational Factors for Online Learning?

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Background of Study
The Covid-19 outbreak has influenced many areas, including our educational system. It has caused face-to-face learning discontinued, and online, blended, asynchronous, synchronous, and technology-aided learning became the norm. It has led the educators to shift direct classroom to virtual classroom. Due to this, online learning has become the most used teaching approach as it is suitable and practical during the pandemic. Online learning is a type of remote education that is made feasible by technology tools utilised by single learners in their own environments (Meşe et al., 2021). Platforms such as Google Meet, Webex, Google Classroom, Zoom and other platforms are the medium used by the educators in their teaching. However, conducting online learning could be a challenge for the educators and learners. There are several issues experienced by them such as the availability of facilities, infrastructure and bad signals (Putra, 2021). These issues have affected learners' motivation to learn online which could be seen through their attendance list and poor participation during online class (Putra, 2021). Several factors could influence learners' participation in classroom and one of it is motivation.
Motivation is the first condition to take on a learning task and is the engine that powers the process. Students can be motivated to learn online if the methods and approach used by the teachers are interesting. Some teachers find that online learning is new and they were not able to use various media or platforms to conduct learning activities online. This has made the teaching and learning process become monotonous (Durriyah & Zuhdi, 2018) and led to students' boredom. As a consequence, it significantly affect students' motivation in learning. In Malaysia, students find that learning using online tools is interactive despite having internet connection problems (Sufian et. al., 2020). The guiding question for the researchers in this study was students' motivation in online learning which was new for all stakeholders. Understanding the factors that have an impact on students' perceptions could also help administrators to make informed decisions about the course and organizational design as well as guide professional development workshops for instructors. Therefore, the present study is to explore learners' perceptions on the expectancy, value and social support as motivation to learning online

Statement of Problem
Prior to Covid-19, learning in schools or universities was mostly done in physical classrooms with some integration of online learning. However, since the outbreak of Covid-19, more online learning classes have been taking place. This is because during the pandemic time, many students did not have the opportunity to attend physical classes. Therefore, online learning allows students to be able to study without having to go to physical class nor are they constrained by a specific time to study. As traditional face to face learning is being reduced and replaced by online learning, students are expected to be able to adapt well to this new change. However, it is found that online learning comes with its own limitations that may affect students' motivation to learn online. It is found that decreased eye health, screen fatigue, lack of campus life were among the drawbacks for students to fully participate in online learning (Istinjo, 2022). There are many studies that have explored the motivation for online learning. It was found that web based learning affected the students' attitude, anxiety level and their motivation to learn (Mahande et al., 2021). The study showed that students' attitude is a crucial factor in influencing their performance in online learning. In addition, this study also revealed that students faced lower levels of anxiety and nervousness while doing online learning. Every learning method has its own positive and negative aspects that would affect the students' motivation to study, hence, it is important that universities to be aware of the positive aspects to be implemented while eliminating the negative aspects from the education process (Istijanto, 2022). The purpose of this paper was to determine the relationship between motivation and online learning. Motivation for online learning was analyzed in terms of expectancy, value, and social support. However, research on the students' motivation to learn online in higher education systems is still in development and therefore wider and more distinctive perspectives are needed to enrich the existing findings (Istinjo, 2022). In conclusion, this study attempts to fill the research gap.

Objective of the Study and Research Questions
This study is done to explore perception of learners on their use of learning strategies. Specifically, this study is done to answer the following questions; • How do learners perceive expectancy as motivation to learning online?
• How do learners perceive value as motivation to learning online?
• How do learners perceive social support as motivation to learning online?
• Is there a relationship between all motivational constructs in online learning?

Literature Review
Disadvantage and Advantages of Learning Online One paragraph The post-COVID-19 pandemic has affected all sectors, including government, business, tourism, health, and education. This has changed how these services were delivered, forcing educators to develop effective online learning strategies for students to keep the learning process on the run. Online learning is a method of distance learning using information technology infrastructures, including the use of digital applications, online learning software, and internet connectivity (Clark et al., 2016;McDonald et al., 2018). Studies have found some advantages or positive effects of online learning. They suggested flexible schedules and convenience, conducive environments, and improving the students' technical skills are some of the advantages of learning online (Shehzadi et al., 2021). Other advantages include the ease of sharing educational materials, effective access to study resources, updated learning materials, and flexibility in time and space (Yuhanna et al., 2020). Despite the advantages offered, some studies mentioned the advantages of learning online such as the struggle with focusing on the screen for long periods as students are easily distracted by social media or other sites. Another major disadvantage of online classes is internet connectivity. A good internet connection with decent speed is needed which without a good internet connection can also be demotivating for students to learn online. Therefore, educators must keep their online learning classes fresh, engaging, and interactive to help students stay focused on the online lesson (Axmedova & Kenjayeya, 2021).

Motivations to Learn Online
Every sector was impacted for more than a year by the COVID-19 pandemic, but education was especially hard hit. This forced educators, instructors, and teachers to set up online teaching and learning measures. Students are required to adopt a new learning process that is built on online learning platforms like Google Meet, Google Classroom, Zoom, and others. Motivation is the term for the wants or needs that guide behaviour toward an objective. (Spielman et al., 2017). According to the research, a student's performance is impacted when their motivation to learn changes (Pgri et al., 2020). This is in line with Vroom's theory. In his theory, Vroom (1964) outlined three elements (Yunos et al., 2021). The learner's expectation is based on their belief that their efforts will result in the desired performance outcome. This expectation is based on the learners' instrumentality or their belief that, if the performance expectation is met, they will obtain the desired result. Finally, valence refers to the specific value that students place on a given outcome. This shows that students' motivations can be heightened if they establish expectations for their learning and it can benefit students more when they also have other factors that support their motivation for learning, such as social support and value-driven beliefs.

Past Studies on Disadvantage and Advantages of Learning Online
Many studies have been conducted in the past on the advantages and disadvantages of online learning. Previous research has shown that online learning can both benefit and harm students. Online learning has been shown to have several benefits or positive effects. A study by Bui (2021) has demonstrated it when he conducted a study examining the pros and cons of 60 first-to senior-year students majoring in English Foreign Language (EFL) whom they encountered while studying online in a group at Van Lang University. The results showed that collaborative virtual learning methods are advantageous in terms of distance and the elimination of time and financial limitations. However, the study also found disadvantages of online learning, including that students have difficulties in interaction and concentration due to technical problems such as weak internet connections and computer skills. Moreover, some distractions, such as social media, a noisy environment, and chatty peers, are negative aspects of online learning. Meanwhile, research done by Zaki (2022) has proven the positive and negative sides of online learning. He conducted a study in Turkey with forty participants, including twenty-four women and sixteen men between the ages of sixteen and twenty-two. The results indicate that financial affordability and flexible schedules each are some of the pros and cons of studying online. Furthermore, easy access to and sharing of resources, individual attention, self-discipline, and self-motivation were other benefits of online learning. However, freedom, time savings, and social interaction had the lowest percentages. Lack of social interaction, health issues, and connection issues each had the highest percentages of disadvantages. In addition, difficulty concentrating, a lack of motivation, easy distraction, a lack of teacher control, and wasted time were the other negative sides of online learning. Another research within the same line and context done by Trang (2022) indicated the advantage of online learning at a university towards 25 English majors from different cohorts. The researcher also randomly selected a participant for the interview based on the students' schedules which shows the advantages are convenience, cost and time savings, and teaching quality. Nonetheless, the study also found the cons of online learning, such as isolation, technical problems, and cheating.)

Past Studies on Motivations to Learn Online
Many studies have been done to investigate the motivation to learn online. A study by Istinjo (2022) was done to explore and compare the approach and avoidance factors in motivating students to study using three different learning methods which are face-to-face learning, online learning, and hybrid learning. Thirty three informants from two universities in Indonesia were interviewed and later the verbatimdata were analyzed using a thematic content analysis to identify motivational factors. He found four motivational factors for faceto-face learning while five motivational factors for online learning. Moreover, all of the positive factors for face to face and online learning can be found in hybrid learning. This study concluded that higher education institution should implement hybrid learning as the best approach for education system post Covid-19.
Another study by Liu and Zainuddin (2021) was done to explore the extrinsic and intrinsic motivational factors that affect accounting students' acceptance behaviour towards the online component of blended learning (OCBL) in the context of COVID-19. A total of 354 accounting students from a Malaysian public university was selected. Questionnaire were distributed and later analysed using confirmatory factor analysis, correlation and regression analysis and an independent sample t-test. The results showed all the motivational factors (perceived ease of use, perceived enjoyment, perceived competence, perceived choice, perceived tension, perceived value, and acceptance behaviour) that were examined can significantly contribute to students' acceptance behaviour towards OCBL except for perceived ease of use. While both of these research had the same limitation which was generalisability, these studies suggested that higher education institutions should expand and implement the use of online learning as this would improve students' acceptance of online learning

Conceptual Framework
Online classes has become a trend post-covid and instructors and students have become accustomed to them. So all learning activities that were done face-to-face are now done online; even group work. Group work online is done to give confidence to students to interact (Rahmat et.al., 2021). Figure 1 shows the conceptual framework of the study. This study is replicated from the study by (Fowler, 2018 Table 2 Reliability of Survey Table 2 shows the reliability of the survey. The analysis shows a Cronbach alpha of .934, thus, revealing a good reliability of the instrument chosen/used. Further analysis using SPSS is done to present findings to answer the research questions for this study.

Findings
Findings for Demographic Profile Q1.Gender Male Female A total of 114 participants responded to the survey completely with a rate of 100%. From the 114 participants, 75% of the respondents were female compared to only 25% were male respondents. Thus, this shows that most of respondent were mainly female as shown in Figure   Q2 Internet Access The respondents were then asked on their internet access as to gather information for their online learning experience. Based on figure 4, a total of 76% mainly responded that they have medium coverage compared to only 16% have strong coverage. In contrast, only 8% of the respondents stated that they have low or weak internet access. Thus, this indirectly might affect their online motivation in learning online.

Findings for Expectancy
This section presents data to answer research question 1-How do learners perceive expectancy as motivation to learning online? In the context of this study, expectancy is measured by (i) self-efficacy, and (ii) control of learning beliefs.
(i) SELF-EFFICACY (ESE) Figure 6 : Mean for Self-Efficacy Figure 6 presents the mean scores for effort Self-Efficacy (ESE). Among the eight items, the mean scores range from 3.3 to 4.2. The highest mean score is obtained from item ESEQ1 with M=4.2. This shows that the respondents held the opinion that learning online requires expectation as a motivator. This is followed by ESEQ5 with M=4.0 where the respondent agrees that they are confident in their ability to complete assignments and tests in an excellent manner. The respondents to items ESEQ2 and ESEQ4 with the lowest mean (M= 3.3) respectively concurred that they can be certain to comprehend the readings' most challenging material and that the respondents are secure in their ability to understand even the most challenging material presented by the instructors ii) CONTROL OF LEARNING BELIEFS (ECB)

Figure 7 : Mean for Control of Learning Beliefs
Based on the data above, the control of learning beliefs that had the highest mean score of 4 was ECBQ3, which is "If I try hard enough, then I'll understand the material presented". This is followed by ECBQ1 and ECBQ2, namely, "If I study in appropriate ways, then I'll be able to learn online" and "It's my own fault if I don't learn the material taught. The least popular mean score is 3.6, which is namely "I don't understand the material presented; it's because I didn't try hard enough" in ECBQ4.

Findings for Value
This section presents data to answer research question 2-How do learners perceive value as motivation to learning online? In the context of this study, value is measured by (i) intrinsic goal orientation, (ii) extrinsic goal orientation, and (iii) task value. ECBQ3If I try hard enough, then I'll understand the material presented.
ECBQ4If I don't understand the material presented, it's because I didn't try hard enough.
(i) Intrinsic Goal Orientation (VI) Figure 8 : Mean for Intrinsic Goal Orientation Figure 8 shows the mean for intrinsic goal orientation. There are four statements in this section. One statement shows a mean of 3.8 while the others show a mean of only 3.5. The statement with the highest mean (3.8) is 'The most satisfying thing for me is trying to understand the content as thoroughly as possible'. On the other hand, the other three statements for intrinsic goal orientation 'I prefer material that really challenges me, so I can learn new things' , 'I prefer material that arouses my curiosity, even if it's difficult to learn' and 'I choose assignments that I can learn from even if they don't guarantee a good grade' only show a mean of 3.5 each.
(ii) Extrinsic Goal Orientation(VE) Figure 9: Mean for External Goal Orientation Based on figure 9, the overall mean scores of extrinsic goal orientation (VE) were gathered from the analysis. The highest mean score was item VEQ1 with a total score of 4.6 is which students feel that getting good grades is the most satisfying aspect of learning online. This is followed by items VEQ2 and VEQ4 with a total score mean of 4.5. It showed that students student wants to improve their overall grade and at the same time want to do well in classes because they want to show their ability to family, friends, employer and others. Thus, getting good grades is the most important item for the respondents external goal orientation for this study.
(iii) Task Value (VT) Figure 10 : Mean for Task value Figure 10 presents the mean scores for Task Value (TV), on how learners perceived value as motivation to learn online. The six items received mean scores that varied from 4.1 to 4.2. VTQ1 had the component with the highest mean of 4.2 which is equally shared with items VTQ2, VTQ4 and VTQ6. These results show that the respondents thought it was important for them to learn the course material in that class, that the course material was useful for them to learn, and that understanding the subject matter was important. They also believed that they would be able to use what they have learned in other courses too. Meanwhile, the lowest mean is 4.1 which is fairly shared by two items, VTQ3 and VTQ4, where the respondents overwhelmingly agreed that they are very interested in the course's subject matter and that they like the course's subject matter as well.

Findings for Social Support
This section presents data to answer research question 3-How do learners perceive social support as motivation to learning online? In the context of this study, social support is measured by (i) social engagement, and (ii) instructor support. VTQ2It is important for me to learn the course material in this class.
VTQ3I am very interested in the content area of this course.
VTQ4I think the course material in this class is useful for me to learn.
VTQ5I like the subject matter of this course.
VTQ6Understanding the subject matter of this course is very important to me.
(i) Social Engagement (SSE) Figure 11 : Mean for Social Engagement Based on the data above, the social engagement that had the highest mean score of 4.2 was SSEQ3I, where the respondents perceived social support as motivation to learn online by enjoying class discussions. This is followed by SSEQ2I, with a mean score of 4, which states that they perceive social support as motivation to learn online by paying attention in class. Finally, the least popular of the social engagement measures is ISSEQ1, with a mean score of 2.5, in which the respondent perceives social support as motivation to learn online by feeling "disconnected" from their teacher and fellow students in classes (ii) Instructor Support (SIS) Figure 12: Mean for Instructor Support Based on the data above, the highest mean for instructor support is 4.3 for the statement 'The instructor provides the guidance I need to be successful in this class'. Next, the statement ' The instructor presents the material in a way that makes it relevant to me' has SISQ2The instructor responds to questions, clearly, completely, and in a timely manner.
SISQ3The instructor's expectations for me in this class are clear.
SISQ4The instructor provides the guidance I need to be successful in this class.
SISQ5The instructor presents the material in a way that makes it relevant to me.
SISQ6In this course, I have the freedom to guide my own learning SISQ7The instructor provides regular feedback that helps me gauge my performance in this class.
the second highest mean (4.2). This is followed by two other statements with a mean of 4.1 each which are 'The instructor's expectations for me in this class are clear' and 'The instructor provides regular feedback that helps me gauge my performance in this class.' Lastly, the statement 'In this course, I have the freedom to guide my own learning' has the lowest mean at only 4.

Findings for Relationship between all Motivational Constructs for Online learning
This section presents data to answer research question 4-Is there a relationship between all motivational constructs in online learning?
To determine if there is a significant association in the mean scores between metacognitive, effort regulation, cognitive, social and affective strategies data is anlaysed using SPSS for correlations. Results are presented separately in table 3, 4, 5 and 6 below. Table 3 Correlation between Expectancy and Value Table 3 shows there is an association between expectancy and value. Correlation analysis shows that there is a high significant association between expectancy and value (r=.687**) and (p=.000). According to Jackson (2015), coefficient is significant at the .05 level and positive correlation is measured on a 0.1 to 1.0 scale. Weak positive correlation would be in the range of 0.1 to 0.3, moderate positive correlation from 0.3 to 0.5, and strong positive correlation from 0.5 to 1.0. This means that there is also a strong positive relationship between expectancy and value. Table 4 Correlation between Expectancy and Social Support Table 4 shows there is an association between expectancy and social support. Correlation analysis shows that there is a moderate significant association between expectancy and social support (r=.448**) and (p=.000). According to Jackson (2015), coefficient is significant at the .05 level and positive correlation is measured on a 0.1 to 1.0 scale. Weak positive correlation would be in the range of 0.1 to 0.3, moderate positive correlation from 0.3 to 0.5, and strong positive correlation from 0.5 to 1.0. This means that there is also a moderate positive relationship between expectancy and social support. Table 5 Correlation between Value and Social Support Table 5 shows there is an association between value and social support. Correlation analysis shows that there is a high significant association between value and social support (r=.603**) and (p=.000). According to Jackson (2015), coefficient is significant at the .05 level and positive correlation is measured on a 0.1 to 1.0 scale. Weak positive correlation would be in the range of 0.1 to 0.3, moderate positive correlation from 0.3 to 0.5, and strong positive correlation from 0.5 to 1.0. This means that there is also a strong positive relationship between value and social support.

Summary of Findings and Discussions
The main goal of this study was to investigate learners' perceptions on the expectancy, value and social support as motivation to learning online. Research question one is to identify how learners perceive expectancy as motivation to learning online. Expectancy refers to the belief of a person who chooses their behaviour based on what they believe would give them the most beneficial outcome. The findings show that learners can do well in online learning. They belief that online learning can help them to understand the lesson if they do their best in classroom.
Meanwhile, research question two is to identify how learners perceive value as motivation to learning online. Value refers to the desirable goal that motivates the person to want to do something. Intrinsic and extrinsic goal are two motivational factors that motivate a person to achieve something. The present study has shown that learners' feel satisfied when they try to understand the content as thoroughly as possible. Some students might have difficulties to understand the content in online learning. This could be due to lack of interaction with the teacher and concentration in classroom (Bui, 2021). Other than that, students can easily distracted with other things such social media and chatty peers due to lack of teacher control in online learning (Zaki, 2022). As they manage to understand the content thoroughl, it will keep them motivated to stay focus in online learning and this has fulfill their intrinsic goal. Learners' extrinsic goal in online learning is when they aim to get good grade. Getting good grade will make the learners feel satisfied with themselves. They will be more motivated to learn.
Learners' perception on the social support as motivation to learning online refers to having people around to refer to in times of need. Online learning is a process where the learner sits alone and far from their teacher. Social support is very much needed in online learning as it will help the learners to have someone to refer to. During online learning, teacher should create group discussion as a form of interaction with the learners. The findings show that students enjoy the class discussion. Students able to communicate with each other during the class discussion and this will motivate them to participate in classroom discussions. Other than group discussion, teachers should help the learners by providing guidance to the students. The findings show that student need support from their teacher in order to be successful in class.
Research question four is to identify the relationship between all motivations constructs in online learning. The findings have shown that all motivation constructs have significant relationship. This indicates that expectancy, value and social support have relationship in online learning. Learners who belief that they can do well in online learning could be due to the social support that they received from teachers and friends. Besides that, their intrinsic and extrinsic goal are the other factors that could motivate them to learn online.

(Pedagogical) Implications and Suggestions for Future Research
The findings of the study have shown that motivation is significant in online learning. Students will be more motivated in online learning if they receive support from other people. There are some pedagogical implications that might be drawn as a result of the present study. First of all, measures should be taken to maximize interaction between teachers and students and within the group of students. Other than that, course content and materials should be engaging and meaningful in order to increase student motivation and learning. Instructional designers and teachers should guide students to learn independently as online courses largely depend on students' determination to continue. Not only that, students need teachers' feedback and encouragement as this will increase their motivation in online learning.
The present study has contributed in terms of teacher's awareness regarding students' needs in a virtual course. Hence, Professional Development activities can be designed to carter student's need in learning and to help the teachers to implement the activities in teaching.
Additionally, dialogic interaction should be sustained among the teachers to help them feel more motivated as well.