Investigating Students’ Learning Motivation Based on Value, Expectancy and Affective Components

Students’ Based Expectancy, and Affective Abstract Students’ learning motivation has been affected greatly during the COVID -19 pandemic due to the new challenges posed by the online learning environment. Thus, this study aims to investigate how the value, expectancy, and affective components form students’ learning motivation during this crisis. This quantitative study was conducted by distributing a Likert-scale questionnaire with three main sections: Section A- Value Components (12 items), Section B- Expectancy Components (7 items), and Section C- Affective Components: Test Anxiety (5 items), to students at a public university in Malaysia. The questionnaire was answered by 150 respondents and the data were analysed by using descriptive statistics via IBM SPSS version 28. The findings revealed that the respondents reacted positively in all the three components: Value, Expectancy, and Affective Components. In the Value Components, extrinsic goal orientation received the highest mean scores when compared with intrinsic goal motivation orientation and task value beliefs, while in the Expectancy Components, control beliefs for learning obtaining higher mean scores than students’ perception of self -efficacy. Meanwhile, in Affective Component, the findings demonstrate that the respondents were anxious in taking a test or an exam. Pedagogical implications and future research of the study were also discussed in this paper. the detrimental impact of English language learning demotivation on the language learning outcomes of university students. Participating in the study were 215 second-year undergraduates from two public universities in Balochistan, Pakistan, who had registered in an English programme. A 40-item English language learning demotivation questionnaire was utilised to assess academic resilience (Wagnild, 2009) and personality characteristics (John et al., 1991). Compared to the classroom environment, classroom resources, and class characteristics, the study found that teacher behaviour has a minor effect on students' motivation. Additionally, internal factors negatively impacted learners' motivation and were influenced by external influences. Students lost interest in learning the English language, for instance, due to irrelevant and complex language education resources. For the five qualities of resilience, the results showed that perseverance negatively influenced the six components of language learning. Still, the meaning had a substantial adverse impact on class features and failure experiences. In addition, personal qualities contribute to demotivating elements, indicating that conscientious learners were equipped with self-discipline, productivity, meticulousness, and confidence. The personality trait of openness was found to be associated with instructor behaviours, characteristics of classes, and classroom resources to address potential demotivators, as well as correlating metacognitive the survey and the of the multiple regression revealed that metacognitive self-regulation and cumulative GPA were statistically significant variables to successful course Implications and applications of this study include the importance of and self-regulation and the use of learning strategies in the specific context of learning lower-level Spanish classes.


Introduction
Background of Study Globally, the COVID-19 epidemic has had a significant impact on the educational opportunities of students. During extreme conditions, such as this pandemic, online learning has proven to be a viable alternative to face-to-face learning over the past two years (Ertan & Kocadere, 2022). Students and instructors have been compelled to switch from traditional classrooms to online or distance learning. As a result, they encounter significant obstacles in changing techniques from a focus on face-to-face learning to a technology-mediated online learning environment (Chiu et al., 2021). During this very crucial time period, these newly developing difficulties have never before been noticeable. Consequently, it is necessary and essential for researchers to reflect on and enhance the current methods of online learning and instruction by taking students' motivation to study into account.
Students in Malaysian higher education institutions encounter two key challenges: maintaining concentration and maintaining motivation when they transition from traditional classroom settings to online learning environments (Yong & Thi, 2022). According to Sani (2020), some students have little trouble keeping up with their online courses, but others are finding it tough due to issues including a lack of online support, complicated technical requirements, or simply being uncomfortable learning on their own. Students enrolling in online learning classes for the first time who lack the required resources, such as gadgets and internet access, exacerbate the situation. The three primary concerns are a lack of personal desire or the student's conviction in his or her own abilities, which leads to feelings of loneliness and isolation; the significance of instructor support in communicating with and helping students throughout the rapid adjustment, which would make the move less difficult; and the importance of the location environment, which includes the state of the learning environment (Sani, 2020).

Statement of Problem
The teaching and learning process depends heavily on motivation (Ng et al., 2021). The success of teaching and learning depends on how motivated the students are in the classroom whereby motivational techniques in the classroom would help them become interested in and care about what they learn (Alcivar, 2020). A study on the topic of motivation was conducted by Emda (2018), who focused on the intrinsic and extrinsic motivation that stimulated and equipped students to learn and overcome difficulties. Would it be possible for students to maintain the same level of motivation for studying if the teaching and learning process was carried out entirely online as opposed to face-to-face? Academic motivation is likely to suffer as a result of the difficulties students face due to COVID-19 (Fong, 2022).
Recent studies indicated lower levels of satisfaction with online learning caused by a lack of social connection and lower levels of motivation to study online due to less ideal facilities (Meeter et al., 2020); the difficulties associated with online learning, such as the inability to comprehend the course material, the absence of face-to-face interaction, and technological obstacles such as limited data and an inconsistent internet connection (Chung et al., 2020); and the effect of COVID-19 on tertiary students who reported lower motivation and learning performance in online education due to a lack of infrastructure and social support (Tan, 2020). A study by Lessard and Puhl (2021) discovered that during the pandemic, the most often stated concerns among U.S. secondary students were motivation to focus on schoolwork. Students' academic motivation, which can be understood as the process whereby goaldirected (academic) work is prompted and sustained (Schunk, Meece & Pintrich, 2014), is a key factor in students' achievements (Fong et al., 2021;Lazowski & Hulleman, 2016) as well as in their capacity to study independently (Pintrich, 1999). Therefore this study is conducted to investigate students' learning motivation based on these three components: value, expectancy, and affective. The objectives of this study are: • to investigate the value components on students' learning motivation, • to investigate the expectancy components on students' learning motivation, and • to investigate the affective component on students' learning motivation.

Literature Review
Demotivators for Learning Demotivator can be defined as specific external forces that reduce or diminish the motivational basis of a behavioral intention or an ongoing action (Dornyei & Ushioda, 2011, p. 143). Similarly, Gokuladas & SK (2020) defined demotivators as those factors that could potentially influence individuals negatively. Conceptually similar to motivators which help individuals to perform better, there could also be demotivators that hinder such development. Sato et. al (2022) operationally define factors that affect motivation negatively as demotivators, and these factors can be categorised into situational-and individual-specific factors. Li & Zhou (2017) defined demotivation as a phenomenon of lack of motivation to as a result of both external and internal factors. It was mentioned that earlier on, Dornyei (2001) interpreted demotivation as the external force, which may make people reduce or lose a certain behavior tendency or the conduct of behavior. However, Li & Zhou (2017) highlighted that this definition only focused on the external factors and was criticized for failing to take into account the internal factors.
Comparatively, Gokuladas & SK (2020) categorised demotivators as Intrinsic or Extrinsic. Demotivators play an influential role in the morale, in which the lesser the number of demotivators, be it extrinsic or intrinsic, the greater will be the perceived usefulness and the perceived ease of the matter. Chong et. al (2019) have identified that not only external factors but also internal factors can come into play in demotivating the process, specifically on the context of language learning; which further expanded Dornyei's (2001) interpretation of demotivation. This is also highlighted by Ikeno (2002) in his study which suggested that both internal factors (e.g.: lack of a sense of control) and external ones (e.g. teachers' inability) were the main demotivating factors. Li & Zhou (2017) in their study on Chinese University Students' Demotivation to Learn English categorized demotivators into internal and external factors; and some examples of these factors are unclear study goal and experience of failure as well as teaching facilities, process and content respectively. With relation to this, Sakai & Kikuchi (2009) revealed that experience of failure has been the most strongly demotivating factor, similar to the results drawn from the study of . It is also suggested by Kikuchi (2017) that each type of learner experienced unique motivators and demotivators in/outside of the classroom and reacted differently.
Eddy-U (2015) identified themes such as interest, perceived effectiveness, good groupmates, good classroom social situation, personal vision and self-confidence as both motivators and in contrast, demotivators, when in inverse form or absent. From the perspective of online learning, Aikina & Bolsunovskaya (2020) revealed a set of factors concerning pedagogical, technical, management approaches; in which these can be both motivators and demotivators. As challenging as it can be, the effects of demotivators can be transformed otherwise. Experienced teachers, especially those who held intrinsic motivation to teach, channeled the impact of demotivators, including those relating to the pandemic, to a positive motivational force to teach (Sato et. al., 2022).
Aside from that, as demotivator is concerned, Cankaya (2018) contended that it is an understudied area, and is a relatively new issue for researchers. It is also mentioned by Haryanto et.al (2018) that lack of data has been found on the factors that cause student demotivation as compared to students' motivation and teachers' motivation.

Motivators for Learning
During the COVID-19 pandemic, most educational institutions changed to remote learning. It is without a doubt that students' affective and motivation levels are more crucial during this time compared to normal school times. When there is no teacher present, students are responsible for regulating their learning process. Therefore, self-regulated learning and motivational components are assumed to influence students' learning process.
The phrase "self-regulated learning" first appeared in the 1980s as a result of the greater emphasis on self-regulation in academic contexts (Dinsmore et al., 2008). Motivation and selfregulation are intimately connected (Zimmerman and Schunk, 2001;. These researchers define self-regulated students as individuals that actively engage in their learning processes and pursuit of their objectives in a metacognitive, motivational, and behavioural manner. Motivation is a word derived from the word 'motive'. As the name implies, motivation is what "moves" us to achieve the motives such as needs, desires, or wants. It is the driving force behind everything we do. Motivation plays a significant role in the teaching and learning process (Filgona et al., 2020). Motivating students helps them achieve their learning objectives. It is critical to understand that encouraging learning is a key component of effective education. This suggests that the most crucial aspect of learning is probably the learners' motivation.
According to the Self-determination Theory (SDT) pinned by (Ryan & Deci, 2000), learners may be driven to learn by two sources: internal and external. Generally, there are two types of motivation: intrinsic and extrinsic motivation. Extrinsic motivation is a type of reinforcement that can boost students' performance. For students with a low level of motivation, a dose of extrinsic incentives may increase their enthusiasm and at the same time promote positive behaviours towards learning (Hamdi Serin, 2018). For example, study hard for the sake of getting good grades.
Meanwhile, intrinsic motivation is doing something because it's naturally intriguing (Ryan & Deci, 2000). Learners' intrinsic motivation rises when they collaborate in the classroom because their self-confidence grows. Additionally, they become more optimistic about the material they are studying, respect one another more, and are more open to hearing other people's perspectives. For example, participating in sports because it is fun and enjoyable rather than for the sake of winning medals.
Both intrinsic and extrinsic motivation inspire students to participate in the educational process. While some students can develop a drive to study on their own because they are intrinsically motivated, some students require outside rewards to push them since they are not passionate about learning.
Another process theory related to motivation is the Expectancy Theory as proposed by Vroom (1964). Expectancy theory is mainly concerned with the cognitive antecedents that contribute to motivation and how they interact with one another. That is, expectancy theory is a cognitive process explanation of motivation based on the premise that individuals believe there are correlations between their effort at work, their performance as a result of that effort, and the rewards they receive as a result of their effort and performance (Lunenburg, 2011). In other words, individuals will be motivated if they feel that putting in a lot of effort would lead to good results, and good results will lead to the desired rewards. Vroom (1964) developed the first expectation theory with direct applicability to work settings, which was later broadened and modified by Porter and Lawler (1968) and others.

Past Studies Past Studies for Demotivators for Learning
Prior to this study, several studies addressed the demotivators that affect the learning performance outcomes of students. Xie (2020), for instance, did a study to analyse the demotivators that inhibit high performance among Chinese students and to determine the implications of these elements for future teaching. Based on the qualitative and quantitative methods of a questionnaire survey, 588 responses were obtained from students at a Beijing municipal institution. The results were subsequently analysed using SPSS. The results identified seven demotivating elements: teacher-related competency, learner level, teaching topic and materials, insufficient educational facilities and unjust judgement, grammartranslation teaching style, lack of purpose in foreign language learning, and test pressure. Teacher-related and learner-related problems were comparable to those in other nations. However, teaching content and materials, inadequate school facilities, testing pressure, and grading systems were more prevalent in countries such as Korea and Japan. In addition, students reported feeling demotivated because they lacked control over their actions, such as spending too much time playing video games and lazing around. The findings also revealed different motivations for learning a foreign language in China compared to the West. For example, the perception that learning a foreign language can result in higher social status and a quicker emergence into the world contributed to the demotivation of language learners. Overall, the study indicates the significance of enhancing teacher competence. In addition to motivating to increase academic performance, it is necessary to assist students in overcoming their weaknesses.
Moreover, Pathan et al (2020) investigated the detrimental impact of English language learning demotivation on the language learning outcomes of university students. Participating in the study were 215 second-year undergraduates from two public universities in Balochistan, Pakistan, who had registered in an English programme. A 40-item English language learning demotivation questionnaire was utilised to assess academic resilience (Wagnild, 2009) and personality characteristics (John et al., 1991). Compared to the classroom environment, classroom resources, and class characteristics, the study found that teacher behaviour has a minor effect on students' motivation. Additionally, internal factors negatively impacted learners' motivation and were influenced by external influences. Students lost interest in learning the English language, for instance, due to irrelevant and complex language education resources. For the five qualities of resilience, the results showed that perseverance negatively influenced the six components of language learning. Still, the meaning had a substantial adverse impact on class features and failure experiences. In addition, personal qualities contribute to demotivating elements, indicating that conscientious learners were equipped with self-discipline, productivity, meticulousness, and confidence. The personality trait of openness was found to be associated with instructor behaviours, characteristics of classes, and classroom resources to address potential demotivators, as well as correlating with pragmatic ability. The largest association was shown between diligence and persistence as demotivating variables in English learning. The study confirms the prevalence of demotivating influences in EFL learning among university students in Pakistan. In addition to positive reinforcement, teachers must employ motivational teaching tactics and make learning fun if they want students to learn from their mistakes.
In relation to the demotivational study, Mahmud (2019) attempted to determine the most significant factors that discourage English language learning among ESL diploma students at Universiti Sultan Azlan Shah (USAS). The purpose of the study was to improve the condition of undergraduate students and indirectly contribute to their issues, notably in English language acquisition. This study collected data using a questionnaire with twenty items drawn from (Sakai and Kikuchi, 2009). Course book, inadequate school amenities, test results, noncommunicative methods, instructors' competency and teaching styles, and social were the six factors derived from the research. It was determined that the non-communicative form was the most influential factor in demotivating students, with grammatical emphasis and teaching methods being the primary difficulties. Teachers' expertise and teaching methods were the weakest demotivating components, consistent with the findings of Pathan (2020) that teachers were not the primary contributors. The study provides fresh insight into the evolution of the new teaching method. The results can serve as a guide for the university and other institutions of higher education to revise their English language policies.

Past Studies for Motivators for Learning
Many studies have been done to investigate the motivation factors in learning. Motivation in this research points to reasons on how students self-regulate the learning process. Purnama et.al (2019) did research on how attracted learners are to studying English. The data from 22 respondents were analysed with a descriptive qualitative method. From the findings, the writers concluded that respondents are highly motivated to learn English as it is an important language that can aid them in many aspects such as to communicate widely with other people. They were also interested in English if the lesson is fun and engaging like games. It is also interesting that respondents resort to self-exploration via the internet when they have problems in learning the subject matter. This study clearly indicates that motivation is crucial in shaping learners' behaviour and achievement in their studies. It can also assissts teachers in planning the ideal teaching strategies according to the students' preference.
Next, the study by Bisonette (2022) also looked at the importance of academic motivation in providing a pathway to simultaneously support student achievement and wellbeing in both online and traditional learning. A total of 236 undergraduate students 18 years of age or older was the sample size of this quantitative comparative study. This study examined if there are differences in any components of academic motivation such as intrinsic and extrinsic motivation by learning environment. The findings indicated that there were no significant differences in the components of academic motivation between online and face-to-face learning environments. The study's practical implications include informing educators and educational organizations on how to approach developing or adopting instructional strategies for various learning environments. In addition, the study by Esparragoza (2021) also examined motivational constructs and metacognitive self-regulation could be significant predictors of academic performance in a remote asynchronous environment. The study investigated whether intrinsic motivation, extrinsic motivation, task value, metacognitive self-regulation, self-efficacy for learning, and cumulative GPA are predictors of student achievement. 168 undergraduates responded to the survey and the result of the multiple regression analysis revealed that self-efficacy, metacognitive self-regulation and cumulative GPA were statistically significant variables to successful course grade. Implications and applications of this study include the importance of motivation and self-regulation and the use of learning strategies in the specific context of learning lower-level Spanish classes.  Figure 1 presents the conceptual framework of the study. This study's framework is adapted from Pintrich's (2000) framework which highlights goal orientation in the research of selfregulated learning.

Value Components
Value Components are comprised of intrinsic goal orientation, extrinsic goal orientation, and task value (Pintrich et al., 1991). The degree to which a student feels herself to be participating in a task for motives such as challenge, curiosity, or mastery is referred to as intrinsic goal orientation. The presence of an intrinsic goal orientation toward an academic task shows that the student's engagement in the task is an end in itself, rather than a means to an end. Meanwhile, extrinsic goal orientation examines the extent to which a student thinks she is engaging in an activity for external factors including grades, prizes, performance, other people's opinions of her, and competition. When extrinsic goal orientation is high, engagement in a learning task is a means to an end. On the other hand, task value varies from goal orientation in that it pertains to the student's assessment of how interesting, important, and valuable the task is ("What do I think of this task?"). A high task value should result in more participation in one's learning.

Expectancy Components
Expectancy Components generally involve students' beliefs that they are able to perform the task and that they are responsible for their own performance (Pintrich & De Groot, 1990). It includes students' beliefs about their ability to perform a task and covers the aspects of selfefficacy and control of learning beliefs. Self-efficacy can be referred to as the reflection on the ability in mastering a task. It also comprises the perception of the ability regarding accomplishment and confidence in completing the task. As for control of learning beliefs, it refers to students' belief that their efforts, in contrast to external factors, will lead to positive outcomes.

Affective Component
Affective Component in this framework is highly related to test anxiety. It is believed that test anxiety consists of two components which are worry/ cognitive component and emotionality component (Pintrich et al., 1991). Worry relates to students' negative thoughts that interfere with performance, whereas emotionality refers to the affective and physiological arousal elements of anxiety. Cognitive concern and performance preoccupation have been identified to be the main causes of performance degradation.

Methodology
This quantitative study is done to investigate students' learning motivation based on these three components: value, expectancy, and affective. 150 participants were purposely chosen from a public university in Malaysia. The instrument (refer to table 1). used is a survey adapted from (Pintrich & De Groot, 1990). Apart from the demographic profile in Part 1., there are 4 other sections. Section A 12 items on value components, section b has 7 items expectancy component, section D has 5 items on affective components.

Findings for Demographic Profile
Figure 2 -Percentage for Gender Figure 2 indicates the percentage for gender distribution of this study. A total of 150 respondents were involved where 86 of them were male. It takes up to 57%, slightly 14% higher than 64 female respondents with 43%.

Findings for Value Components
This section presents data to answer the first research objective (RO1): To investigate the value components on students' learning motivation. MSVCQ2: In the courses of a program like this, I prefer course materials that arouse my curiosity, even if they are difficult to learn.

Part A: Intrinsic Goal Orientation
MSVCQ3: The most satisfying thing for me in this program is trying to understand the content of the courses.
MSVCQ4: When I have the opportunity in this class, I choose course assignments that I can learn from even if they don't guarantee a good grade.

Intrinsic Goal Orientation
Mean Score Figure 4 shows the mean score for the items with intrinsic goal orientation. All items recorded mean scores above 3.5. Item one and two recorded the same mean score (M=3.75) where the respondents seem to prefer challenging class work and course materials. The highest mean recorded for this value component is item three (M= 3.98) which shows the challenge in understanding this program is the most satisfying. The least mean score recorded is on item four (M= 3.61) indicates that the students will grab the opportunity to add value to their body of knowledge even though it does not guarantee a good grade.  Figure 6 shows the mean scores for task values beliefs items. The highest mean score goes to item 5 (M= 4.18) which indicates that understanding the subject matter of the courses is important for the respondents. The least mean score is on item 1 (M=3.69) where the respondents agree that they will be able to transfer what they have learned from one course to other courses in this program.

Findings for Expectancy Components
This section presents data to answer the second research objective (RO2): To investigate the expectancy components on students' learning motivation. Part A: Students' Perception of Self-Efficacy Figure 7: Mean for Students' Perception Of Self Efficacy Figure 7 presents the mean scores recorded for the 5 items in the category of Students' Perception of Self-Efficacy. The mean scores are generally similar with all 5 items scored between 3.51 and 3.69. The item with the highest mean score is on the students' belief on receiving excellent grades in classes, meanwhile the lowest is on their confidence on understanding the most complex materials presented by the instructors in the courses. The other items scored 3.60, 3.63 and 3.67; which are respectively on their confidence on doing an excellent job on the assignments and tests in the program, certainty on mastering the skills being taught in the classes, and their thoughts on doing well in the classes with consideration on the courses' difficulty. ECSEQ5Considering the difficulty of the courses, the teachers, and my skills, I think I will do well in the classes. Both items scored high, with 4.28 mean score recorded for the students' belief on understanding the course material if they try hard enough, and 4.18 mean score recorded for their ability to learn the material in the program's courses if they study in appropriate ways.

Findings for Affective Component
This section presents the findings to answer the third research objective (RO3): To investigate the affective component on students' learning motivation. ECCBQ1If I study in appropriate ways, then I will be able to learn the material in the courses of this program ECCBQ 2If I try hard enough, then I will understand the course materials.

Control Beliefs for Learning
Mean Score Affective Component: Test Anxiety Figure 9: Mean for Affective Component Figure 9 shows the mean scores for the 5 items in Affective Component scale. All items were rated positively by the respondents with 3.84 as the highest mean for the statement that the respondents thought about items on other parts of the test they could not answer when they took a test. Item 4 in this section received the lowest mean, 3.56, whereby the respondents admitted that they had an uneasy, upset feeling when they took an exam. The other items, item 3-when they took tests, they thought of the consequences of failing, received 3.79 mean score, item 1-when they took a test, they thought about how poorly they were doing compared with other students, received 3.78 mean score, and item5-they felt their heart beating fast when they took an exam received 3.68 mean score.

Summary of Findings and Discussion
This paper presents how value, expectancy, and affective components formed students' learning motivation during the online learning in the COVID-19 pandemic. For the first research objective, the respondents reacted positively in the value components, section A, of the questionnaire. However, extrinsic goal orientation received the highest mean scores when compared with intrinsic goal motivation orientation and task value beliefs. A previous study on motivation has shown that extrinsic motivation was the most significant predictor variable of participation intention, which suggests that if participants begin with a higher level of extrinsic motivation, their participation intention will likewise be higher in the future . This finding implies that in the critical moment of learning with many obstacles due to the COVID-19 pandemic, students' extrinsic motivation has been a major factor that keeps them continue learning.
Meanwhile, for the second research objective, the respondents reacted positively in the expectancy components, section B, of the questionnaire. Both students' perception of self-

Control Beliefs for Learning
Mean Score efficacy and control beliefs for learning received positive reaction from the respondents, with control beliefs for learning obtaining higher mean scores than students' perception of selfefficacy. As explained by Lunenburg (2011), individuals perceive relationships between their effort at work, their performance as a result of that effort, and the benefits they obtain as a reward of their effort and performance. Therefore, this finding has highlighted the importance of control of learning beliefs in motivation for learning (Pintrich et al., 1991) which refers to students' belief that their efforts, in contrast to external factors, will lead to positive outcomes.
Finally, for the third objective, the respondents reacted positively in the affective components, section C, of the questionnaire, which demonstrate that they were anxious in taking a test or an exam. The findings in this section are in line with Xie's (2020) finding whereby test pressure was identified as one of the seven demotivating elements that inhibit high performance among Chinese students.
In conclusion, there are three major findings in this study. First, extrinsic goal motivation is an important factor in determining students' learning motivation during a crises, such as COVID-19 pandemic. Second, students' control beliefs for learning can be another important factor in students' motivation for learning. Third, test anxiety can be a demotivating factor that affects students' motivation for learning. The next section will discuss the pedagogical implications for each major finding and suggestions for future research.

Pedagogical Implications and Suggestions for Future Research
Based on the findings, several recommendations can be made in relation to the topic of students' learning motivation. The first recommendation is to consider providing valuable extrinsic motivation as it has been found to be motivating the students to learn in a difficult time such as COVID-19 pandemic. When faced with many obstacles in a learning environment like the absence of electronic gadgets, stable internet connection and face-to-face interaction with instructors and classmates, extrinsic motivation has proven to be a major factor for the students to continue learning. However, instructors must also think about ways to improve the students' intrinsic motivation such as providing engaging activities to elevate students' participation in the lesson embedded with motives such as challenge, curiosity, or mastery (Pintrich et al., 1991). Second, students' effort in learning should be encouraged as their control beliefs for learning are significant in the learning process. Although this is not easy to achieve, if a student believes she has control over her academic performance, she is more likely to implement the necessary changes strategically (Pintrich et al., 1991). Encouraging words and support in the teaching and learning process by the instructors may help the students believe that they can control their own learning and put more effort to achieve their desired outcomes. Third, as test anxiety can be a demotivating factor in the learning process, instructors must think about ways to reduce students' anxiety while taking the test. For example, the instructors can provide steps and strategies to answer each specific question to help the students feel more confident and less anxious during the test.
This study only focuses on the three components of motivation scales without the learning strategies scales in the MSLQ Manual by Pintrich, P. R., & De Groot E. V. (1990). Therefore, future research should also include the learning strategies scales to better understand both the students' learning motivation and learning strategies during the COVID-19 pandemic. The prospect of collecting this data serves as a preparation of what to do and how to execute the teaching and learning process during a difficult time, hence better execution in the future.