Exploring Motivation for Learning Through Aldefer’s Theory

The objective of this study is to explore and analyse the learning motivation by the postgraduate students in the Faculty of Administrative Science and Policy Studies (FSPPP), UiTM using Alderfer’s Theory. The study evaluates in detail the existence, relatedness and growth factors which influence learning motivation. The study uses a survey approach as a research instrument to collect data. The survey consists of a set of questionnaires and was administered using an online platform which was shared to all postgraduate students of full-time and part-time mode. A total of 72 respondents responded to the survey. The results indicate that for existence factors between intrinsic and extrinsic motivation, extrinsic factors show higher mean than intrinsic factor. The findings for relatedness factors reveal that the item control beliefs for learning scored higher mean and the results for growth factors reveal that all items scored a moderate mean level.


Background of Study
What motivate a person to learn varies from one person to another person.Lin, Chen and Liu (2017) viewed learning motivation as a learner's individual opinions about affairs, and learners would present different knowledge acquisition needs because of distinct opinions.Koff & Mullis (2011) regarded learning motivation as student intention or desire to participate in and make efforts on learning, which was performed on student choice of specific learning activity and the efforts on such activity.Learning motivation may derive from several reasons Block et al (2013) believed that learning motivation could be guided by both intrinsic and extrinsic factors.This is agreed by Lin et al (2017) that both intrinsic and extrinsic motivation complement each other.A person starts learning from a young age and normally experiences several tiers of learning levels namely primary, secondary and tertiary.Some even would pursue a higher degree like the postgraduate level.What makes one pursue to a higher degree level drives from various motives.Learning motivation according to Karim (2012) is regarded as inherent belief such as to guide one's goal, cause continuous efforts in learning, reinforce cognition history and improve learning outcomes.Looking into the aspect of one's goal, the motivation to learn sometimes is not necessarily driven from the external factors but it is the need for self-growth.Lin et al (2017) believed that this is a good internalization motivation as this type of learners do not need an extrinsic factor such as incentives to force or drive them to learn.Therefore, learning motivation is defined, in this study, as students' desire and effort to continue learning guided by clear learning outcomes.This study will be focusing on learning motivation among postgraduate students of UiTM, specifically on the FSPPP master's degree students.

The Issues of Motivation
Motivation has a positive connotation in various aspects including learning.It is also broadly recognised as a significant factor which influences learning.Salili and Hoosan (2007) were of the opinion that education which respects diversity creates an inclusive safe environment and engages student motivation to learn.This can be analysed that a learner who sees that their cultural identity is being given a big concern may succeed in their educational goal.Motivation is the result of a person building personal needs, interests and emotions, goals and objectives and the presence of motives Khaydarova et al (2020) at achieving their goals.In the case of learning new technology or a new subject as an example, it may become an issue in the beginning of the lesson.However, if a person is able to build up strong interests, determine goals to be achieved, the issue of low motivation can be hindered.Another example of motivation issues in learning new subjects, if a student can pile up such a high interest in learning, he or she may easily overcome difficulties, master the material well, and they develop solid speech skills (Khaydarova, et al., 2020).

Statement of Problem
Motivation in learning is a vital factor in enhancing personal growth and quality of life among students for better academic performance (Zalts et al., 2021).It has been shown that students' well-being is a factor that might have an implication on student's learning such as burnout (Wasson et al., 2016), depressed and demotivated.These implications can make the students have slow progress in their achievement.Academic success is closely associated with motivation and achievement of a student (Guterman and Neuman, 2021).The level of achievement among students can be varied according to the performance shown by students in their academic and learning process.According to Sunaidah et al ( 2021), the ability of students in learning is said to be different based on their understanding on the subject.The authors furthered, students' learning levels are different as some need medium, slow and rapid level of understanding through learning.These levels determine the motivation factor among students to success in their academic performance.Demotivating factors such as learning material, learner characteristics and institute environment affect the learning motivation among the students and help to create the awareness to reduce demotivation and facilitate motivation (Juybar & Rahimi, 2021).Motivation impedes academic performance of students and work at all levels such as primary, secondary, college and university level (Talpur et al., 2021).Thus, researchers explore and analyse the learning motivation by evaluating the existence, relatedness and growth factors which influence learning motivation among students.In this perspective, the researchers' interest developed in exploring learning motivation among postgraduates of FSPPP that affected their academic performance.

Objective of the Study and Research Questions
This study is done to answer the following questions; • RQ1-How do existence factors influence learning motivation?• RQ2-How do relatedness factors influence learning motivation?• RQ3-How do growth factors influence learning motivation?

Literature Review
Introduction This section discusses the concepts and theories related to learning motivation and its components.Past studies on each concept used will be deliberated accordingly.

Motivation for Learning
How does Affective factors influence learning motivation?
Existence is one of the components in Elderfer's theory of motivation that is pinned on the vitality of security.It linked with affective factors that feeling safe by fulfilling the basic materials of the human needs, which matched with Maslow's physiological and safety needs (Elujekwute et al., 2021).It mainly referred to the prevention of fear, anxiety, threat, danger and tension.According to Diep et al (2019), a learner would be concerned with physical and technical conditions of learning that help them to be self-directed learners.In online learning, system functionalities and technical support are among the needs that are required by the students to commit in their studies.Hence, learners would develop self-confidence in navigating the online contents of the studies.
Existence or affective is one of the components that is essential for learners' confidence.
According to Choi et al (2020), affective components such as linguistic confidence and egoresilience are vital for the social mobility in learning.It equips the learners with problemsolving skills by mastering reading and writing comprehension.Lehtiniemi and Kapulainen (2021) posit that affective identity held by the learners resemble the readiness to lead.Individuals who have this identity know what their learning objective is and are driven to achieve them.
In the social work field, existence is perceived as incentives to the employees' recognition in the workplace.The internal environment of the organization should establish a fair reward system, with material and spiritual incentives for their contributions (Chaoqun, 2021).By this way, employees feel protected and safe, while it will result in the acquisition of means to sustain life with rewards.Hence, this component is regarded as the most important in ERG Theory (Elujekwute et al., 2021).In similar findings, Elujekwute et al (2021) highlighted that job tenure for employee's growth is an important element for employees' motivation.The failure to entrench this matter would result in regress of affective components.
In another study of 250 volunteering students during their university years, Logeswaran and Muniandy (2019) identified that growth was the main reason for volunteering, while existence and relatedness were less influenced.In this sense, safety is a prevention from feeling anxiety, fear, threat, tension, or stress.Volunteers always think ahead about whether the event they are volunteering would contribute stress to them due to the uncertainties and lack of experience.In this case, the students found that gaining experience on the events was more important than the safety and relatedness where most of their friends were also volunteering.

How does value factors influence learning motivation?
A student Intrinsic Goal Orientation aims toward the completion of academic tasks.It indicates the students' participation in completing tasks is a significant motivation, not the result of the participation itself.Students partake in responsibility for reasons such as challenge, curiosity, and mastery (Pintrich et al., 1991).Most studies observed a significant and positive impact on Intrinsic goal orientation towards learning (Bhattacharya et al., 2016;Eom, 2015;Lee et al., 2014;Stolk & Harari, 2014).
On the other hand, extrinsic Goal Orientation concerns the degree to which students perceive themselves to be participating in a task for reasons such as grades, rewards, performance evaluation of others and competition.Students with high extrinsic goal orientation engage in learning lessons or performing tasks to achieve something in return.While some studies have found a negative relationship between extrinsic goal orientation and students' motivation to learn (Baars & Wijnia, 2018;Bhattacharya et al., 2016), many others found the opposite effect.Studies by Eom (2015); Komarraju & Nadler (2013); Stolk & Harari (2014) show extrinsic goal orientation positively affects students' motivation to study primarily in a selfregulated environment.
A task Value refers to students' evaluation of how interesting, vital, and valuable the task is.
The high task should lead to more involvement in learning.Task value refers to the students' perceptions of the course material regarding interest, importance, and utility (Pintrich et al., 1991).A higher task value associated with an activity will trigger interest and motivation to the students.Studies have indicated a positive and significant link between task value and students' motivation to learn (Baars & Wijnia, 2018;Liu et al., 2014) How does growth factors influence learning motivation?Individual growth develops responsible and autonomous learners.There is a strong link between motivation and self-determination (McCombs, 2015).Supporting student autonomy helps them in developing responsibility and self-motivation for learning.It is imperative for the students to know what is expected of them, how they will be graded and what kind of support is available for them.In supporting autonomous learners, instructors need to be clear about the kinds of choices that are acceptable relative to the learning objectives and provide feedback for the students (McCombs, 2015).
Growth needs describe the intrinsic desire for personal development.These needs align with the other portion of Maslow's esteem-related needs (self-esteem, self-confidence, and achievement) and self-actualization needs (such as morality, creativity, problem-solving, and discovery).According to Alderfer's ERG model, growth relates to self-development, fulfilment and the sense of achieving your potential.Alderfer's ERG model is different from Maslow's hierarchy of needs even though Alderfer based the ERG model on Maslow's.Maslow states that individuals need to satisfy one hierarchy of needs before moving on to another hierarchy.
Alderfer's ERG theory on the other hand states that individuals can be motivated without adhering to the hierarchy as long as all one of the needs is satisfied.In other words, an individual's priorities and motivations may be fluid and can move between the existence, relatedness and growth levels of need over time.They can move upwards, and they can move downwards (Caulton, 2012).
Growth needs involve needs for self-esteem and self-actualization.The need for self-esteem refers to self-productive effects such as the ability to pursue, to seek knowledge, to achieve, to control, to build confidence, to be independent and to feel competent (Yang et al., 2011).Self-actualization refers to self-accomplishments including achieving an individual's goals and developing his or her personality.This clearly shows that it is pertinent for students to be well-informed about the expectations of the subject or even the instructor in order to fulfil their growth needs.Students need to be able to control their class environment, be it physical class or online class in order to increase their motivation for learning.They need to feel that available information for the online course can guide them towards achieving their goals in learning thus increasing their motivation.
Alderfer isolates growth needs' an intrinsic desire for personal development.These include the intrinsic component from Maslow's esteem category and the characteristics included under self-actualization (Neto, 2015).Intrinsic motivation occurs when people are internally motivated to do something because it either brings them pleasure, they think it is important, or they feel that what they are learning is significant.Intrinsic motivation is driven by internal rewards because the students simply enjoy the process of learning.They see learning as an opportunity to explore, learn and actualize their potential.This situation can be applied in order to understand the motivation of the postgraduate students to learn.

What demotivates learners to learn?
Demotivating factors such as lack of self-motivation is one of the sources that can reduce students' motivation toward learning.The study by Al Yousif and Alsuhaibani (2021) was done to investigate demotivating factors among high school EFL students on language learning.The data of the study were collected via two research instruments: a questionnaire and semistructured interviews with students and teachers.A total of 365 Saudi high school EFL students and 18 secondary English language teachers from six public schools participated in the study.The findings revealed that subject-related and teacher-related demotivating factors were the most reported demotivating factors for Saudi high school EFL students.The results also showed that lack of interesting topics, lack of activities for practicing English, overemphasis on grammar, and incompetence of teachers were the most demotivating factors for EFL students toward English learning.
Another study also looked at demotivation was by (Talpur et al., 2021).The study was done to investigate demotivation factors that influenced English language learning of college students.Two hundred (200) college students, 100 male and 100 female students from two colleges participated in this study as potential respondents.Data collection instrument was a survey questionnaire.Findings exhibited that significant differences in terms of 'class material and lack of interest' were recorded in first and second-year college students.However, 'experiences of failure, class environment and class materials' recorded low scores.

What motivates learners to learn?
Motivation is an essential tool in learning.It is an internal state that drives a student to reach desired goals (McShane & Von Glinow, 2010).In earlier learning motivation theory, Gardner and Lambert (1972) identified two main motivations adopted by the students: instrumental and integrative motivations.Instrumental motivation refers to the drive of the students to use learning as capital that assists them in future, such as getting a job, passing the examination or obtaining rewards.On the other hand, integrative motivation is a desire to learn the culture and be part of the people who speak the language (Rifai, 2010).Pintrich and De Groot (1990) suggested a general expectancy-value model of motivation.A survey on 173 seventh-grade from eight and seven English classrooms in South Eastern Michigan identified that there are learning differences in students' motivation, cognitive engagement and self-regulation in class rooms.The model highlighted three critical components to measure motivation.There is expectancy, value, and affective.The expectancy component outlines the student's belief in completing a task given and being accountable for the result.The component could also be driven by instrumental motivation through the offered rewards and by controlling one's performance (Vroom & Deci in Hassan et al., 2021).On the same note, the value component is the students motive by doing the task.In this way, the students understand the objective of their learning, which will lead to mastery.The last component is affective.Affective is the internal set of feelings about the learning.According to Chen et al (2021), students who learn with anxiety scored low proficiency in learning a second language.A survey was undertaken on 441 first-and secondyear Japanese female students from a private university in Japan identified that developing a personality that is happy, full of interest, resilience and grit are vital for L2 students.Students who have self-competence could promote self-efficacy, interest and lowering anxiety, hence it promotes incremental gains in their learning.Thus, building a solid self-concept and selfsystem is vital in learning motivation, either instrumental or integrative motivation.
Affectiveness is one of the motivating factors to students that is related with building interpersonal confidence and relationships with others.In a study of 293 Chinese universities on English language learners' motivation and online self-regulation, Zheng et al (2018) identified that students who have positive illustration on their learning and intrinsic interest in the English culture tend to have better self-regulatory capacity.On the other hand, students who focus on avoiding bad results are recognized to be less motivated in learning.
The study focused on improving the students' visualization of themselves as a student and improving the intrinsic interest in learning the language.
Project based learning such as role play and drama is not only promoting students' confidence but it is a reflection of the whole outcome of the learning.In a study by Sri Sri Mangkorn (2018), project-based learning could promote speaking skills among English as Foreign Language (EFL) learners.23 students were undergone pre-and post-interview identified bolstering their speaking skills and affective factors.It promotes confidence, giving rooms to practice the language and enjoying the learning journey.Thus, project-based learning gives an opportunity to EFL learners to learn the language in a communicative context.
Consistent with the above, motivation could develop learners' self-efficacy, which defines one's existence and promotes one's growth in learning.Ugwuanyi et al (2020) determined that there is a relationship between motivation and self-efficacy in learning Physics, hence contributing to the learners' academic achievement.The research sample of 375 Physics learners from 89 secondary schools in Benue State of Nigeria were taken using learners' motivation and learner self-efficacy scales.The research identified that motivation and selfefficacy are the major determinants of learner performance in the subject.
During the Covid-19 pandemic, teaching and learning have been shifted to online distance learning.Azlan et al ( 2020) undertook a case study in Malaysia on postgraduate medical physics that underwent an e-learning platform.Based on the semi-structured interview with 11 students, they postulated that the preferences were face-to-face and physical teaching.
Although admitting that pre-recorded videos and tutorials helps in their learning, they have difficulties to focus due to the housing environment and limited internet connectivity.Hence, a hybrid learning strategy, which combines face-to-face and e-learning is a new future in learning.

Research Design
In achieving the objective of the study, the quantitative method was adopted.to investigate the motivation for learning among the postgraduate students of FSPPP, UiTM.The study uses the purposive sampling technique as the respondents were identified and confirmed earlier.

Sample
Sample can be defined as the numbers of units to be studied.Students from the three postgraduate programmes under FSPPP were chosen as respondents.Based on the questionnaire posted online through Online Google Survey, only 72 respondents participated in the study.

Instrument
The instrument is a survey adapted from ERG Theory (Alderfer, 1969).The survey consists of four main sections.The main section is the demographic profile which has 9 items.Section A has which measure the Value component consists of 8 items.Section B has 7 items measuring relatedness through Expectancy components while Section C measures the Affective components which has 5 items.Therefore, the total number of items asked in the questionnaire consists of 24 items.A reliability test is done to measure the consistency and validity of the instruments.It is important to conduct this test (George & Mallery, 2003) to ensure that the items are accurately measured.The Cronbach's Alpha result (Figure 1) shows to record 0.844 reliability coefficients.According to Hair et al (2010), the item is reliable when Cronbach's Alpha value is above 0.60.

Method of Data Collection
Questionnaire is used as a tool to collect the primary data in this study from the respondents.The questionnaire consists of four main sections including demographic profile, value, expectancy and growth components was distributed through an online Google Survey form among the postgraduate students of FSPPP UiTM Shah Alam, Sabah and Sarawak campuses.
The questionnaire used the 5-point Likert Scale method.

Method of Data Analysis
In this study, the data was analysed using a software system known as Statistical Package for Social Sciences (SPSS).Cronbach's Alpha reliability coefficient is tested to measure the reliability of the items in the questionnaire.

Findings Demographic Profile
Findings for Demographic Profile In order to obtain the demographic information among the respondents, the frequency distribution analysis focusing on overall percentage is used.The Tables below have the results.4.1 above shows the demographic of gender among respondents.The majority of respondents are male of which 79% of the male postgraduate students take part in the survey.Female postgraduate respondents in total are 21%.4.4 above, majority of respondents are in their second semester with the highest percentage of 35%.This follows by 26% respondents in their third semester, 21% from the first semester, 16% from fourth semester and 1% for both fifth semester and sixth semester.Part-time 57% The Table 4.5 shows that 57%, which is the highest percentage of respondents, are part time students, be it from EMAS, MOCA or MIRAD program.Meanwhile, 43% of respondents are full time students coming from the main three postgraduate programs.4.6 shows the results for respondents from the campuses.The results clearly indicate that Shah Alam campus scores the highest percentage of respondents.In detail, Shah Alam campus constitutes 90% respondents, followed by Sabah 6% and Sarawak 4%.No 44% Among the respondents, there are postgraduate students who are currently employed.Based on the results from Table 4.7, 57% of them are currently working while pursuing their postgraduate study while 44% are not working.Widower 1% The majority of the respondents are single, which is represented by 72%.This figure was followed by married (21%), divorced (6%), and finally, 1% widowed.

MSVCQ2
In the courses of a program like this, I prefer course materials that arouse my curiosity, even if they are difficult to learn.

MSVCQ3
The most satisfying thing for me in this program is trying to understand the content of the courses 4.2 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.

3.5
Table 4.10 shows the findings for the Value component-Intrinsic Goal Orientation on learning motivation.In measuring this, the value of mean must be identified.In having a better understanding on the range of mean whether it is high, moderate or low, the level category by Muslim (2015) is adopted for this study, as stated below.

Mean Value
Type of range

4.4
MSEGQ3 I want to do well in the classes because it is important to show my ability to my family, friends, or others.

4.1
The above table states the findings of the extrinsic goal orientation on learning motivation.Using Muslim (2015) as indicator for mean level, the findings on the mean for MSEGQ1 (getting good grades) which the score is 4.4, MSEGQ2 (improving overall grade point) stated a similar mean range which is 4.4 while MSEQ3 mean score 4.1 (important of doing well in class).The three results indicate that the number is in the range of high-level mean value.
Findings for RQ2 B. EXPECTANCY COMPONENT-7 items (a) STUDENTS 'PERCEPTION OF SELF-EFFICACY (5 items) Table 4.12 Students' Perception of self-Efficacy Mean ECSEQ1 I believe I will receive excellent grades in the classes.
3.8 ECSEQ2 I'm confident I can understand the most complex materials presented by the instructors in the courses.

3.8
ECSEQ3 I'm confident I can do an excellent job on the assignments and tests in this program.
3.9 ECSEQ4 I'm certain I can master the skills being taught in the classes.
3.9 ECSEQ5 Considering the difficulty of the courses, the teachers, and my skills, I think I will do well in the classes.

3.9
Table 4.12 represents findings for the Expectancy component.One sub-component which is students' perception is being measured.Comparing the findings with mean level indicator by Muslim (2015), it shows that the results scored high mean for all five items.in between 3.8 to 3.9.Three items scored mean of 3.9 whereas two items obtained mean 3.8.

(b)
CONTROL BELIEFS FOR LEARNING (2 items)  3.6 ACQ4 I have an uneasy, upset feeling when I take an exam.
3.4 ACQ5 I feel my heart beating fast when I take an exam.

3.7
With reference to Table 4.14, respondents reported that they "feel heart beating when they take an exam" (3.7) because they "thought about the items that they cannot answer" (3.7) in the exam.They also postulate on "the consequences of failing" (3.6).The overthinking of "how poor they are doing in a test compared to other students" (3.5), and "uneasy, upset feeling when taking an exam" (3.4) are the consequences of the affective component on learning motivation.

Conclusion
The study has reported important findings about motivation to learn among the postgraduate students of FSPPP.RO1 measures the existence factors through Value Components.The value components are divided into intrinsic and extrinsic goal orientation.The results show that extrinsic orientation scores higher mean for the three items which are above 4.0.However, one item from the intrinsic orientation on understanding the courses also scores high mean.
In fact, it is higher than one item of extrinsic goal orientation.This indicates that most of the respondents feel that the good grades will make them a better person, thus indirectly making them more motivated and disciplined in learning.This finding corroborates with Zheng et al., (2018) as Zheng clearly stated in his study that students who have positive illustration on their learning and intrinsic interest in the English culture tend to have better self-regulatory capacity.
Findings for RO2 are regarding the Expectancy component.This component which specifically measures students' perception of self-efficacy and control beliefs for learning consists of seven items.Findings show a high mean level achieved by all items.The two items under control beliefs of learning obtained the highest mean score of 4.3 and 4.4.The scores indicate that respondents knew very well that they can perform better in their study provided they study appropriately and try harder to understand the course material.The positive attitude or self-efficacy shown by respondents can be further analysed as the main reason they are motivated to keep learning by taking the postgraduate program.This finding is similar to the Ugwuanyi et al (2020) who determined that there is a relationship between motivation and self-efficacy in learning using learners' motivation and learner self-efficacy scales.The research identified that motivation and self-efficacy are the major determinants of learner performance in the subject.
Findings for RO3 which is measuring the Affective component shows that the results are mostly moderate mean value.Except for two items, they score 3.7, which is a borderline of high mean value.The results indicate that respondents' actions or emotional actions in learning may arise or influence feelings towards motivation to learn at a postgraduate level.For example, one of the questions which scores the lowest mean of 3.4 is about having a feeling of uneasiness and upset when taking an exam.If this kind of anxiety feeling prolongs, that might affect the students' motivation in their learning process.The findings corroborate with Cheng, at al (2021) of which their research findings indicated that students who learn with anxiety scored low proficiency in learning.Therefore affective plays an important role in a person's emotional or behaviour as study at postgraduate level requires one to have a high level of motivation and keep learning.
Considering the results of this study, the following pedagogical implications are proposed: 1) Motivation in learning is important for the students to perform better in their studies.
2) Classes should be well-equipped with technology and with access to internet connection.
3) Faculty can use cooperative and collaborative methods to engage students and enhance their motivation.4) There should be emphasis placed on outcomes of education related to the motivation component.5) Lecturers should be aware of the current education setting and help to create a motivational learning environment for the students by assessing their development frequently.

Suggestion for Future Research
One of the main outcomes of this study is to outline the factors of learning motivation among postgraduate students.Few suggestions were highlighted for future research.Firstly, the insights of this study would provide guidance and direction to the students to be well aware about causes of demotivation prevailing among postgraduate students.This study also will guide the postgraduates to perform better in their studies.This is because motivation in learning helps the students towards personal and professional development in all spheres of life.Moreover, findings of this study pave the way for novice researchers to conduct further research on motivation factors of learners at all levels since little research has been done on this subject so far in the context of FSPPP.

Figure
Figure1-ERG Theory (Source:Alderfer, 1969) Figure 3: Reliability Test take a test, I think about items on other parts of the test I can't answer 3.7 ACQ3 When I take tests I think of the consequences of failing.

Table 4 .
2 represents the findings for demographic profile of age groups among respondents.The majority of respondents are from the age group of 20 to 29 years old which constitute 68% of overall respondents.Second higher percentage of 26% are respondents from age 30 to 39 years old.The age group 40 to 49 years old only contribute 6% to the findings while there are no respondents from the last two categories of age group 50 years and above and 60 years and above.Question 3 relates with the programmes students registered under the faculty.The faculty offers three postgraduate programmes namely Executive Master of Administrative Science (EMAS), Master of Corporate Administration (MOCA) and Master of International Relations and Diplomacy (MIRAD).The frequency distribution analysis for programmes indicates that the frequency distribution of EMAS programme represented the highest number of percentage respondents, 43 or equivalent to 60%, and followed by MOCA (25%) or 18 respondents and MIRAD (15%) or 11 respondents.

Table 4 .
9 shows the results for the percentage of respondents with or without children.Majority, 85% of the respondents have no children.Meanwhile, 15% have at least one child.

Table 4 .
13 listed the findings for sub-component control beliefs for learning.Two items were measured and both scores were 4.3 for the statement of being able to do well in learning if studied appropriately and 4.4 mean value score in responding to the statement of being able to understand the course material well if they try hard in their study.Both scores are high.