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Dang Huu Phuc

ANTECEDENTS OF STUDENT’S INTENTION TO PARTICIPATE IN

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Dang Huu Phuc

ANTECEDENTS OF STUDENT’S INTENTION TO PARTICIPATE IN

EXTRA-CURRICULAR

MASTER OF BUSINESS (Honours)

SUPERVISOR: Prof LE NGUYEN HAU

Ho Chi Minh City – Year 2014

Students of universities, especially University of Economics Ho Chi Minh City, and all my colleagues, my friends for kindly helping me to collect information necessary for the study

Though the author has tried the best to complete the thesis, errors could not be completely avoided Consequently, the author is looking forward to receiving the contributions and comments from respectful lecturers and friends

COMMITMENT

I would like to commit that this thesis, “Antecedents of student’s intention to participate in extra-curricular”, was accomplished based on

my independent and serious research

I certify that any help hand received in preparing this thesis and all the sources that used have been acknowledged

Table 3.2: Rules of Thumb about Cronbach Alpha Coefficient Size 24

Table 4.1: Demographic characteristics 29

Table 4.2: Cronbach alpha coefficients 30

Table 4.3: KMO and Bartlett's Test for independent variables 33

Table 4.4: Total Variance Explained 33

Table 4.5: Rotated Component Matrix for independent variables 34

Table 4.6: KMO and Bartlett's Test for dependent variables 35

Table 4.7: Total Variance Explained for dependent variables 36

Table 4.8: Component Matrix for dependent variables 36

Table 4.9: Correlations 37

Table 4.10: Collinearity Statistics 39

Table 4.11 ANOVA(b) for model 1 41

Table 4.12 Model Summary(b) for model 42

Table 4.13: Coefficients(a) for model 1 42

Table 4.14: The important rank of four independent variables 43

Table 4.15: Model Summary for model 2 43

Table 4.16: Coefficients(a) for model 2 44

Table 4.17: Hypotheses testing result 44

Table 4.18: The result of chow test for Gender 45

Table 4.19: Regression analysis with Gender as moderator 45

Table 4.20: The result of chow test for School Year 46

Table 4.23: Hypotheses testing result for moderator variable 48

Figue 2.1: TRA model 8

Figue 2.2: TAM model 10

Figue 2.3: TPB model 11

Figure 2.4 Research Model 18

Figure 3.1: Research process 22

Figure 4.1: Gender 28

Figure: 4.2: School year 29

Figure 4.3: Working 29

Figure 4.4: Scatterplot 40

Figure 4.5: Histogram 41

CHAPTER 1: INTRODUCTION 2

1.1 Background of the research 2

1.2 Research objectives 4

1.3 Research scope 4

1.4 Structure of the study 5

CHAPTER 2: LITERATURE REVIEW 6

2.1 Extra-curricular activities: 6

2.2 Human behavior theories 7

2.3 Research model and hypothesis 12

CHAPTER 3: RESEARCH METHODOLOGY 19

3.1 Research method 19

3.1.1 Qualitative research 19

3.1.2 Quantitative research 20

3.2 Research process 21

3.3 Research sampling 22

3.3.1 Sample size 22

3.3.2 Selecting the sampling technique 23

3.4 Methods of data analysis 23

3.4.1 Descriptive statistics: 23

3.4.2 Reliability analysis: 24

3.4.3 Factor Analysis (FA): 24

3.4.4 Multiple Linear Regression Analysis: 26

3.4.5 Chow test: 27

CHAPTER 4: DATA ANALYSIS & RESULTS 28

4.1 Descriptions of sample 28

4.2 Measurement scale 30

4.3.2 Assessing the scale measuring intention to take part in extra-curricular activities 35

4.4 Correlation Testing 37

4.5 Multi-Linear Regression Analysis for testing hypotheses 38

4.5.1 Checking regression assumptions 38

4.5.2 Hypotheses testing 41

4.6 Test the effect of Moderating variables 45

CHAPTER 5 CONCLUSIONS AND RECOMMENDATIONS 49

5.1 Conclusion 49

5.2 Recommendations 50

5.3 Academic contributions of the study 52

5.4 Limitations and Future Research: 52

REFERENCES 54

APPENDIX A: THE SCALES FOR REFERENCE 61

APPENDIX B: QUALITATIVE RESEARCH 63

APPENDIX C: THE QUESTIONNAIRE 66

APPENDIX D: RELIABILITY STATISTICS 68

APPENDIX E: EXPLORATORY FACTOR ANALYSIS (EFA) 71

ABSTRACT

This study is conducted to find out which factors affect to students’ intention

to participate in extra-curricular activities basing on theory of planned behavior and

a part of signaling theory In addition, the research also explores the moderating role

of some demographic variables such as Gender, School Year, Working Hence, this study provides a clear picture about the effects between Male and Female; Sophomore and Junior; Working student and Non-working student

The results indicate all independent factors: (1) Attitudes toward curricular (ATT), (2) Subjective norm toward extra-curricular (NORM), (3) Perceived behavioral control (PBC), and (4) Clarity of extra-curricular information (INFO) have significant impact on dependent variable: Intention to participate in extra-curricular (INT) The PBC factor (beta = 0.340) has highest effect on INT while the less one is INFO factor (beta = 0.146) In addition, this research also reveals the relationship between INFO and ATT However, R square of this impact

extra-is small, it extra-is just 0.032 Besides that, through Chow test, “Gender”, “Working” variables also are found that they can be moderator variables while School Year is not good to be considered as moderator variable

The last part of this study also give some recommendation to encourage students to take part in extra-curricular and it also figures out some limitations of this study for further research in this field

CHAPTER 1

INTRODUCTION

The first chapter represents the research approach, background of the study, the objective and the scope of research Finally, this chapter introduces the structure of the thesis

1.1 Background of the research

Since Vietnam jointed to WTO in 2007, the economy of Vietnam has developed rapidly in many industrial fields, especially in trade and service (Thành Luân, 2012) Many companies, corporations have entered to Vietnam market in many forms such as associated companies, affiliated companies, etc Because of many foreign companies operating in Vietnam, many Vietnamese employees have more opportunities to work in these multi-national corporations It affects not only Vietnam economy but also Vietnam labor market According to Ministry of labor – invalids and social affairs, after jointed WTO, the number of career opportunities and employee income have been significant increased In the 5 year-period (2007 – 2011), unemployment rate in urban decreased 0.9% from 5.1% in 2006 to 4.2% in

2011 and the average income per employee has two-fold increase from 1.8 million VND in 2006 to 3.84 million VND in 2011 (Hà Anh, 2012)

Current students are next high quality employee generation of Vietnam Entering to the international labor market gives students many opportunities but it is also bring to them many challenges International jobs require employee not only knowledge but also extended skills However, many students who have just

graduated do not have enough skill to deal with problems in the real work environment, especially communication and workgroup skills Yamashita – brand general director of Tokyo Mitsubishi bank in Ho Chi Minh city stated: It is undeniable that students have knowledge after 4 years in the university but the weakness of them is transferring these knowledge from the theory to practical Whenever there is a problem, these new employees can not solve and afraid to talk with their boss They usually argue and no one take responsibility in discussion, etc These issues show that universities do not pay attention enough in skills for student, especially extra-curricular in university period (Thùy Vinh, 2012)

While it could be argued that time spent in extracurricular activities result in a decrease in time available for schoolwork and thus a decrease in grades, previous literature has found that extracurricular activities can help develop self-esteem, social ties among students, teachers, and parents, and positive educational trajectories as well as low rates of involvement in risky behaviors (Broh, 2002; Dole, 2000; Carns, Carns, Wooten, Jones, et al., 1995) According to Parajes (1997), participating in extra-curricular activities in university period not only have possible effect to student’s study result but also give students opportunities to practice, improve necessary skills for their job in the future for example presentation, communication, working in group, etc The influences of taking part in extra-curricular have been studied many times However, lacking of researches have been conducted to examine what factors affect to participating in extra-curricular, especially in Vietnam It is very important for managers of the university to understand which factors are good indicators for taking part in extra-curricular

When they know clearly these factors, they can apply some suitable methods to encourage student participate in extra-curricular activities Because of the positive relationship between taking part in extra-curricular and the academic result so that the university which has many students taking part in extra-curricular can be high

reputation in both academic and activities Therefore, a research “Antecedents of student’s intention to participate in extra-curricular” will be conducted to

explore these factors in Universities in Vietnam

1.2 Research objectives

The main objectives of the research are:

- To identify antecedents of student’s participation in extra-curricular

- To investigate the moderating effects of “School year”, “gender”, and “job after school” on the relationship between identified factors and decision to participating in extra-curricular

1.3 Research scope

This study confines itself in the investigation of students in the universities in

Ho Chi Minh city, concretely: University of Economics, Open University

Freshmen are new and senior students have to conduct their final thesis so they do not have enough time to enter extra-curricular activities Hence, the subjects

of this study are students who are sophomore, junior in universities

1.4 Structure of the study

In this research, the introduction is expressed in chapter 1 where an overview

of the study is delivered Available literature relates to theory of planned behavior and signaling theory are presented in Chapter 2 where hypotheses and research model are also introduced Chapter 3 provides the research methodology used to resolve the research problem The design for the sample selection and size, research instruments used, procedures followed and the statistical techniques used to analyze the data is also highlighted Chapter 4 focuses on data analysis and the findings that became apparent from the research study The discussion of the results that are obtained in chapter 5 where conclusions are drawn based on the obtained results and the possible practical implications of the research findings The conclusion comes

with some recommendations for further researches

CHAPTER 2 LITERATURE REVIEW

This chapter reviews some theories that are used on this research They are: Theory of planned behavior, and Signaling theory Then, the research model and hypotheses will be proposed

2.1 Extra-curricular Definition:

Student participation in extracurricular activities has been identified as an important aspect of the education experience Review of the extant literature, however, reveals a potentially important gap in this filed That is there is an apparent lack of a generally accepted definition for extra-curricular (Kenneth et al., 2012) In many research, therefore, this concept has commonly been treat as self-explanatory For example, Rubin et al (2002) state, “One intuitive notion is that extracurricular activities are a place where students look to utilize, and perhaps refine and develop, their interpersonal skills.” In addition, when extracurricular is described, it is often in the form of examples For example, Barnett (2007) notes that “…schools encourage students to participate in various extracurricular activities, such as athletics, vocational clubs, student government, newspapers and yearbooks, and special interest groups” Similarly, Bîrzéa et al (2004) describe extracurricular activities “to be part of non-formal curriculum and they range from visits to different settings and institutions, school exchanges, voluntary work, and student organizations to student clubs and projects outside the school They may take place after and during school programmes and both in and out of school

buildings.” Finally, some researchers describe extracurricular activities through the use of synonyms, such as “non-academic endeavors” (Chia, 2005) or “out-of-class experiences” (Nelson et al 2002)

Extra-curricular activities in this study are defined as activities in the academic club, athletic club, and social activities

2.2 Human behavior theories

Explaining human behavior is a difficult task (Ajzen, 1991) However, many researchers also tried to do study in this field in order to get a broad and clear picture about human behavior Studying about intention to take part in extra-curricular can be conducted based on some human behavior theories There are some well-known models to predict the behaviour of human

 Theory of reasoned action (TRA)

The first one is the theory of reasoned action (Ajzen & Fishbein, 1980; Fishbein & Ajzen, 1975) The purpose of this model is to explain human behavior regarding to volition These behaviors must be voluntary, spontaneous, habitual All

of behaviors that are forced, constrained should be excluded in this model The TRA also exclude behaviors that require special skills or resources or must to have some opportunities to act (Liska, 1984) The predictor of the human behavior is intention In the simple form of TRA, there are two components that affect to human behavior: (1) one’s attitude toward performing the behavior (Attitude), and (2) one’s subjective norm related to performing behavior (Subjective norm) The attitude factor can be measured by multiplying the one’s beliefs about the

consequence of performing the behavior (can be considered that the belief strength) and his or her evaluation of these consequences, or the feeling of him or her about whether this result is good or bad (belief evaluation) (Fishbein & Ajzen, 1975) Subjective norm is seen as a combination of one’s perceptions of what important specific referent individuals or group thinks he or she should do and the motivation to comply with these referents In other words, "the person's perception that most people who are important to him or her think he should or should not perform the behavior in question" (Fishbein & Ajzen, 1975)

Figue 2.1: TRA model The theory of reasoned action had been applied in many research in many fields such as: education (Fredricks & Dossett, 1983), smoking (Budd, 1986), seat-belt use (Budd, North, & Spencer, 1984); voting behavior (Netmeyer & Burton, 1990); and several others Overall, this theory has proven a huge picture for understanding the behavior about decision-making According to many researches, approximately 30% of variance in intention seems to be explained by attitudinal factor, while the normative factor has less influence to intention and does not appear to be a stable variance for the interpretation of behavior Intention is essential predictor for

Subjective Norm

behavior Among 12 published studies reviewed show that there is a high relationship between intention and behavior The correlation between two these factors averaged 0.55 (Gaston, 1994)

The limitation of this model is that the behavioral intention in this model is under volitional control, for example the person just think whether he or she will to perform or not This model did not consider non-motivational factors such as available of requisite opportunities and resources (time, money, skill, cooperation and others) However, this model is also a fundamental background for latter models

 Technology acceptance model (TAM)

Technology acceptance model (TAM) was originally proposed by Davis in

1986 Davis developed this model from the Theory of reasoned action (TRA) TAM

is one of the most popular models to predict user’s acceptance of Information Technology and usage in an organizational context Davis suggests that human decision about whether they would use new technology or not can be predicted by Attitude towards using

Davis hypothesize that the attitude toward a system is good indicator for the actual use of human The attitude toward using is influenced by two major factors

such as: Perceived Usefulness and Perceived Ease of Use Perceived usefulness is

defined by Fred Davis as "the degree to which a person believes that using a

particular system would enhance his or her job performance"; and Perceived

ease-of-use is defined as "the degree to which a person believes that using a particular

system would be free from effort"

Figue 2.2: TAM model Many researchers have conducted a number of researches to test TAM such as Selim (2003) investigated TAM with web-based learning; Constance & Naveen (2006) use TAM test about Internet usage, so on However, this model is suitable for technology field, it is not adequate for social activities as extra-curricular in this study

 Theory of Planned Behavior (TPB)

This theory is an extension from Theory of reasoned behavior, which was developed with the same author Azjen introduced this model in 1987 in order to deal with the limitation in the original model TRA As we discussed above, TRA assumed that the intention is affected by motivation factors include attitude toward the behavior and subjective norm It is true but not enough, however, if a human has

a desire to do an activity but he or she can not do that because of lacking of opportunities or capabilities to perform so that he or she will not intent to do Beside motivation factors, therefore, human intention also be affected by non-motivational factors as availability of necessary opportunities and resources (for example: time, money, skills, cooperation of others) These components represent people’s actual

External

Variables

Perceived Usefulness

Perceived Ease of Use

Attitude towards using

Behavioural Intention of Use

Actual System Use

control over the behavior (Azjen, 1991) Therefore the official model of TPB include three factors: (1) Attitude toward the behavior, (2) Subjective norm, and (3) Perceived behavior control Two factors in the beginning are the same to the original model TRA and the last one represents the capability of human to perform

an action is Perceived behavioral control This new factor plays an important part in the theory of planned behavior (Azjen, 1991)

Figue 2.3: TPB model The theory of planned behavior has been applied in many fields in order to understand a number of different behaviors in which people engage Many studies show the evident for the suitable of this theory in predicting the human behavior For example, Ajzen and Driver (1992) apply the TPB in order to predict the leisure intentions and behavior among a group of college students They find evidence that three factors: (1) attitudes toward the behavior, (2) subjective norms, and (3) perceived behavior control are also good predictor for leisure intentions among this group This study also show the relationship between intention and behavior Parker

Behavioral beliefs Evaluation of consequences Normative beliefs Motivation to comply Control beliefs

Perceived power

Attitudes

Subjective norms

Perceived behavioral control

Intention

et al (1992) apply TPB for predicting the response of drivers in some situations such as: drinking and driving; speeding; close following; and overtaking in risky curricular The findings in this study confirm the hypothesis that all of three independent factors affect to the intention

This model is suitable for the study about curricular activities The student intention about whether he or she will participate in extra-curricular activities could

be affect not only by their attitude, by influencing of their relationship such as family, friends, so on but also by their abilities to take part in

2.3 Research model and hypothesis

Base on the foundation theory – TPB, the research model is illustrated as figure 2.1 (page 18) There are three factors that affect to intention to take part in extra-curricular: (1) Attitude toward extra-curricular, (2) Subjective norms toward extra-curricular, and (3) Perceived behavioral control In addition, because of following reason, research model is added one more factor from signaling theory, that is Clarity of extra-curricular information Hence, there are four independent variables that affect on dependent variable in the finally model The detail

discussions are in the next sections

 Attitude toward extra-curricular

According to Azjen (1991), Attitude toward behavior has an effect on intention to perform an action In addition, many conducted studies have figured out this relationship (Budd, 1986; Netmeyer & Burton, 1990)

In this study, attitude toward extra-curricular shows the student’s assessments about the benefits of joining in extra-curricular activities In order to decide whether participate in extra-curricular or not, a student will think about some results from this activity such as get more relationship, knowledge, skills, and so on Hence, if a student thinks that he/she can get benefits from this activity, the student will join in

In addition, the theory of Schwartz also consolidates this relationship This is

suitable with the Self-direction value in Theory of basic human values proposed by

Schwartz (1992, 2005) This value express the selection or evaluation about people, events, actions, so on People will choose to perform the action that help them can control and mastery suitable things to achieve their goals Base on the consequences, people will consider which action is good or bad in order to perform

or avoid

Hypothesis 1: There is a positive relationship between Attitudes toward curricular and Intention to take part in extra-curricular activities

extra- Subjective norm toward extra-curricular

Subjective norm can be considered as social pressure to a person This factor express a person’s feeling about whether other people who are important to this one think that he or she should perform an action or not Azjen (1991) suggested that there is a positive relationship between Subjective norm and Intention In addition,

the Conformity value in Theory of Basic human value also reinforces idea of Azjen

This value describes restrained actions of human to upset or harm others, especially close people such as parents, teachers, and bosses The characters of this value are

self-discipline, obedient, politeness, honoring parents and elders (Schwartz, 2006) Hence, people have tendency to do things that are suitable to social norm, or suitable to opinion of people who are important to them

Linking to this study, a student will take part in extra-curricular if he thinks that his parents, teachers, friends, and other important people to him suppose that he should take part in extra-curricular activities, therefore the following hypothesis will

be considered

Hypothesis 2: There is a positive relationship between Subjective norm toward extra-curricular and Intention to take part in extra-curricular activities

 Perceived behavioral control

The last factor in the theory of planned behavior is Perceived behavioral control It can be considered as person’s capability to perform an action This factor

also resembles a factor in Schwartz’s theory In Theory of Basic human value, Schwartz (1992, 2005) also mentioned a value that is the same to last factor of TPB,

it is Security value This value derive from basic individual and group requirements

(Kluckhohn, 1951; Maslow, 1965), it expresses that people tend to do things that are safe to them, or they can do it easily

Applying to this study, if a student believes that extra-curricular can be performed easily, and he or she has enough condition to take part in extra-curricular such as time, money, transportation, so on, this student will join in

Hypothesis 3: There is a positive relationship between Perceived behavior control and Intention to take part in extra-curricular activities

 Clarity of extra-curricular information

Information affects the decision-making processes used by individuals in households, businesses, and government Individuals make decisions based on public information, which can get freely, and private information, which is available

to some groups of the public (Connelly et al., 2011) However, the information that

the receiver have is not always the same to the sender have Signaling theory is

fundamentally concerned with reducing information asymmetry between two parties (Spence, 2002) It is useful for describing behavior when two parties (individuals or organizations) have access to different information Signaling theory plays an important role in a variety of management literatures such as entrepreneurship, strategic management, and human resource management (Connelly et al., 2011)

There are a variety of studies in this field The review of Connelly et al (2011) has figured out previous findings Chung and Kalnins (2001) showed that more signals increase signaling effectiveness; Signals that are more visible are more effective (Zhang & Wiersema, 2009); Multiple signals (increasing frequency) improves the likelihood of accurate interpretation (Filatotchev & Bishop, 2002); Good signals are observable, irreversible, governed, and credible (Janney & Folta, 2006)

In the research concern with loyalty in Master of Business Administration (MBA) education programs, Tho (2009) had found that signal quality affect to perceived quality The quality of a signal plays an important role to make customers inferences about the signal Hence, the relationship between signal quality about extracurricular activities and the student’s attitude will be tested

There are three parts of a quality signal: (1) clarity, (2) credibility, and (3) consistency (Erdem and Swait, 1998) As the definition of Erdem and Swait, there are three properties of a quality signal In this study, however, the author will test the first component: “clarity factor” The authorities of universities creates extra-curricular programs to give more benefits to their students, not for their own profits

so that the information may not be incredibility In education environment, in addition, the information should right and can be trusted The issue is that whether the university publishes information to each student, or each student can get information easily, or they can understand clearly the information Therefore, the signal quality in this study is considered as clarity of information

If the extracurricular information is clarity, student can get clear information and understand fully the benefit from these activities, therefore it may positive affects to the attitude of student In the current research, the relationship between clarity of extra-curricular information and attitudes toward extra-activities will be tested In addition, this research also find out whether the clarity of extra-curricular information affect to intention to take part in extra-curricular or not If a student receive enough and relevant information about extra-curricular activities, whether

he/she has a positive attitude about these activities, and whether this student decides

to participate with these activities

Hypothesis 4a: There is a positive relationship between clarity of curricular information and Attitudes toward extra-activities

Hypothesis 4b: There is a positive relationship between clarity of curricular information and Intention to take part in extra-curricular activities

extra- Moderating variables

 Gender

There are many studies that have conducted to show the differences between men and women In physical research, for example, Wright et al (2008) find the differences in hemispheres between men and women In psychological study, researchers believe that women are more related with others than men However men are more autonomous and individuated (Chodorov, 1990) According to Gilligan (1982), women pay more attention on care and responsibility while men focus on justice and fairness In addition, Schwartz (2005) points that female is benevolence and universalism while male focus on power and achievement Because of these differences, this study will test the effect of gender on relationship between three factors and intention to participate extra-curricular

H5a: Gender plays the role as moderating variable in research model

 Education

According to Kohn & Schooler (1983), education experiences enhance the intellectual openness, flexibility, and give people a breadth of perspective,

therefore, in different level of education, people will have different way to act In addition, the education has positively relationship with achievement values Schwartz (2006) Hence, students with different year in university could act in different ways of extra-curricular activities The effect of year in university will be tested in this study as mediating variable

H5b: School Year variable plays the role as moderating variable in research model

 Job after school

Students do part-time jobs after school is popular in our current society Some common jobs that students usually do are tutor, waiter/waitress, sale, so on Students can get salary for spending in their student life from these jobs In addition, student can accumulate real experiences and skills However, the students who have to work after school do not have time for other activities In addition, these students may have different attitude comparing to students who have much free time Hence, in this study the effect of job after school will be tested as mediating variable

H5c: Job after school variable plays the role as moderating variable in research model

Intention to participate extra-curricular

Attitudes toward

Clarity of extra-curriculum information

H4b H4a

Job after school H5b

CHAPTER 3

RESEARCH METHODOLOGY

In this chapter, the measurement scales were developed based on the theory in

chapter 2 Besides that, the research methodology of the thesis was discussed

including research method, research process, and research sampling

Qualitative research was mainly conducted through focus groups in order to cover the potential factors, modify the word, and develop the official scale for quantitative research There were 3 groups with 5-6 members in each group The

members in focus group were sophomores and juniors Besides that, the author also conducted 2 in-depth interviews with experts who manage students in the University of Economics Ho Chi Minh city

The main finding in this step was recognition the possible relationship between the Information about extra-curricular activities that student can get and Intention to participate in these activities Besides that, through qualitative research, the author had modified the TPB scale to be suitable with education context in Vietnam The detail was shown in appendix

3.1.2 Quantitative research

Quantitative research was used to test whether the hypotheses were confirmed

or ignored In this stage, quantitative data was collected by using questionnaires

A questionnaire or measuring instrument is a formalized set of questions for obtaining information from respondents (Malhotra, 1996) After qualitative research, draft questionnaire was designed and pilot study was conducted with 60 samples in order to check the scale

The final questionnaire in this study included two main sections The first section was demographic variables (gender, school year, working) and the last section included 17 items for four independent factors and 3 items for a dependent factor Each item was measured on five-point Likert-type scales on which 1 represents “strongly disagree” and 5 represents “strongly agree”

In this study, the scale of TPB were used to modify for measuring four factors: (1) Attitudes toward extra-activities, (2) Subjective norm, (3) Perceived behavioral

control, and (4) Intention Clarity of extra-curricular information was modified from the scale of Tho (2009)

Table 3.1: The official scale Attitudes toward extra-curricular

1 I believe that I can get good activity mark when I take part in extra-curricular

2 I believe that I can learn many good skills when I take part in extra-curricular

3 I believe that I can get many benefits when I take part in extra-curricular

4 I believe that I can expand my social network when I take part in curricular

extra-5 I feel interesting when I take part in extra-curricular

Subjective norm toward extra-curricular

1 My parents would think that I should take part in extra-curricular

2 My teachers would think that I should take part in extra-curricular

3 My classmates would think that I should take part in extra-curricular

4 My best friends would think that I should take part in extra-curricular

Perceived behavioral control

1 I believe that I can perform extra-curricular well

2 I have capability to take part in extra-curricular

3 I have enough resources to take part in extra-curricular

4 I believe that I have enough skills to perform extra-curricular easily

Clarity of extra-curricular information

1 This university provides clear information about extra-curricular activities

2 This university always provides sufficient information about extra-curricular activities

3 I have no trouble to find out the information about extra-curricular activities

4 I have no trouble figuring out what this university is trying to provide for students

Intention to participate in extra-curricular

1 I have intention to take part in extra-curricular

2 I will take part in extra-curricular when I have information

3 I will take part in extra-curricular in next course

3.2 Research process

After reviewing literature, the draft scale was developed This scale would be adjusted in qualitative research with three focus groups and two in-depth interviews

to create the official scale The final questionnaire was sent to students for collecting data Raw data was checked to eliminate unsuitable respondents The final data was test for the Reliability, Discriminant Then, Linear regression was run and moderator effect was tested

3.3 Research sampling

3.3.1 Sample size

According to Hair et al (2003), at least 5 observations should be used to estimate a measurement variable The number of items in this study were 19, so the minimum observations were 20 * 5 = 100 In other to increase the valid of this

scale

Qualitative research (n=3)

Official scale

Cronbach Alpha

Exploratory factor analysis

Linear regression

Moderator effect testing

Figure 3.1: Research process

study, 350 questionnaires were used to collect information and it was expected that

at least 300 questionnaires were suitable

3.3.2 Selecting the sampling technique

Because of time and money barrier, in this study the author based on convenient method for sampling The author sent questionnaires to colleagues and ask them to give their students

3.4 Methods of data analysis

Statistic Package for Social Science (SPSS) software was applied on this study

to analyze and present the result of this research First of all, SPSS software was used to import data Raw data would be imported into spreadsheet of SPSS window Here, data was also coded according to the purpose of study And after that there were some statistical tools to be applied in this study: Descriptive statistic, Reliability analysis, Exploratory Factor Analysis (EFA) to check whether the scales were suitable to analyze in regression step

3.4.1 Descriptive statistics:

Descriptive statistic was actually used to report the characteristics of the data

such as mean, frequency, standard deviations, percentage and range (Sekara, 2006)

In this study, the descriptive statistic was used to consolidate the data to determine the balance of samples about gender, school year, working by checking the frequency and the percentage of each variable This method is useful once comparison between the groups of respondents’ demographic each other

3.4.2 Reliability analysis:

The reliability testing was used to measure the items of the variables in the questionnaires and the internal stability and consistency of a question can be determined by the coefficient value of Croanbach’s alpha (Nunnally & Bernstein, 1994) According to Hair et.al (2003), the Rules of Thumb about Cronbach Alpha Coefficient as follows:

Table 3.2: Rules of Thumb about Cronbach Alpha Coefficient Size

Alpha Coefficient Range (α) Strength of Association

Source: Hair et.al (2007)

In the case of the research concept is totally new or it is conducted in new environment, Cronbach’s Alpha index gains 0.6 is accepted (Trọng & Ngọc, 2008) According to Nunnally & Burnstein (1994), the item has item-total correlation

index lesser than 0.3 would be eliminate

The research about intention to take part in extra-curricular activities base on TPB is new in Vietnam, so that the Cronbach’s Alpha standard to accept the scale and item-total correlation index is 0.6 and 0.3 respectively

3.4.3 Factor Analysis (FA):

Factor Analysis (FA) is a primary method to identify the underlying structure

in data (i.e, determine the correlation among a large number of variables) Factor Analysis refers to the cluster of interdependence technique whereas it summaries

the information from a large number of variables into factors, depending on their relationships (Hair et al, 2007)

EFA is a technique to downsize and summarize the data The EFA method would help to identify the groups of variables necessary for the research problem and find out the interrelationship between variables In the implementation of Exploratory Factor Analysis (EFA), researchers usually pay attention to some criteria as follows:

 Kaiser – Meyer – Olkin (KMO) and Bertlett’s Test: KMO is an indicator used

to evaluate the appropriateness of EFA method with the data If the KMO indicator runs from 0.50 to 1, EFA would be applicable (Kaiser, 1974) Moreover, Bartlett’s Test is used to test the null hypothesis that the variables

in the population correlation matrix are uncorrelated If the observed significance level is lower than 0.05, it is small enough to reject the hypothesis and concluded that the strength of the relationship among variables is strong

It is a good idea to proceed a factor analysis for the data

 Kaiser criterion: this criterion would help to identify factors which are extracted from the scales The less important factors would be eliminated The important factors would be maintained while we look at the Eigenvalues values, which represent the variations that could be explained by each factor Only factors whose Eigenvalues value is equal or bigger than 1 would be kept

in the model (Anderson and Gerbing, 1988)

 Variance explained criteria: the total variance explained should not be lower than 50% (Anderson & Gerbing, 1988)

 To satisfy discriminant validity of the scale: the differences of factor loading values between variables in different factors should be equal or bigger than 0.30 (Jabnoun et al., 2003)

 Factor Loading: According to Hair et al (1998), factor loading is an indicator ensuring practical significance of EFA method If factor loading is equal or bigger than 0.30, it is at minimum level; If factor loading is equal or bigger than 0.40, it is necessary; and if it is equal or bigger than 0.50, it is considered practical significance In addition, Hair et al (1998) advised that if factor loading is equal or bigger than 0.30, the sample size should be at least 350 If the sample size is about 100, we should choose the factor loading is equal or bigger than 0.55 If the sample size is about 50, the factor loading should be equal or bigger than 0.75 So, with 302 items of sample size in this research, if the observed variables having factor loading is equal or smaller than 0.50 would be dismissed

For the unidimensionality scale like the measurement of intention to use in this study, the author would apply principal component analysis together with the Varimax rotation method to reduce the number of variables

3.4.4 Multiple Linear Regression Analysis:

Multiple Linear Regression analysis had been done to examine the simultaneous effects of several independent variables on a dependent variable that is

interval scaled (Cavana et al, 2001) In this study, multiple linear regression analysis was used to know whether all of the independent variables (Attitudes toward extra-curricular activities, Subjective norm toward extra-curricular, Perceived behavioral control, Clarity of extra-curricular information) would significantly add to the variance explained in the dependent variables (Intention to participate in extra-curricular) Besides that, the simple linear regression was used

to test the relationship between Quality of extra-curriculum information and Attitudes toward extra-activities Thus, there were five hypotheses in this study to

be analyzed by using the regression analysis in order to determine of any possible relationship between independent and dependent variables under the context of the study

In summary, this chapter was discussed about research methodology employed

in this study which covered to research framework, sample design, data collection procedures and also discussed about the statistical tools which had been used to analyze the data in this study

CHAPTER 4

DATA ANALYSIS & RESULTS

In this chapter, the remaining items were analyzed to test the hypotheses The content of the Chapter includes: description of sample, assessing the reliability and the validity of scale through Cronbach alpha coefficients and Exploratory Factor Analysis (EFA) method; testing the research model and hypotheses with correlation analysis, multi linear regression analysis, Chow test SPSS software version 16.0 was the tool using for this data analyzing process

4.1 Descriptions of sample

The subjects of this study were students who were sophomore, junior in universities Totally 350 questionnaires were sent to students in the main quantitative study, and there were 304 people replied The data was collected and checked, then 278 answers were found valid for the study The accepted sample was the questionnaire that had all answered items

- Gender : Among the 278 qualified respondents, 137 respondents (49.3%)

were male, and 141 (50.7%) were female

Figure 4.1: Gender

- In terms of educational level: 125 respondents (45%) were sophomores, and

153 respondents (55%) were juniors

Figure: 4.2: School year

- Working: In the research sample, there were 115 students work after school

(41.4%) and 163 students did not have any job (58.6%)

Figure 4.3: Working Table 4.1: Demographic characteristics

School year Gender Job after school

Table 4.2: Cronbach alpha coefficients

Item-Cronbach's Alpha

if Item Deleted Attitudes toward extra-curricular (ATT) : Cronbach alpha = 0.724

extra-items had high Corrected Item-Total Correlation (the least value – ATT1 was 0.414)

so all the items of this scale were accepted

There were 04 items measuring Subjective norm toward extra-curricular

(from NORM1 to NORM4) The Cronbach’s Alpha value was 0.689 and all of the items had high Corrected Item-Total Correlation (the least value – NORM4 was 0.322) However, if NORM4 was deleted, Cronbach’s Alpha value increased to 0.712, so this item would be eliminated in next analysis All of the remaining items

of this scale were accepted

There were 04 items for Perceived behavioral control (from PBC1 to PBC4)

The Cronbach’s Alpha value was 0.812 and all of the items had high Corrected Item-Total Correlation (the least value – PBC4 was 0.452) If PBC4 was deleted, Cronbach’s Alpha value increased to 0.846 However, the increasing was so small

In addition, Corrected Item-Total Correlation of PBC4 was high (0.452 was bigger