SPSS work analysis : 24 hours

“Inferential statistics is a body of methods used to draw conclusions or inferences about characteristics of populations based on sample data” (Keller, 2009, p.3).

“Pearson‟s correlation coefficient is a measure of the correlation between 2 variables (X) independent and (Y) dependent variables, which gives a value between +1 and -1”

( http://en.wikipedia.org/wiki/Pearson_product-moment_correlation_coefficient).

Pearson‟s Correlation Coefficient will be used to examine the scores between the between (X) variables of service quality and (Y) overall student satisfaction of students of Universities in Thailand. The formula of Pearson‟s correlation coefficient is:

å XY -

å X åY

r =

N

æ

( X )2

öæ

(

Y )2

ö

ç

å X 2

-

å

֍

åY 2

-

å

÷

ç

N

֍

N

÷

è

øè

ø

The rule for testing the hypothesis is, if the P-value (significance of correlation) is less than the value of Alpha, the null hypothesis (Ho) will be rejected, which means the alternative hypothesis (Ha) will be accepted.

The strength of correlation coefficient is measured based on r value, shown in table 4.2 below:

43

Table 4.2: Pearson Correlation Coefficient

Correlation (r)

Interpretation

1

Perfect positive liner association

0

No liner association

-1

Perfect negative association

0.09

~

0.99

Very high (very strong) positive correlation

0.70

~

0.89

High (strong) positive correlation

0.4 ~ 0.69

Medium (moderate) positive correlation

0 ~ 0.39

Low (weak) positive correlation

0~ -0.39

Low (weak) negative correlation

-0.40 ~ -0.69

Medium (moderate) negative correlation

-0.70

~ -0.89

High (strong) negative correlation

-0.90

~ -0.99

Very high (very strong) negative correlation

Source: Hussey and Hussey (1997)

Similarly, to test the research questions Analysis of Variance (ANOVA) will be used to determine whether there are differences between 2 or more population means (Keller, 2009).

This chapter discussed about the methodology used for conducting the survey and analysis. The research methods used, target population, sample size, sampling methods, research instruments, data collection procedure, reliability test and how the data would be analyzed were all discussed in detail. A quantitative survey was the method used for this research. Non-probability convenience sampling was utilized to collect the data among graduate students studying in Thailand. Research questions were adopted from the past study of Firdaus (2005), Afal et al. (2009) and Huang (2009). The online questionnaire and hard copies were distributed among graduate students. 200 copies of hard copy questionnaires were distributed but 178 were valid to use, and from the online survey out

44

of 126, 125 were valid to use. Reliability tests of the questionnaire were also conducted to test the consistency of the questionnaire. The collected data was then analyzed using SPSS and hypotheses were tested on the basis of Pearson‟s Coefficient Correlation.

Chapter five discusses about the analysis and results of the collected data in detail. All the collected data are analyzed and the results are evaluated in this chapter.

45

CHAPTER FIVE

PRESENTATION OF DATA AND CRITICAL DISCUSSION OF

RESULTS

This chapter presents the analysis of collected data. The entire data analysis is divided into two parts: Descriptive statistics and inferential statistics. Descriptive and inferential analyses are two statistical techniques used in the data analysis. The program SPSS was used to analyze the collected data.

5.1 Descriptive statistics

Descriptive analysis refers to the transformation of the raw data into a form that will make them easy to understand and interpret (Zikmund, 1999).

The data collected from respondents was analyzed by using the SPSS program to calculate frequency distribution and percentage distribution

5.1.1 Gender

Table 5.1.1: Analysis of gender levels by frequency

Gender

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Male

165

54.5

54.5

54.5

Female

138

45.5

45.5

100.0

Total

303

100.0

100.0

46

Table 5.1.2: Analysis of gender and service quality by variables

Report

Gender

Male

Female

Total

Mean

N

Mean

N

Mean

N

Non academic aspects

3.6776

165

3.6196

138

3.6512

303

Academic aspects

4.0013

165

3.9758

138

3.9897

303

Program issues

3.5000

165

3.4656

138

3.4843

303

Reputation

3.6646

165

3.7343

138

3.6964

303

Access

3.8081

165

3.7585

138

3.7855

303

Group size

3.9838

165

3.9130

138

3.9516

303

Design, delivery, assessment

3.6545

165

3.7493

138

3.6977

303

Overall, I am satisfied with

3.95

165

3.89

138

3.92

303

the university

Table 5.1.1 shows total number of sample size collected was 303 out of which 165 (54.5%) were male respondents and 138 (45.5%) were female respondents. The majority of the participants were male graduate students.

In Table 5.1.2 we can analyze the perception of service quality variables and satisfaction by the gender. Male respondents has scored higher mean in non-academic, academic, program, access and group size where female has score higher in reputation and design, delivery and assessment. Overall, male seems a bit more satisfied with their university compared to female, although this is not statistically significant.

47

5.1.2 Age

Table 5.1.3: Analysis of age levels by frequency

Age Range

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

20-25

123

40.6

40.6

40.6

26-30

137

45.2

45.2

85.8

31-35

29

9.6

9.6

95.4

above 35

14

4.6

4.6

100.0

Total

303

100.0

100.0

Table 5.1.4: Analysis of age range and service quality by variables

Report

Age Range

20-25

26-30

above 30

Total

Mean

N

Mean

N

Mean

N

Mean

N

Non academic aspects

3.7862

123

3.6022

137

3.4209

43

3.6512

303

Academic aspects

4.0614

123

3.8986

137

4.0749

43

3.9897

303

Program issues

3.5691

123

3.4161

137

3.4593

43

3.4843

303

reputation

3.7588

123

3.6302

137

3.7287

43

3.6964

303

Access

3.9377

123

3.7032

137

3.6124

43

3.7855

303

Group size

3.9702

123

3.9440

137

3.9225

43

3.9516

303

Design, delivery,

3.7138

123

3.6628

137

3.7628

43

3.6977

303

assessment

Overall, I am satisfied

3.97

123

3.86

137

4.00

43

3.92

303

with the university

48

Table 5.1.3 is the analysis of age group of the respondents. So, in the above table we see 40.6% (n=123) respondents were between the age group of 20-25 years, 45.2% (n=137) respondents were between the age of 26-30 years, 9.6% (n=29) respondents were in the age group 31-35 years and 4.6% (n=14) respondents were above 30. So, out of 303 sample size most of the graduate students belonged to the age group 26-30 years (45.6%) and in the age group of 20-25 years (40.6%).

In table 5.1.4, we can see the respondents who are among the age group 20-25 tends to have higher mean score in the service quality variables. In this table the group of 30-35 and above 35 was re-coded into group as above 30 using SPSS. The reason was to create more equal sized groups. In terms of overall satisfaction, the age group of 20-25 and above 30 tends to be more satisfied than the respondents who were among the age group of 26-30, although this is not statistically significant.

5.1.3 Tuition Fee Sponsor

Table 5.1.5: Analysis of ethnic group by frequency

Tuition Fee Sponsor

Cumulative

Frequency

Percent

Valid Percent

Percent

Valid Parents/others

186

61.4

61.4

61.4

Self

99

32.7

32.7

94.1

Employer

18

5.9

5.9

100.0

Total

303

100.0

100.0

49

Table5.1.6: Analysis of tuition fee sponsor and service quality by variables in

Report

Tuition Fee Sponsor

Parents/others

Self

Employer

Total

Mean

N

Mean

N

Mean

N

Mean

N

Non academic aspects

3.6624

186

3.6414

99

3.5889

18

3.6512

303

Academic aspects

4.0119

186

3.9327

99

4.0741

18

3.9897

303

Program issues

3.5390

186

3.3460

99

3.6806

18

3.4843

303

reputation

3.7455

186

3.5825

99

3.8148

18

3.6964

303

access

3.7849

186

3.7609

99

3.9259

18

3.7855

303

Group size

4.0108

186

3.8990

99

3.6296

18

3.9516

303

Design, delivery, assessment

3.7108

186

3.6626

99

3.7556

18

3.6977

303

Overall, I am satisfied with the

4.00

186

3.74

99

4.17

18

3.92

303

university

Table 5.1.5 shows who pays the tuition fee of the respondent students for their masters program. 61.4% (n=186) respondent‟s tuition fee were sponsored by their parents or others, 32.7% (n=99) respondent pays by their own, and 5.9% (n=18) respondent‟s fee were paid by their employer. So, most of the respondent‟s tuition fee were sponsored by their parents or by others. Others would possibly be by the government (scholarship).

Table 5.1.6 we can see the respondents who are sponsored by parents or others and by employer tends to score higher means in all the service quality variables and are also more satisfied with their university than the respondents who pay their own tuition fee.

This also answers our research question “does self payment and payment by others influence satisfaction?” The answer for this question is answered in more detail in the inferential statistics section.

50

5.1.4 Ethnic Group

Table 5.1.7: Analysis of tuition fee sponsor by frequency

Ethnic group

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

African

5

1.7

1.7

1.7

Asian

230

75.9

75.9

77.6

European

34

11.2

11.2

88.8

North American

33

10.9

10.9

99.7

Oceania

1

.3

.3

100.0

Total

303

100.0

100.0

Table 5.1.8: Analysis of Ethnic group and service quality by variables

Report

Ethnic group

Design

Non

Academic

Program

delivery

Overall,

academic

aspects

issues

reputation

access

Group size

assessment

satisfaction

Asian

Mean

3.5996

3.9773

3.4837

3.7174

3.7348

3.9377

3.6974

3.92

N

230

230

230

230

230

230

230

230

Non-

Mean

3.8137

4.0289

3.4863

3.6301

3.9452

3.9954

3.6986

3.93

Asian

N

73

73

73

73

73

73

73

73

Total

Mean

3.6512

3.9897

3.4843

3.6964

3.7855

3.9516

3.6977

3.92

N

303

303

303

303

303

303

303

303

Table 5.1.7 shows which ethnic group the respondents belong to. As the research was about the graduate student satisfaction studying in Thailand, it was obvious for Asian students to number more than other ethnic groups. So, the above table shows 1.7% (n=5) students were African, 75.9% (n=230) were Asian, 11.2% (n=34) were European, 10.9% (n=33) were North American, and 0.3% (n=1) was from Oceania.

In Table 5.1.8, ethnic groups like African, European, North American and Oceania were re-coded into single group because the sample of those groups were far less compared to the Asians. To create more equal size group it was re-corded. From the table we can analyze except „reputation‟ in all the other variables, Non-Asian has scored higher mean. Maybe the Non-Asian has more expectation from the graduate program of Thailand. But

51

still the mean score is above 3.6 i.e. which belongs to somewhat „agree level‟. But the overall satisfaction of both groups is similar.

5.1.5 Terms studied

Table 5.1.9: Analysis of terms studied by frequency

Please tell me how many terms have you been studying?

Cumulative

Frequency

Percent

Valid Percent

Percent

Valid1st term

28

9.2

9.2

9.2

2nd term

70

23.1

23.1

32.3

3rd term

75

24.8

24.8

57.1

4th term

41

13.5

13.5

70.6

more than 4th term

89

29.4

29.4

100.0

Total

303

100.0

100.0

Table 5.1.10: Analysis of terms studied and service quality by variables

Report

Please tell me how many terms have you been studying?

More than

1st term

2nd term

3rd term

4th term

4th tem

Total

Mean

N

Mean

N

Mean

N

Mean

N

Mean

N

Mean

N

Non academic

4.0107

28

3.6129

70

3.7413

75

3.6341

41

3.5000

89

3.6512

303

Academic

4.1825

28

3.8429

70

3.9778

75

4.0325

41

4.0350

89

3.9897

303

Program

3.8750

28

3.4857

70

3.5167

75

3.3720

41

3.3848

89

3.4843

303

issues

Reputation

3.9881

28

3.6381

70

3.6578

75

3.6098

41

3.7228

89

3.6964

303

Access

4.0357

28

3.6905

70

3.8089

75

3.6911

41

3.8052

89

3.7855

303

Group size

4.1905

28

3.8857

70

3.8489

75

3.9431

41

4.0187

89

3.9516

303

Design

3.9143

28

3.5829

70

3.6267

75

3.7122

41

3.7730

89

3.6977

303

Overall, I am

4.32

28

3.80

70

3.76

75

3.98

41

4.01

89

3.92

303

satisfied with

the university

Table5.1.9 shows which term the respondents studying, as a measure of the level of experience they have had. 9.2% (n=28) were studying in 1st term whom we can consider

52

as freshman students, 23.1% (n= 70) were in 2nd term, 24.8% (n=75) were in 3rd term, 13.5 % (n=41) were in 4th term, and 29.4% (n=89) were in more than 4th term or in their final terms. So, from the table we can say most of the students were seniors rather than freshman who completed the questionnaire.

Table 5.1.10 shows the analysis of term studied and perception of the quality of service variables. From the table we can see respondents who were in 1st term are more satisfied compare to the experienced one. Respondents who were studying in 2nd or 3rd term have lower mean score compared to other 3 groups. From the above table we can conclude (excluding fresher student) satisfaction increase with the increase in terms (experience).

5.1.6 University category

Table 5.1.11: Analysis of university category by frequency

Please categorize the University you are studying?

Cumulative

Frequency

Percent

Valid Percent

Percent

Valid Public University

78

25.7

25.7

25.7

Private University

142

46.9

46.9

72.6

Others

83

27.4

27.4

100.0

Total

303

100.0

100.0

53

Table 5.1.12: Analysis of university category and service quality by variables

Report

Please categorize the University you are studying?

Private

Public University

University

Others

Total

Mean

N

Mean

N

Mean

N

Mean

N

Non academic aspects

3.5205

78

3.7782

142

3.5566

83

3.6512

303

Academic aspects

4.0014

78

4.1056

142

3.7805

83

3.9897

303

Program issues

3.4840

78

3.5176

142

3.4277

83

3.4843

303

reputation

3.7607

78

3.7441

142

3.5542

83

3.6964

303

Access

3.6880

78

3.9225

142

3.6426

83

3.7855

303

Group size

3.9402

78

4.1080

142

3.6948

83

3.9516

303

Design, delivery,

3.7179

78

3.8310

142

3.4506

83

3.6977

303

assessment

Overall, I am satisfied with

3.95

78

4.00

142

3.77

83

3.92

303

the university

Table 5.1.6 shows the category of the University in which the students are studying their masters program. 25.7% (n=78) students were studying under public university (school), 46.9% (n=142) students were studying under private university (school) and 27.4% (n=83) were studying under others university (school). Other university is the category which is neither public nor private university. The university which fell under the other category were intergovernmental schools, joint schools etc. But majority of the respondents who belonged to others category was from Asian Institute of Technology (AIT). AIT is an intergovernmental school.

In Table 5.1.12 we can see that the respondents of private university tend to score higher mean in every service quality variable except reputation. Public university‟s respondent has score higher in reputation. The respondents who were studying in other university

54

have lower score than of the both university. Overall satisfaction private university has

higher mean, than public and other university.

5.1.7 Non-academic aspects

Table 5.1.13: Analysis of Non-academic aspects by average mean and standard deviation

Descriptive Statistics

N

Minimum

Maximum

Mean

Std. Deviation

The staff respect rule of

303

2

5

3.81

.774

confidentiality when I

disclose information to them

Administrative staff

303

1

5

3.80

.847

communicates well with

students

Administrative staff shows

303

1

5

3.73

.849

positive work attitude towards

students

When the staff promise to do

303

1

5

3.65

.848

something by a certain time,

they do so

When I have a problem,

303

1

5

3.64

.917

administrative staff show a

sincere interest in solving it

Administration offices keep

303

1

5

3.62

.749

accurate and retrievable

records.

Administrative staff provide

303

1

5

3.59

.852

caring attention

Administrative staff have

303

1

5

3.57

.802

good knowledge of the

systems

Students are treated equally

303

1

5

3.56

.854

by the staff

Inquiries are dealt with

303

1

5

3.54

.791

efficiently

Valid N (list wise)

303

Non academic aspects

303

1.50

5.00

3.6517

.60636

Table 5.1.7 presents the perception of the respondents in term of non-academic aspects. From the table we can see the mean score of the non academic aspects was 3.6512, with the standard deviation of 0.6064. There were 10 items (questions) under non-academic aspects. Out of 10 questions “The staff respect rule of confidentiality when I disclose

55

information to them” and “Administrative staff communicates well with students” scored the highest with the mean of 3.81 and 3.80, and standard deviation of 0.774 and 0.847.

For “the staff respect rule of confidentiality” respondent‟s maximum score was 5 i.e. “Strongly agree” and lowest score was 2 i.e. “Disagree”. The items which were scored the lowest were “Inquiries dealt with efficiently” and “students are equally treated by the staff” with the mean score of 3.54 and 3.56, and standard deviation on 0.791 and 0.854. Both of the questions in the Likert scale got the highest score “5” and lowest score “1”.

But looking at the above table we can conclude all the questions mean score are slightly above 3 which means, it is above the neutral.

5.1.8 Academic aspects

Table 5.1.14: Analysis of academic aspects by average mean and standard deviation

Descriptive Statistics

N

Minimum

Maximum

Mean

Std. Deviation

Instructor are highly educated in

303

2

5

4.33

.731

their respective fields

Instructor has the knowledge to

303

2

5

4.11

.715

answer my questions relating to

the course content.

Instructor deals with me in a

303

2

5

4.11

.682

courteous manner.

Instructor show positive attitude

303

2

5

4.06

.728

towards students

The handouts are provided

303

1

5

3.96

.827

adequately by the Instructor.

Instructor communicate well in

303

1

5

3.94

.772

classroom

The documentations are provided

303

1

5

3.89

.788

adequately by the Instructor.

When I have a problem,

303

2

5

3.88

.769

Instructor shows a sincere interest

in solving it.

Instructor provide feedback about

303

1

5

3.62

.844

my progress

Valid N (list wise)

303

Academic aspects

303

1.89

5.00

3.9897

.53576

Table 5.1.8 presents the perception of the respondent‟s in term of the academic aspects.

The mean score of this variable is 3.9897 with the standard deviation of 0.53576. There 9

56

items (questions) under this service quality variable. The question “Instructors are highly educated in their respective fields” has the highest mean score of 4.33 and standard deviation of 0.731. The minimum score for this question is 2 i.e. “disagree” and maximum question is 5 i.e. “strongly agree. The question “Instructor provide feedback about my progress” has the lowest mean score of 3.62 and the standard deviation is

0.844. Here, in the above table the mean score of overall academic aspects is near to 4 i.e. 3.9897. So, we can conclude that academic aspects lie on “agree level”.

5.1.9 Design, Delivery and Assessment

Table 5.1.15: Analysis of Design, Delivery and Assessment by average mean and standard deviation

Descriptive Statistics

N

Minimum

Maximum

Mean

Std. Deviation

The timing of the class is

303

1

5

3.83

.853

suitable

Teaching Methodology is

303

1

5

3.78

.751

appropriate.

Curriculums designed by the

303

1

5

3.67

.937

university are up to date.

The proportion between

303

1

5

3.61

.850

theory and practice are

appropriate

The assessment and the

303

1

5

3.61

.858

grading by the instructor are

fair.

Valid N (list wise)

303

Design, delivery and

303

1.80

5.00

3.6977

.59174

assessment

Table 5.1.9 presents the perception of the respondents in term of design, delivery and assessment. This service quality variable gains a mean score of 3.6977 and standard deviation of 0.59174. So, the mean score of design, delivery and assessment is above neutral. There were 4 items that asked about design, delivery and assessment. Among 4 items “timing of the class is suitable” score the highest. The mean score was 3.83 and

57

standard deviation was 0.853. The maximum score was 5 i.e. “strongly agree” and minimum score was 1 i.e. “strongly disagree”. Items like “The proportion between theory and practice are appropriate” and “The assessment and the grading by the instructor are fair” got lowest and same mean score of 3.61 but standard deviation was 0.850 and 0.858.

5.1.10 Group size

Table 5.1.16: Analysis of group size by average mean and standard deviation

Descriptive Statistics

N

Minimum

Maximum

Mean

Std. Deviation

Small class size helps the

303

1

5

4.30

.822

class make more interactive.

A smaller the class size helps

303

1

5

4.24

.860

student better understand

The number of students

303

1

5

3.31

.900

enrollment in one class is

small

Valid N (list wise)

303

Group size

303

2.00

5.00

3.9516

.63836

Table 5.1.10 presents the analysis of the perception of respondents in term of group size.

The mean score gained by group size is 3.9516 which is close to score 4 i.e. “agree level” and the standard deviation is 0.63836. There were 3 items under group size. “Small class helps the class make more interactive” scored highest with the mean 4.30 and standard deviation of 0.822 whereas “The number of students‟ enrollment in one class is small” scored the lowest with the mean 3.31 and standard deviation of 0.900.

58

5.1.11 Program issues

Table 5.1.17: Analysis of program issues by average mean and standard deviation

Descriptive Statistics

N

Minimum

Maximum

Mean

Std. Deviation

The university runs excellent

303

1

5

3.62

.844

quality programs

The university offers

303

1

5

3.54

.908

programs with flexible

structure

The university offers a wide

303

1

5

3.52

.898

range of programs with

various specializations

The university operates an

303

1

5

3.26

.876

excellent counseling service

Valid N (list wise)

303

Program issues

303

1.25

5.00

3.4843

.65290

Table 5.1.11 shows the analysis of the perception of the respondents in term of program issues. The program issues have the mean score of 3.4843 which is slightly above

“neutral” with standard deviation of 0.65290. There are 4 items under this service quality variable. “The university runs excellent quality programs” scores the highest mean i.e. 3.62 and standard deviation is 0.844 and “the university operates an excellent counseling service” has the lowest mean of 3.26 and standard deviation is 0.876.

5.1.12 Reputation

Table 5.1.18: Analysis of reputation by average mean and standard deviation

Descriptive Statistics

N

Minimum

Maximum

Mean

Std. Deviation

The university has a

303

1

5

3.87

.835

professional image

The academic program run by

303

1

5

3.81

.844

the university is reputable

The university‟s graduates are

303

1

5

3.41

.821

easily employable

Valid N (list wise)

303

Reputation

303

1.33

5.00

3.6964

.63980

Table 5.1.12 represents the analysis of perception of respondents in term of reputation. The reputation has the mean score of 3.6964 and standard deviation of 0.63980. There

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were 3 items under this service quality variable. “The university has a professional image” scored highest mean i.e. 3.87 and its standard deviation was 0.835. “The university‟s graduates are easily employable” has the lowest mean score of 3.41 and the standard deviation of 0.821.

5.1.13 Access

Table 5.1.19: Analysis of access by average mean and access

Descriptive Statistics

N

Minimum

Maximum

Mean

Std. Deviation

Instructor allocate sufficient

303

1

5

3.82

.764

time for consultation

Instructor is never too busy to

303

2

5

3.78

.803

respond to my request for

assistance.

The staff are easy to contact

303

1

5

3.76

.887

Valid N (list wise)

303

Access

303

2.00

5.00

3.7855

.61604

Table 5.1.13 represents the analysis of the perception of respondents in term of access. Access is the last service quality variable in this research. The mean score of this variable is 3.7855 and standard deviation is 0.61604. There were 3 items under this variable.

“Instructor allocates sufficient time for consultation” has the highest mean score and its standard deviation is 0.764. Under this variable all the items mean score is above 3.7. So, we can conclude access is slightly closer to “agree level”.

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5.1.14 Overall Satisfaction

Table 5.1.20: Analysis of access by average mean and standard deviation

Descriptive Statistics

N

Minimum

Maximum

Mean

Std. Deviation

Overall, I am satisfied with the

303

1

5

3.92

.792

university

Valid N (list wise)

303

Table 5.1.15 represents the analysis of the overall student satisfaction with the university.

The mean score of this item is 3.92 which closer to score 4. So, it is close to “agree level”. We can conclude most of the respondents agree they are satisfied with the university. Though there are some respondents who are not satisfied with the university so the minimum score for this item is 1 i.e. “Strongly disagree” but the most of the student are satisfied so the mean score is 3.92. The standard deviation for this item is 0.792.

5.1.15 Recommend Others

Table 5.1.21: Analysis of recommend others by frequency

Would you recommend your university to others ?

Cumulative

Frequency

Percent

Valid Percent

Percent

Valid Definitely not recommend

7

2.3

2.3

2.3

Probably not recommend

24

7.9

7.9

10.2

Not sure

21

6.9

6.9

17.2

Probably recommend

133

43.9

43.9

61.1

Definitely recommend

118

38.9

38.9

100.0

Total

303

100.0

100.0

Table 5.1.14 is the analysis of the question “Would you recommend your university to others?” As the number of the respondents were 303 students, 43.9% (n=133) students would probably recommend their university, 38.9% (n=118) would definitely recommend, 7.9% (n=24) would probably not recommend, 6.9% (n=21) were not sure

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and 2.3% (n=7) would definitely not recommend. So, from the above statistics we may conclude the students who satisfied with the service quality would probably or definitely recommend their university to others.

5.2 Inferential Statistics

Pearson Correlation Coefficient is used to test the relationship between the service quality variables (Non-academic aspects, academic aspects, design, delivery and assessments, group size, program issues, reputation, and access) and overall student satisfaction, and ANNOVA is used to test the research question “Does self payment and other‟s payment influence satisfaction?” and “If there is any difference in perception of satisfaction in term of other demographic factors?” For deciding whether the hypotheses is rejected or accepted, the researcher has to examine significance (p) value. The rule is the null hypothesis is rejected, if the p-value is less than Alpha. Since, the analysis was measured with 95% of level of confidence, so the alpha would be 5 % i.e. 0.05. Therefore, if the significance value is less than 0.05, the alternative hypothesis is accepted. The results of the hypotheses testing are shown below:

Hypothesis 1: relationship between non-academic aspects and overall student satisfaction

Ho1: there is no relationship between non-academic aspects and overall student satisfaction of the students of universities in Thailand.

Ha1: there is a relationship between non-academic aspects and overall student satisfaction of the students of universities in Thailand.

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Table 5.2.1: relationship between non-academic aspects and overall student satisfaction

Correlations

Overall, I am satisfied

Non academic

with the university

aspects

Overall, I am satisfied with the university

Pearson Correlation

1

.437**

Sig. (2-tailed)

.000

N

303

303

Non academic aspects

Pearson Correlation

.437**

1

Sig. (2-tailed)

.000

N

303

303

**. Correlation is significant at the 0.01 level (2-tailed).

Table 5.2.1 shows the analysis of the relationship between non-academic aspects and overall student satisfaction of the students of Universities in Thailand. The analysis is based on the Pearson Correlation Coefficient.

The above table shows the significance is equal to .000. According to the rule if sig. is less than alpha (.000 < .001), we reject null hypothesis. Since the p-value (sig.) is less than 0.01, we can say that there is overwhelming evidence to infer that the alternative hypothesis is true. We can also say that the relationship is highly significant between non-academic aspects and overall student satisfaction of the students of universities in Thailand (Keller, 2009).

The correlation between non-academic aspects and overall student satisfaction of the students is moderate positive correlation of 0.437. Therefore, we can infer that an increase in quality of non-academic aspects may lead to a slight increase in student satisfaction.

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Hypothesis 2: relationship between academic aspects and overall student

satisfaction

Ho2: there is no relationship between academic aspects and overall student satisfaction of the students of universities in Thailand.

Ha2: there is a relationship between academic aspects and overall student satisfaction of the students of universities in Thailand.

Table 5.2.2: relationship between academic aspects and overall student satisfaction

Correlations

Overall, I am

satisfied with the

university

Academic aspects

Overall, I am satisfied with the

Pearson Correlation

1

.617**

university

Sig. (2-tailed)

.000

N

303

303

Academic aspects

Pearson Correlation

.617**

1

Sig. (2-tailed)

.000

N

303

303

**. Correlation is significant at the 0.01 level (2-tailed).

Table5.2.2 is the analysis of the relationship between academic aspects and overall student satisfaction of the students of Universities in Thailand. The table shows significance is 0.000. So, p-value (sig.) is less than 0.01 i.e. 0.000<0.01, we reject null hypothesis. Since, sig. is less than 0.01; we can say the relationship is highly significant between academic aspects and overall student satisfaction of the students of University in Thailand.

The correlation between academic aspects and overall student satisfaction is moderate positive correlation of 0.617. Therefore, quality in academic aspects positively influences student satisfaction.

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Hypothesis 3: relationship between design, delivery and assessment and overall

student satisfaction

Ho3: there is no relationship between design, delivery and assessment and overall student satisfaction of the students of universities in Thailand.

Ha3: there is a relationship between design, delivery and assessment and overall student satisfaction of the students of universities in Thailand.

Table 5.2.3: relationship between design, delivery and assessment and overall student satisfaction

Correlations

Overall, I am

satisfied with the

Design, delivery and

university

assessment

Overall, I am satisfied with the

Pearson Correlation

1

.641**

university

Sig. (2-tailed)

.000

N

303

303

Design, delivery and assessment

Pearson Correlation

.641**

1

Sig. (2-tailed)

.000

N

303

303

**. Correlation is significant at the 0.01 level (2-tailed).

Table 5.2.3 presents the analysis of the relationship between design, delivery and assessment and overall student satisfaction of the student of Universities in Thailand. The table shows the p-value (sig.) is .000 which is less than 0.01 (0.000<0.01), so we reject null hypothesis. As the p-value is less than .0001, we can say the relationship between design, delivery and assessment and overall student satisfaction of the student of University in Thailand is highly significant.

The correlation coefficient between design, delivery and assessment and overall student satisfaction is moderate positive correlation of 0.641. Therefore, with the increase in quality of design, delivery and assessment there will be increases in student satisfaction.

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Hypothesis 4: relationship between group size and overall student satisfaction

Ho4: there is no relationship between group size and overall student satisfaction of the students of universities in Thailand.

Ha4: there is a relationship between group size and overall student satisfaction of the students of universities in Thailand.

Table 5.2.4: relationship between group size and overall student satisfaction

Correlations

Overall,

I

am

satisfied

with

the

university

Group size

Overall, I am satisfied with the

Pearson Correlation

1

.329**

university

Sig. (2-tailed)

.000

N

303

303

Group size

Pearson Correlation

.329**

1

Sig. (2-tailed)

.000

N

303

303

**. Correlation is significant at the 0.01 level (2-tailed).

Table 5.2.4 presents the analysis of the relationship between group size and overall student satisfaction of the student of Universities in Thailand. Since the p- value is less than 0.01 (0.000<0.01), we reject null hypothesis and we can say there is a highly significant relationship between group size and overall student satisfaction of the student of Universities in Thailand.

The correlation between group size and overall student satisfaction is low positive correlation of 0.329. So, we can also conclude increase in quality in group size may also help to increase to student satisfaction, because the relationship between them is weak but is still positive.

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Hypothesis 5: relationship between reputation and overall student satisfaction

Ho5: there is no relationship between reputation and overall student satisfaction of the students of universities in Thailand.

Ha5: there is a relationship between reputation and overall student satisfaction of the students of universities in Thailand.

Table 5.2.5: relationship between reputation and overall student satisfaction

Correlations

Overall, I am satisfied

with the university

Reputation

Overall, I am satisfied

with the Pearson Correlation

1

.636**

university

Sig. (2-tailed)

.000

N

303

303

reputation

Pearson Correlation

.636**

1

Sig. (2-tailed)

.000

N

303

303

**. Correlation is significant at the 0.01 level (2-tailed).

Table 5.2.5 shows the analysis of the relationship between reputation and overall student satisfaction of the students of Universities in Thailand. The p- value is 0.000 which is less than 0.01 (0.000<0.01), so we reject the null hypothesis, and we can say the relationship between reputation and overall student satisfaction of the students of University in Thailand is highly significant.

The correlation between reputation and overall student satisfaction is moderate positive correlation of 0.636. Therefore, we can conclude the student satisfaction also increase the good reputation of their university.

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Hypothesis 6: relationship between program issues and overall student satisfaction

Ho6: there is no relationship between program issues and overall student satisfaction of the students of universities in Thailand.

Ha6: there is a relationship between program issues overall student satisfaction of the students of universities in Thailand.

Table 5.2.6: relationship between program issues and overall student satisfaction

Correlations

Overall, I am

satisfied with the

university

Program issues

Overall, I am satisfied with the

Pearson Correlation

1

.611**

university

Sig. (2-tailed)

.000

N

303

303

Program issues

Pearson Correlation

.611**

1

Sig. (2-tailed)

.000

N

303

303

**. Correlation is significant at the 0.01 level (2-tailed).

Table 5.2.6 presents the analysis of the relationship between program issues and overall student satisfaction of the student of Universities in Thailand. The p-vale of this service quality variable is 0.000. Since it is less 0.01 (0.000<0.01), we reject null hypothesis and we can infer that the relationship between program issues and overall student satisfaction of the students of Universities in Thailand is highly significant.

The correlation between program issues and overall student satisfaction is moderate positive correlation of 0.611. Therefore, increase in the quality of program issues leads to positive increase in student satisfaction.

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Hypothesis 7: relationship between access and overall student satisfaction

Ho7: there is no relationship between access and overall student satisfaction of the students of universities in Thailand.

Ha7: there is a relationship between access and overall student satisfaction of the students of universities in Thailand.

Table 5.2.7: relationship between access and overall student satisfaction of the students

Correlations

Overall, I am satisfied

with the university

Access

Overall, I am satisfied with the

Pearson Correlation

1

.401**

university

Sig. (2-tailed)

.000

N

303

303

access

Pearson Correlation

.401**

1

Sig. (2-tailed)

.000

N

303

303

**. Correlation is significant at the 0.01 level (2-tailed).

Table 5.2.7 shows the analysis of the relationship between access and overall student satisfaction of the student of Universities in Thailand. The above table shows p-value is 0.000 and it is less than 0.01. So, we reject the null hypothesis and we can say that there is highly significant relationship between access and overall student satisfaction of the student of Universities in Thailand.

The correlation between access and overall student satisfaction of the student is moderate positive correlation of 0.401. So, we can say accessibility, ease of contact with both academic and non academic staff somehow influence student satisfaction.

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Research question:

Does tuition fee paid by self and tuition fee paid by others influence satisfaction?

Table 5.2.8: Tuition fee paid by self and tuition fee paid by others influence satisfaction

Non

Academic

Design

Group

Program

Reputation

Access

Overall

Academic

size

issues

satisfaction

a. Parents/

3.6624

4.0119

3.7108

4.0108

3.5390

3.7455

3.7849

4.00

others

(n=186)

b. Self (n=

3.6414

3.9327

3.6626

3.8990

3.3460

3.5825

3.7609

3.74

99)

c. Employer

3.5889

4.0741

3.7556

3.6296

3.6806

3.8148

3.9259

4.17

(n=18)

df

2

2

2

2

2

2

2

2

F

.139

.944

.304

3.480

3.755

2.449

.545

4.559

Sig.

.871

.390

.738

.032

.025

.088

.581

.011

Significant

None

None

None

a and c

None

None

None

a and b

differences

(0.022)

(0.027)

between

means

(Post-hoc

analysis)

Table 5.2.8 shows the mean score and ANOVA analysis of the tuition fee sponsor with overall satisfaction. Post hoc test was conducted for exploratory and interpretative purposes by comparing multiple groups for a single independent variable. The test can be done if the F-test of ANOVA found any significant difference among the groups (Lomax, 2001; Kerlinger, 2000). This study used Games-Howell test to examine the differences among groups. “The Games-Howell procedure is the most powerful when the population variances are different but can be liberal when sample sizes are small. However, Games-Howell is also accurate when sample sizes are unequal” (Field, 2005, p.341). From the ANOVA table we find out sig. to be 0.011 which is less than 0.05. If

70

the p-value lies between 0.01 and 0.05, we can say there is a significant difference between respondents who pays the tuition fee by themselves and who gets it paid in terms of overall satisfaction. From the post hoc test we there was significant difference (0.025<0.05) between the group parents/others and self, in terms of perception of overall satisfaction. And from the mean score we see respondents whose tuition fee is paid by the employer has the highest mean of 4.17, followed by parents/ others with 4.00 and self payment with the lowest mean of 3.74. The man score of the respondents whose tuition fee is paid by employer may be high because the sample size of the respondents is small. But still, from this analysis we can say the student who pays tuition fees by themselves have higher expectation of service quality and they are less satisfied than the students who get their tuition fees paid. So, we can conclude the self payment and payment by others influence satisfaction.

ANOVA of other demographic factors and Overall student satisfaction

To test the significance between student satisfaction and other demographic factors (gender, age, ethnic group, term studied and universities category), ANOVA was used. ANOVA was conducted to access the differences between group means and post-hoc test was conducted to determine which mean differ. Games-Howell post-hoc test was conducted as this procedure is considered the most powerful when population variance and sample size are different and unequal (Field, 2005).All the demographic factors were tested (see Appendix II). The demographic factors like gender, age, ethnic group and categories of university didn‟t have statistical difference (significance) between the group and in terms of perception of overall student satisfaction. But some differences in perception of service quality variables were found between the groups like age and

71

categories of university. So, here we presented only the demographic factors which had statistical significant difference between the groups. No differences between the groups like gender and ethnic group were found in terms of perception of service quality or overall student satisfaction (see appendix II for ANOVA of gender and ethnic group).

Table 5.2.9: ANOVA of Age range

Non

Academic

Design

Group

Program

Reputation

Access

Overall

Academic

size

issues

satisfaction

a. 20-25

3.7862

4.0614

3.7138

3.9702

3.5691

3.7588

3.9377

3.97

(n=123)

b. 26-30

3.6022

3.8986

3.6628

3.9440

3.4161

3.6302

3.7032

3.86

(n=137)

c. Above

3.4209

4.0749

3.7628

3.9225

3.4593

3.7287

3.6124

4.00

30 (n=43)

df

2

2

2

2

2

2

2

2

F

6.851

3.691

.543

.106

1.827

.1377

6.936

.812

Sig.

.001

.026

.582

.900

.163

.254

.001

.445

Significant

a and b

a and b

None

None

None

None

a and b

None

differences

(0.37),

(0.036)

(0.006),

between

a and c

a and c

means

(0.03)

(0.011)

(Post-hoc)

Table 5.2.9 is the ANOVA analysis of the respondents of different age group. In the table we can see the significance value of overall satisfaction is 0.445 i.e. 0.445>0.05. This mean there is no difference in the perception of overall student satisfaction between the age group. But if we look at the significance value of service quality variables like non academic aspects, academic aspects and access, we find statistical significance difference. From the post-hoc analysis we find the perception of the respondents which fall under the age group of 20-25 differs from the respondents of age group of 26-30 yrs and above 30 yrs in terms of non academic aspects and access. Looking at the mean score

72

they tends to score higher than other groups. Even perception of service quality of

academic aspects differs between age group of 20-25 yrs and 26-30 yrs.

Table 5.2.10: ANOVA of Terms studied

Non

Academi

Design

Group

Progra

Reputati

Access

Overall

Academi

c

size

m issues

on

satisfaction

c

a. 1 st term

4.0107

4.1825

3.9143

4.1905

3.8750

3.9881

4.0357

4.32

(n= 28)

b. 2 nd term

3.6129

3.8429

3.5829

3.8857

3.4857

3.6381

3.6905

3.80

(n=70)

c. 3 rd term

3.7413

3.9778

3.6267

3.8489

3.5167

3.6578

3.8089

3.76

(n=75)

d. 4 th term

3.6341

4.0325

3.7122

3.9431

3.3720

3.6098

3.6911

3.98

(n=41)

e. More

3.5000

4.0350

3.7730

4.0187

3.3848

3.7228

3.8052

4.01

than 4 th

term

(n=89)

df

4

4

4

4

4

4

4

4

F

4.540

2.504

2.271

1.923

3.484

1.918

1.884

3.418

Sig.

.001

.042

.062

.107

.008

.107

.113

.009

Significant

a and b

a and b

None

None

a and d

None

a and b

a and b

differences

(0.012,

(0.038)

(0.028)

(0.044)

(0.012),

a

between

a and e

, a and

and c

means

(0.001)

e

(0.003)

(Post-hoc

(0.013)

analysis)

Table 5.2.9 shows the analysis of the perception of the respondents who are studying in different terms. In the table we can see the sig. value of student overall satisfaction is 0.009. There is a strong significant relationship between terms studied and overall student satisfaction because the sig. value is less than 0.01 i.e. 0.009<0.001. Post-hoc analysis shows us there is difference in perception of overall satisfaction between 1st and 2nd term (0.012<0.05) and 1st and 3rd term (0.003<0.01). The post hoc analysis in tale 5.2.9 also

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reflects that perception of service quality variables like non-academic aspects, academic aspects, program issues and access differs among the respondents studying in different terms. We see most of the differences are between the respondents studying in 1st term and respondents of other terms, as respondents of 1st term tends to score higher mean in every factor.

In the study of Zeithmal et al. (1993), they found that a customer‟s level of expectations is dependent on a number of antecedents. One of these determinants is past experience. So, the student who are fresh, they may not know what to expect of college. Therefore, expectations may be high or low, but as the student becomes more experienced their expectations should become more realistic. And as a student comes closer to matriculation, he or she is more likely to become involved in the goal of graduating and obtaining a desirable job. It is believed that the student is likely to increase their expectations of institution‟s role in achieving these goals (Citied in Ham et al., 2003, p. 199).

So, from the table we can conclude that the respondent in their 1st term have higher satisfaction than others because they lack experience and as the respondents progress through their expectation become more realistic. As we see in the table, after the 1st term their perception has decreased and after 4th term it again starts increasing. So, as mentioned in the study of Ham et al. (2003), the reason for increasing satisfaction could be due they are involved in achieving the goals of graduating and obtaining desirable job.

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Table 5.2.11: ANOVA of Categories of university

Non

Academic

Design

Group

Program

Reputation

Access

Overall

Academic

size

issues

satisfaction

Public

3.5205

4.0014

3.7179

3.9402

3.4840

3.7607

3.6880

3.95

(n=78)

Private

3.7782

4.1056

3.8310

4.1080

3.5176

3.7441

3.9225

4.00

(n=142)

Others

3.5566

3.7805

3.4506

3.6948

3.4277

3.5542

3.6426

3.77

(n=83)

df

2

2

2

2

2

2

2

2

F

6.136

10.267

11.652

11.774

.495

2.874

6.990

2.260

Sig.

.002

.000

.000

.000

.610

.058

.001

.106

Significant

a and b

a and c

a and c

a and c

None

None

a and b

None

differences

(0.013),

(0.032),

(0.016),

(0.029),

(0.20),

between

b and c

b and c

b and c

b and c

b and c

means

(0.013)

(0.000)

(0.000)

(0.000)

(0.003)

(post- hoc)

Table 5.2.10 is the analysis of perceptions of respondents who are studying in public, private or other universities. The sig. value of overall satisfaction is 0.106 which is greater than 0.005 (0.106 > 0.005). It means there are no differences in perceptions of satisfaction among the respondents studying in different categories of universities. But if we look at the sig. value of service quality variables (non-academic, academic, program issues, reputation and access), it indicates that the respondents studying in different categories of universities have different perceptions of service quality. From the post hoc analysis we found that mostly perception of service quality variable is different between the respondents of public and others university, and private and others university.

Looking at the mean scores of overall satisfaction of the respondent‟s of private university tends to score high, followed by public university and other university. But it is

75

not statistically significant to say that the respondents of private university are more satisfied because sig. value (0.106) is more than alpha value (0.05).

Regression analysis of dependent and independent variables

All the items measuring constructs were analyzed using factor analysis. “Factor analysis is a statistical method used to describe variability among observed variables in terms of a potentially lower number of unobserved variables called factors” ( http://en.wikipedia.org/wiki/Factor_analysis). Table 5.2.9 shows the rotated component matrix which is a matrix of factor loadings for each variable for each factor. The factor loadings less than 0.4 were suppressed and the overlapping items were removed. All items shown in table 5.2.9 are the remaining items after the analysis. The items grouping into factors were then transformed into compound variables. The reason for this is to reduce multicollinearity and also to reduce the sample size needed for regression.

“Multicollinearity is usually regarded as a problem because it means that the regression coefficients may be unstable. This implies that they are likely to be subject to considerable variability from sample to sample. In any case, when two variables are very highly correlated, there seems little point in treating them as separate entities”

(Savatsomboon, 2010, p.87).

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Table 5.2.12: Rotated component matrix

Rotated Component Matrix a

Component

1

2

3

4

5

Administrative staff communicates well with students

.778

Administrative staff provide caring attention

.753

Administrative staff shows positive work attitude towards

.750

students

Administrative staff have good knowledge of the systems

.740

When I have a problem, administrative staff show a sincere

.712

interest in solving it

The staff are easy to contact

.708

Inquiries are dealt with efficiently

.691

When the staff promise to do something by a certain time,

.648

they do so

Administration offices keep accurate and retrievable records.

.635

The university runs excellent quality programs

.772

The university has a professional image

.686

The university offers a wide range of programs with various

.681

specializations

The academic program run by the university is reputable

.606

The university‟s graduates are easily employable

.575

The university operates an excellent counseling service

.569

Curriculums designed by the university are up to date.

.528

.421

The proportion between theory and practice are appropriate

.498

Instructor allocate sufficient time for consultation

.716

When I have a problem, Instructor shows a sincere interest in

.715

solving it.

Instructor is never too busy to respond to my request for

.687

assistance.

Instructor show positive attitude towards students

.663

Instructor are highly educated in their respective fields

The handouts are provided adequately by the Instructor.

.837

The documentations are provided adequately by the

.826

Instructor.

The assessment and the grading by the instructor are fair.

.475

Instructor has the knowledge to answer my questions relating

.403

to the course content.

A smaller the class size helps student better understand

.863

Small class size helps the class make more interactive.

.856

Extraction Method: Principal Component Analysis.

Rotation Method: Varimax with Kaiser Normalization.

a. Rotation converged in 6 iterations.

Therefore, from the above table we find five variables remaining. They are (1) non-academic aspects, (2) reputation, (3) access, (4) academic aspects and (5) group size. The researcher analyzed these variables using regression (multiple) model in SPSS. “Multiple

77

regression seeks to predict an outcome from several predictor independent variables. This is an incredibly useful tool because it allows us to go a step beyond the data that we actually possess” (Field, 2005, p. 144). The results are as follows:

Table 5.2.13: Summary of the model

In table 5.2.9 the first table is a summary of the model. This summary table provides the value of r, r2 and adjusted r2 for the model that has been derived.

„r‟ represents the value of the multiple correlation coefficients between the predictors and the outcome (Field, 2005). Here, r has a value 0.756, this value represents the simple correlation between group size, academic aspects, access, design, delivery and assessment and non-academic aspects and overall student satisfaction.

„r2‟ is a measure of how much of the variability in the outcome is accounted for by the predictors (Field, 2005). The value of r2 is 0.572 which tells us that these five service quality variables can account for 57.2% of the variation in the overall student satisfaction. This means that 42.8% of the variation in overall student satisfaction cannot be explained by these five service quality variables. So, there must be other variables too that have an influence.

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„The adjusted r2‟ gives an idea of how well the model generalizes and ideally its value is likely to be the same or very close to, the value of r2 (Field, 2005). Here, the difference between r2 and adjusted r2 is 0.7% (0.572 – 0.565= 0.007). This means that if the model were derived from the population rather than a sample it would account for approximately 0.7% less variance in outcome.

Table5.2. 14: ANOVA table analysis between independent and dependent variables

Table 5.2.10 is the output reports of an analysis of variance (ANOVA). „F-ratio‟ represents the ratio of the improvement in prediction that results from fitting the model, relative to the inaccuracy still exists in the model (Field, 2005). “A large value of „F‟ indicates that most of the variation in „Y‟ is explained by the regression equation and that the model is valid. A small value of „F‟ indicates that most of the variation in „Y‟ is unexplained” (Keller, 2009, p.679). From the table we can see, F is 79.321, which is significant at p (sig.) value <.001, i.e. 0.000< 0.001. This result tells us that there is less than a 0.1% chance of F-ratio being this large. Therefore, the regression model significantly improved our ability to predict overall student satisfaction (outcome, or dependent variable).

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Table 5.2.15: Coefficients of the regression model

The b-values in the table 5.2.11 represent the relationship between overall student satisfaction and each predictor (i.e. service quality variables). If the value is positive we can tell that there is a positive relationship between the predictor and the outcome whereas negative coefficient represents a negative relationship. The b-value also tells us to what degree each independent variable affects the dependent variables if the effects of all other independent variables are held constant (Field, 2005).

In the table 5.2.11 all five service quality variables have positive b-values; which indicates the positive relationships between the service quality variables and overall student satisfaction. As non-academic aspects quality increases, student‟s satisfaction increases; as reputation increases, student‟s satisfaction increases; likewise as quality of access, academic aspects, group size increases, so do the student‟s satisfaction increase.

Here, for e.g., if reputation increases by one unit, student satisfaction will increase by 0.481, other variables held constant.

The beta value tells us the number of standard deviations that the outcome will change as a result of one standard deviation change in the predictor (Field, 2005). Higher beta value signifies stronger correlation with the dependent variable. In table 5.2.11 reputation have the highest beta (0.607), followed by academic aspects (0.329), non academic aspects

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(0.206), access (0.183) and group size (0.138). This represents as if the quality of reputation increases by one standard deviation, overall student satisfaction standard deviation increases by 0.607, if the academic aspects increases by one standard deviation, overall student satisfaction standard deviation increases by 0.329, if the non-academic aspects increases by one standard deviation, overall student satisfaction standard deviation increases by 0.206 and so on. But the interpretation is true only if the other variables are held constant while measuring the relationship between dependent variables and one of the independent variables. So, from the results of multiple regression we can infer that reputation influences the graduate student‟s satisfaction the most followed by academic aspects, non-academic aspects, access and group size.

Figure 5.1: Results of Regression analysis

Reputation=

0.607

Academic

aspects= 0.329

Overall student

satisfaction /

Non-academic

aspects= 0.206

2

= 57.2 %

r

Access= 0.183

Group size=

0.138

In this chapter all the collected data which were analyzed in SPSS were presented. Descriptive analysis and hypothesis testing were performed. Descriptive analysis helped see perceptions of the respondents towards service quality. Hypothesis testing was under

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to find the out relationship between the service quality variables and overall student satisfaction. In chapter six the findings of the survey, conclusions and recommendations will be presented.

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CHAPTER SIX

CONCLUSIONS AND RECOMMENDATIONS

This study “The study of graduate student satisfaction towards service quality of

Universities in Thailand” firstly aimed to measure the perception of the student satisfaction from the service quality delivered by the universities in Thailand. This research also tried to find out if, self payment or tuition fee paid by others influence satisfaction and are there any differences in perception of satisfaction in terms of other demographic factors. This is the last chapter where summary and conclusions of findings and recommendation are discussed.

6.1 Summary and Conclusion of Findings

This study aims to find the relationship between the student satisfaction and service quality delivered by the Universities in Thailand. This study tries to answer the following questions:

• Do these service quality variables (non-academic aspects, academic aspects, design, delivery and assessment, group size, program issues, reputation and access) influence satisfaction of the student of the universities in Thailand?

• Does self payment and others‟ payment influence satisfaction?

• Are there any differences in the perception of satisfaction in terms of other demographic factors?

To accomplish the research objectives, a questionnaire survey was conducted from 16th

February, 2011 to 13th March, 2011by using a quantitative survey. Research questions were adopted from the studies by Firdaus (2005), Afjal et al. (2009) and Huang (2009).

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The questionnaire was produced in two formats: printed out (hard copy) and online (soft copy). The hard copy questionnaire was created using Microsoft Word 2007 and the online questionnaire was created through a website called www.docs.google.com. As the survey was about the perception of graduate student towards the service quality of their university the respondents were all the graduate students who were studying a Masters program in any university of Thailand. Most of the hard copy questionnaires were distributed in universities like Webster University of Thailand and Asian Institute of Technology. The online questionnaire was distributed through posts on university websites, email addresses and via Facebook. The total sample collected was 303.

The data was analyzed using SPSS. All the research questions of this study were answered in chapter five. The summary of the research results are as follows:

Table 6.1.1: Summary of the Tested Hypotheses

Hypothesis

Mean

Sig.

r

Results

H1: Relationship between non academic aspects and

3.65

0.000

0.437

Reject Ho

overall student satisfaction

H2: Relationship between academic aspects and overall

3.99

0.000

0.617

Reject Ho

student satisfaction

H3: Relationship between design, delivery and

3.7

0.000

0.641

Reject Ho

assessment and overall student satisfaction

H4: Relationship between group size and overall

3.95

0.000

0.329

Reject Ho

student satisfaction

H5: Relationship between reputation and overall

3.7

0.000

0.636

Reject Ho

student satisfaction

H6: Relationship between program issues and overall

3.5

0.000

0.611

Reject Ho

student satisfaction

H7: Relationship between access and overall student

3.79

0.000

0.401

Reject Ho

satisfaction

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All the null hypotheses were rejected because value of the significance was less than 0.01. So, we can infer the relationship between the overall student satisfaction and service quality variables were highly significant.

Analyzing the mean score of the service quality variables we find academic aspects has the highest mean score i.e.3.99, followed by group size with 3.95access with 3.79, design, delivery and assessment and reputation with 3.7 , non academic aspects with 3.65 and program, issues 3.5 . From these mean score we can say respondents are less satisfied with the program issues and also performance of non-academic aspects. But still the entire variable‟s mean score is above 3.5, which are near to “agree level”. This reflects the respondents agree that are satisfied with overall performance of these variables of the service quality.

Analyzing the value of the correlation coefficients (r) between service quality variables and overall student satisfaction, we find design, delivery and assessment has the highest value i.e. 0.641, followed by reputation, academic aspects, and program issues and so on. Except group size all the other service quality variables have moderate positive correlation for influencing the student satisfaction. Though group size has weak correlation with the student satisfaction but still there is a positive correlation between them. Even though the question about overall service quality wasn‟t included in the questionnaire, still the researcher measured the correlation between overall service quality and student satisfaction through the help of SPSS which is shown in table 6.1.2 below:

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Table 6.1.2: correlation between overall service quality and overall student satisfac-tion

Correlations

Overall, I am satis-

Overall Service

fied with the uni-

quality

versity

Overall Service quality

Pearson Correlation

1

.696**

Sig. (2-tailed)

.000

N

303

303

Overall, I am satisfied with the

Pearson Correlation

.696**

1

university

Sig. (2-tailed)

.000

N

303

303

**. Correlation is significant at the 0.01 level (2-tailed).

From table 6.1.2 we can find the correlation value between overall service quality and overall student satisfaction is 0.696 ~0.7. As it is 0.7 we can say there is strong positive correlation between the groups. So, we can conclude that all these service quality variables positively influence the student satisfaction. If there is an increase in quality of these variables, it should help to increase the satisfaction level of the students.

For the research question “Does self payment and payment by others influence satisfaction?” We found students whose tuition fee is paid by others differ from the students who pay their own fees in terms of satisfaction. It was shown in table 5.2.8 of chapter five. We found respondents whose tuition fee was sponsored by others had the higher mean score than the respondents who paid their own fees. Meaning, the respondents who pays their own fees have higher expectation of service quality. Even from the significance test we found there is evidence to show that perceptions of satisfaction differ between the respondents whose tuition fee is paid by others and who pay their own tuition fees.

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For the last research question “Are there any differences in perception of student satisfaction in terms of other demographic?” We found the student perception of satisfaction differed as the term or experience increased. The students studying in different terms had different levels of perceptions of satisfaction.

After the analysis of the collected survey of 303 graduate students studying in universities of Thailand we can infer that most of the respondents are satisfied with the service quality delivered by their university. It is shown in the following table 6.1.3:

Table 6.1.3: student satisfaction with the university

Overall, I am satisfied with the university

Cumulative

Frequency

Percent

Valid Percent

Percent

Valid Strongly disagree

2

.7

.7

.7

disagree

15

5.0

5.0

5.6

neutral

50

16.5

16.5

22.1

agree

173

57.1

57.1

79.2

strongly agree

63

20.8

20.8

100.0

Total

303

100.0

100.0

Table 6.1.3 shows 57.1 % (n=173) respondents are satisfied with their university, 20.8% (n=63) respondents are strongly satisfied with their university. So, the overall conclusion is that respondents are satisfied with the service of their university and these service quality variables positively influence student satisfaction among students of universities in Thailand.

6.2 Recommendations

After the analysis of the survey of all the collected data, we can conclude that these service quality variables have significant relationships with the overall satisfaction of the graduate students who were studying in universities in Thailand. The service quality

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variables and student satisfaction have a moderately positive correlation which means there is still room for continuous improvement. The university may try to focus and put more effort on the service quality variables like non-academic aspects, and program issues because they have the lowest mean scores.

Non-academic aspects consisted of items related to duties of carried out by non-academic staff. The university may try to increase the quality of the performance of the non academic staff, perhaps by performance appraisal or other performance reviews.

Program issues consisted of items like wide range of specialization program, flexible program structure, quality counseling services etc. In our research, this variable has the lowest mean score. So, there is space for improvement. If we see table 5.1.11 we can find the items like „university operates excellent counseling‟ service has a lower mean score i.e. 3.26 which is near the neutral level. These are areas where the university can make some improvements to increase the satisfaction level of the students more. They might try to provide various counseling services about career, education, and perhaps finance or others issues. Universities should provide a wide range of specialization programs and other program with flexible structure, which gives more options for students to enroll.

The university should also consider focusing on the other variables since other variables like academic aspects, reputation and design delivery and assessment, as they are important variables for influencing the satisfaction level. As this survey was conducted among graduate students, graduate students are more likely to have higher expectations of service quality variables such as academic aspects, reputation of the college, as well as

88

program issues, like offering a wide range of programs, design, delivery and assessment, which influence their satisfaction.

Group size and access also have good mean score. But group size has weak positive correlation and access has low to moderate positive correlation with the satisfaction of the students. Graduate students may consider less about the class timing, class size for their satisfaction but still there is a positive correlation. So, universities should also consider the items like class timing, class enrollment size, approachability, ease of contact with academic and non-academic staff to improve service quality and student satisfaction.

In this globalized world economy, every business organization is competing with many other business organizations throughout the world in their relevant fields. It is same with the universities; they are competing not only with the domestic universities, but also with the universities all around the world. They are not attracting the domestic students but also the foreign students. Thus, high service quality and student satisfaction plays a crucial role for universities to remain in the fast track race, to attract more new students, and for the success of the organization. From this research we can infer that the higher the service quality, the higher the student satisfaction.

6.3 Suggestions for Further Research

This study was developed based on the study of Firdaus (2005) “The development of

HEdPERF: a new measuring instrument of service quality for higher education” with additional variables from Afjal et al. paper “On student perspective of quality in higher education”. This research focuses on finding the relationship between service quality

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variables and overall student satisfactions among graduate student of universities in Thailand, and also tries to answer the research questions: “Does payment by other and payment by self influence satisfaction?” And “Are there any differences in perception of satisfaction in terms of other demographic factors?”

Future research can be conducted by adding other service quality variables that influence student satisfaction. This study only finds the satisfaction of the student with the universities service quality. Researchers may also try to expand this study by finding student intentions to stay in the university and also recommendations about the university, as advocacy is often used as a form of loyalty measure.

The survey was conducted only among graduate students; future studies may change target population from graduate students to undergraduates or mix both and compare.

Students studying all categories of university were surveyed. Future studies might be conducted being more specific with only one category of academia, or more detailed comparisons might be explored between public and private universities.

The future research may be tested in other countries of Asia or outside Asia and try to find out if the findings are similar.

Due to time and budget constraints the survey was limited within Bangkok and the universities which are near Bangkok with sample size of 303. For future studies, researchers might expand the scope of the survey and larger sample size.

As the questionnaires were conducted only in English, Non- English speaking students were not surveyed. Thus, the researcher may also conduct their survey in English

90

languages vs. Thai language questionnaires, although this raises potential issues with

translation and measurement equivalency.

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APPENDIX I

Questionnaire

This survey is used in partial fulfillment of Master Degree of Business Administration, Webster University Thailand. This survey is completely anonymous and confidential. Your responses are a critical part of my research. Please answer all the questions as candidly and completely as possible. Thank you for your time.

Screening Question:

Are you currently studying in Master‟s Program in Thailand?

o Yes

o No

(If, No. Thank you. Have a nice day)

Section A

These Sections are related to certain aspects of the service that you experience in your University. Please mark the appropriate response to indicate your own personal feeling by circling based on the following scale

1= strongly disagree

2=disagree

3=neutral

4= agree

5= strongly agree

1

2

3

4

5

1.

When I have a problem, administrative staff show a

sincere interest in solving it

2.

Inquiries are dealt with efficiently

3.

The university has a professional image

4.

Instructor allocate sufficient time for consultation

5.

Teaching Methodology is appropriate.

6.

Instructor are highly educated in their respective fields

7.

The timing of the class is suitable

8.

The staff respect rule of confidentiality when I

disclose information to them

9.

Instructor is never too busy to respond to my request

for assistance.

10.

Instructor show positive attitude towards students

11.

When the staff promise to do something by a certain

time, they do so

12.

Administrative staff have good knowledge of the

systems

13.

The staff are easy to contact

14.

The university operates an excellent counseling

service

15.

When I have a problem, Instructor shows a sincere

interest in solving it.

16.

Administrative staff provide caring attention

17.

The handouts are provided adequately by the

Instructor.

18.

The documentations are provided adequately by the

Instructor.

19.

Curriculums designed by the university are up to date.

20.

Small class size helps the class make more interactive.

21.

A smaller the class size helps student better

understand

22.

The proportion between theory and practice are

appropriate

23.

The assessment and the grading by the instructor are

fair.

24.

The number of students enrollment in one class is

small

25.

Administration offices keep accurate and retrievable

records.

26.

The university offers programs with flexible structure

27.

Administrative staff shows positive work attitude

towards students

28.

The academic program run by the university is

reputable

29.

Instructor has the knowledge to answer my questions

relating to the course content.

30.

Instructor deals with me in a courteous manner.

31.

Administrative staff communicates well with students

32.

The university‟s graduates are easily employable

33.

Students are treated equally by the staff

34.

The university runs excellent quality programs

35.

The university offers a wide range of programs with

various specializations

36.

Instructor communicate well in classroom

37.

Instructor provide feedback about my progress

38.

Overall, I am satisfied with the university

• Would you recommend your university to others?

Definitely recommend