The following chapter contains two sections. The first section includes an overview of the descriptive statistics of the research data. The second section introduces the results of the PLS findings, including the descriptive statistics, result of validity and reliability, Cronbach’s Alpha and the test of hypotheses. The suggestions and recommendations are derived from the results exposed on this chapter.
Sample Characteristics
The characteristics of the sample are presented in table 4.1 in terms of study program, area of university, type of university, length of time in Taiwan, region of nationality, gender, financial support, English ability and Chinese ability. The majority of participants are currently enrolled in a Master’s degree with (52.75%), followed by bachelor degree with (28.44%) and in third place postgraduate or doctorate degree with (11.01%). In terms of the area of university where the participants are currently studying, most of the participants are from northern Taiwan with (77.06%) followed by southern Taiwan with (12.39%), central Taiwan with (7.80%) and the remaining which pertain to eastern Taiwan constitute only (2.75%). For the type of university, the participants from the study are attending the majority are from public universities (78.44%) and the rest are from the private sector (21.56%). Concerning their length of time studying in Taiwan, the majority of respondents belong to the category of 1-2 years (35.32%), followed by less than one year with (24.31%). Regarding their region of nationality, the majority of participants are from Central America and South America with (50.46 %), followed by Asia and Pacific (25.23 %), Europe (8.71%), Africa (6.88%), Caribbean (5.05%) and North America (3.67%). In terms of Sponsorship, the majority of participants have a TaiwanICDF scholarship with (29.82%), followed closely by university scholarships with (26.15%), Self- sponsored (22.48%), MOFA scholarships with (16.15%), and lastly MOE with (5.05%). The majority of respondents were female but not significantly higher (51.38%) while men have (48.62%). Concerning the English language ability, the majority of participants rated themselves as excellent for English listening ability with (62.84%), followed by a rating of Good (32.57%), and lastly average with (4.13%). In terms of Chinese language ability, most participants rated themselves as poor with (39.45%), Chinese speaking ability as average with (30.28%), a rating of good (19.27%) and excellent (9.63%).
Table 4.1.
46
Characteristics of Sample Population Based on Demographic (N =218)
Variables Entries Percentage
Study program Mandarin study 14 6.42%
Exchange program 3 1.38%
Bachelor 62 28.44%
Master degree 115 52.75%
Postgraduate degree 24 11.01%
Area of University North Taiwan 168 77.06%
Central Taiwan 17 7.80%
Region of nationality Central and South America 110 50.46%
North America 8 3.67%
Europe 19 8.71%
Africa 15 6.88%
Asia and Pacific 55 25.23%
Caribbean 11 5.05%
Sponsorship TaiwanICDF 65 29.82%
Taiwan MOFA 36 16.51%
Sponsorship Taiwan MOE 11 5.05%
University scholarship 57 26.15%
Self- sponsored 49 22.48%
Gender Female 112 51.38%
Male 106 48.62%
(continued)
Table 4.1. (continued)
47 Variables
Entries Percentage
English ability Excellent 137 62.84%
Good 71 32.57%
This section provides a summary of the results from the questions gathered for the study.
In order to get a general description of the basic features of the date, this research uses descriptive statistics. It helps researcher show how relevant and important the study is. It provides basic information of samples to make people easily understand where the data come from.
All the variables are measured with a 5-point Likert’s scale. The participants were instructed to indicate their level of agreement or disagreement with each of the statements with anchors ranging from 1 (Totally disagree) to 5 (Agree completely). Each table shows the mean and standard deviation for every item question.
Findings: Cultural Orientations.
Table 4.2 shows that regarding cultural orientations, the students showed a high level of agreement on the section of uncertainty avoidance (CO_UA) the highest value being (4.24), which stated that ‘Instructions for classwork and homework are important’. This indicates that the majority of the respondents have high degree uncertainty avoidance. For the section of power distance (CO_PD), the students also display a low level of agreement hence a low level of power distance with the highest score being (2.28). Lastly for the sub dimension of individualism/collectivism (CO_CI) the students display a relatively low score for collectivism, the highest item being ‘Students should stick with their team even through difficulties’ with a score of (3.40) all of the other items fall below the score of 3.
Table 4.2.
Cultural Orientations; Likert’s Scales, Mean, and SD; (N= 218)
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Survey Questionnaires Mean SD
CO_PD1 Faculty should make most decisions in the classroom without consulting students.
2.00 0.95 CO_PD2 Faculty should not ask the opinions of students too frequently. 2.23 1.08 CO_PD3 Students should not disagree with the decisions made by
Faculty.
2.09 0.94 CO_PD4 Faculty should not delegate important tasks to students. 2.28 0.97 CO_CI1 Students should stick with their team even through difficulties. 3.40 1.05 CO_CI2 Students should only pursue their goals after considering the
welfare of their classmates.
2.73 1.04 CO_CI3 Classmates’ welfare is more important than individual
rewards.
2.89 1.00 CO_CI4 Faculty should encourage group loyalty even if individual
goals suffer.
2.94 1.04 CO_UA1 It is important to have classwork instructions spelled out in
detail so that I always know what I’m expected to do.
3.82 1.00 CO_UA2 It is important to closely follow classwork instructions and
procedures.
3.78 0.88 CO_UA3 Rules and regulations in the classroom are important because
they inform me of what is expected of me.
3.98 0.83 CO_UA4 Instructions for classwork and homework are important. 4.24 0.85
Note. N= 218 SD= Standard Deviation; CO_CI= Collectivism/individualism; CO_MF= Masculinity/
Femininity; CO_PD= Power distance; CO_UA= Uncertainty avoidance Findings: University Culture.
Table 4.3. shows that all of the items for this variable surpass the (3.0) value mean regarding university culture, the students showed a high level of agreement on the item of managing change (UC_MC), which stated that ‘In my university/program my classmates, professors and staff are flexible and adaptable when changes are necessary’, with a score of (3.50). Followed by an item of the same section ‘In my university/program we constantly stretch our goals to continuously improve’ with (3.39) in third place there are two items from the same section Achieving Goals (UC_AG) with the same value (3.37), ‘In my university/program individuals and teams have clearly defined goals that relate to the goals of the program’ and ‘In my university/program individuals and teams are measured and rewarded according to how well goals are achieved’. Whereas, the lowest item belongs to the section Coordinated Teamwork (UC_CTW), with (3.04). This concludes that the respondents displayed some degree of agreement towards their university culture, since their response commonly ranged from neutral
49 to agree.
Table 4.3.
University Culture; Likert’s Scales, Mean, and SD; (N= 218)
Survey Questionnaires Mean SD
UC_MC1 In my university/program my classmates, professors and staff are flexible and adaptable when changes are necessary.
3.50 1.06 UC_MC2 In my university/program we constantly stretch our goals to
continuously improve.
3.39 1.02 UC_MC3 In my university/program people have a clear idea of why and
how to proceed throughout the process of change.
3.18 1.00 UC_AG1 In my university/program individuals and teams have clearly
defined goals that relate to the goals of the program.
3.37 1.00 UC_AG2 In my university/program individuals and teams are measured
and rewarded according to how well goals are achieved.
3.37 0.99 UC_AG3 In my university/program everyone knows and understands
our academic objectives and priorities.
3.26 0.98 UC_CTW1 In my university/program people value and make use of one
another's unique strengths and different abilities.
3.16 1.10 UC_CTW2 In my university/program people believe in teamwork, the
"what's in it for us" approach rather than "what's in it for me."
3.04 1.03 UC_CTW3 In my university/program people know what is expected of
them and understand their impact on other people, teams and functions.
3.30 0.96
UC_CTW4 In my university/program people believe in working together collaboratively, preferring cooperation over competition.
3.24 1.10 UC_CUST1 In my university/program people believe that their concerns
and anxieties during periods of change are heard and taken into consideration.
3.15 1.04
UC_CUST2 In my university/program everyone strongly believes in a set of shared values about how people should work together to solve common problems and reach mutual objectives.
3.34 0.98
UC_CUST3 In my university/program people have access to timely and accurate information about what's happening in the institution and why.
3.09 1.13 UC_CUST4 In my university/program academic decisions are most often
made based on facts, not just perceptions or assumptions.
3.37 0.96
Note. N= 218 SD= Standard Deviation; UC_AG= Achieving Goals; UC_CUST= Cultural Strength;
UC_CTW= Coordinated Teamwork; UC_MC= Managing Change Findings: Academic Motivation.
Regarding the variable of academic motivation, the respondents display a higher agreement with the item ‘For the pleasure that I experience while I am surpassing myself in one of my
50
personal accomplishments’ from the section of Intrinsic motivation to accomplish (AM_IMTA) with a value of (4.12). The second highest item corresponds to intrinsic motivation to know (AM_IMTK) ‘because my studies allow me to continue to learn about many things that interest me’ with a value of (4.11). Coming third is the item from the same category ‘For the pleasure that I experience in broadening my knowledge about subjects which appeal to me’ and the item from the category of extrinsic motivation identified regulation (AM_EMID) ‘because I think that a college education will help me better prepare for the career I have chosen’ both with (4.10) mean value. The lowest item pertains to the category of intrinsic motivation to experience stimulation (AM_IMES) ‘for the pleasure that I experience when I feel completely absorbed by what certain authors have written’ with a mean value of (3.41). The respondents display a slightly higher agreement towards intrinsic motivation. In this case, we can see that the results of the mean for all the constructs for knowledge sharing were higher than the average or over 3 mid- point of mean.
Table 4.4.
Academic Motivation; Likert’s Scales, Mean, and SD; (N= 218)
Survey Questionnaires Mean SD
AM_IMTK1 Because I experience pleasure and satisfaction while learning new things.
4.07 0.84 AM_IMTK2 For the pleasure that I experience in broadening my
knowledge about subjects which appeal to me.
4.10 0.80 AM_IMTK3 Because my studies allow me to continue to learn about
many things that interest me.
4.11 0.86 AM_IMTA1 For the pleasure that I experience while I am surpassing
myself in one of my personal accomplishments.
4.12 0.76
(continued)
Table 4.4. (continued)
Survey Questionnaires Mean SD
51
AM_IMTA2 For the satisfaction I feel when I am in the process of accomplishing difficult academic activities.
3.91 0.92 AM_IMTA3 Because college allows me to experience a personal
satisfaction in my quest for excellence in my studies.
3.86 0.90 AM_IMES1 For the intense feelings I experience when I am
communicating my own ideas to others.
3.58 0.98 AM_IMES2 For the pleasure that I experience when I feel completely
absorbed by what certain authors have written.
3.41 1.05 AM_IMES3 For the feeling that I experience while reading about various
interesting subjects.
3.81 0.89 AM_EMID1 Because I think that a college education will help me better
prepare for the career I have chosen.
4.10 0.90 AM_EMID2 Because eventually it will enable me to enter the job market
in a field that I like.
4.08 0.87 AM_EMID3 Because I believe that a few additional years of education
will improve my competence as a worker.
3.98 0.97 AM_EXIN1 Because of the fact that when I succeed in college I feel
important.
3.47 1.13 AM_EXIN2 To prove to myself that I am capable of completing my
college degree.
3.53 1.14 AM_EXIN3 Because I want to show myself that I can succeed in my
studies.
3.63 1.08 AM_EMER1 Because with only a high-school degree I would not find a
high-paying job later on.
3.90 1.03 AM_EMER2
In order to obtain a more prestigious job. 4.06 0.97 Note. N= 218 SD= Standard Deviation; IM_TK= Intrinsic motivation to know; IM_TA= Intrinsic motivation to accomplish; IM_ES= Intrinsic motivation to experience simulation; EM_ID=
Identified Regulation; EM_IT= Introjected regulation; EM_ER= External regulation Findings: Academic Satisfaction.
In regards of the variable of academic satisfaction Table 4.5 displays the mean and standard deviation of the data collected. The highest value mean from this construct is the item of the sub dimension academic programs (AS_AP) ‘Academic staff are highly educated’ with a mean value of (4.12). It is followed by the item ‘My university has professional appearance/image’ from the sub dimension of tangibles (AS_TA) with (3.93). The third highest item pertains to ‘Academic facilities are adequate. (classrooms, study rooms, library, etc.…)’ from academic feedback (AS_AF) with (3.90). On the contrary the item with the lowest mean value belongs to ‘Academic
52
staff (professors, lecturers, administrative, etc.) provide feedback about my progress’ from academic feedback (AS_AF) with (3.26).
To conclude the analysis of this variable, all of the items can be observed above a mean value of 3.2, surpassing the mid-point of 3 neutral from the Likert’s scale which demonstrates the students moderate academic satisfaction.
Table 4.5.
Academic Satisfaction; Likert’s Scales, Mean, and SD; (N= 218)
Survey Questionnaires Mean SD
AS_RAS1 Academic staff (professors, lecturers) communicate well in the classroom.
3.39 1.04 AS_RAS2 Academic staff (professors, lecturers) show positive attitude
towards students.
3.86 0.88 AS_RAS3 Academic staff (professors, lecturers) have the knowledge
to answer my questions.
3.88 0.88 AS_AF1 Academic facilities are adequate. (classrooms, study rooms,
library, etc.…)
3.90 1.01 AS_AF2 Academic staff (professors, lecturers, administrative, etc.)
allocate convenient time for consultation.
3.69 0.97 AS_AF3 Academic staff (professors, lecturers, administrative, etc.)
provide feedback about my progress.
3.26 1.13 AS_EM1 When I have academic problems, academic staff
(professors, lecturers, administrative, etc.) show sincere attitude/involvement.
3.63 1.05
AS_TA1 My university has an ideal location with excellent campus layout.
3.61 1.15 AS_TA2 My university has professional appearance/image. 3.93 0.98 AS_TA3 My university physical facilities are visually appealing. 3.60 1.10
AS_TA4 My university has up-to-date equipment. 3.54 1.13
(continued)
Table 4.5. (continued)
Survey Questionnaires Mean SD
53
AS_AD1 When I have a problem, administrative staff show sincere interest.
3.64 1.08 AS_AD3 Administrative staff have good knowledge of the systems. 3.72 0.99 AS_AP1 My university offers programs with flexible timetabling. 3.48 0.99 AS_AP2 My university offers highly reputable programs. 3.88 0.87
AS_AP3 Academic staff are highly educated. 4.12 0.89
AS_AP4 Complaints are dealt with efficiently. 3.39 1.08
Note. N= 218 SD= Standard Deviation; AS_AD= Administrative service; AS_AF= Academic feedback; AS_AP= Academic programs; AS_EM = Empathy; AS_RAS= Responsiveness academic staff; AS_TA= Tangibles
Discussion for Descriptive Statistics Analysis
Correlation Analysis.
A correlation analysis was performed to obtain a correlation matrix. The matrix was examined to detect if multicollinearity was present in the model. Multicollinearity occurs when two variables are closely correlated to one another, with a value above .75. It means that they are likely to be measuring the same construct. Although there might be collinearity between university culture and academic satisfaction it doesn´t reduce the predictive power or reliability of the model.
Table 4.6.
Correlation among All the Constructs
Constructs AM AS CO UC
AM 1 - - -
AS .359 1 - -
CO .421 .323 1 -
Note. N=218; AM= Academic Motivation; AS= Academic Satisfaction; CO=Cultural Orientations; UC= University Culture
Table 4.7.
Collinearity Statistic (VIF) among All the Constructs
54
Constructs AM AS CO UC
AM - 1.279 - -
AS - - - -
CO 1.000 1.240 - 1.000
UC - 1.121 - -
Note. AM= Academic Motivation; AS= Academic Satisfaction; CO=Cultural Orientations; UC=
University Culture
55 Table 4.8.
Correlation Analysis (N =218)
# Variable 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
1 CO_UA1 1
2 CO_UA2 .443 1
3 CO_UA3 .399 .596 1
4 CO_UA4 .334 .530 .628 1
5 UC_MC .092 .182 .182 .223 1
6 UC_AG .088 .193 .113 .171 .726 1
7 UC_CTW .107 .100 .062 .032 .652 .702 1
8 UC_CUST .073 .141 .089 .122 .623 .603 .680 1
9 AM_IMTK .200 .250 .239 .365 .222 .216 .134 .193 1
10 AM_IMTA .134 .257 .193 .279 .222 .257 .154 .192 .576 1
11 AM_IMES .005 .170 .206 .129 .199 .140 .104 .195 .465 .483 1
12 AM_EMID .297 .336 .368 .375 .320 .276 .164 .163 .434 .446 .252 1
13 AM_EXIN .116 .142 .185 .127 .147 .050 .077 .137 .202 .350 .277 .283 1
14 AM_EMER .165 .113 .161 .069 -.008 .058 .096 .025 .085 .135 .005 .344 .266 1
15 AS_RAS .186 .194 .186 .206 .621 .606 .577 .549 .263 .241 .109 .288 .074 .050 1
16 AS_AF .141 .294 .217 .191 .565 .546 .527 .580 .129 .246 .235 .289 .061 -.011 .543 1
17 AS_EM .118 .179 .176 .243 .519 .527 .539 .497 .159 .222 .070 .208 -.016 .031 .618 .562 1
18 AS_TA .122 .170 .190 .219 .471 .476 .412 .371 .274 .257 .163 .256 -.005 -.050 .426 .481 .371 1
19 AS_AD .097 .174 .135 .223 .589 .611 .568 .504 .234 .238 .127 .267 .098 .046 .660 .482 .628 .485 1
20 AS_AP .115 .197 .165 .225 .576 .539 .557 .581 .296 .272 .277 .286 .113 .017 .640 .547 .545 .596 .653 1
Note. UC_AG= Achieving Goals; UC_CUST= Cultural Strength; UC_CTW= Coordinated Teamwork; UC_MC= Managing Change;
CO_UA= Uncertainty avoidance; IM_TK= Intrinsic motivation to know; IM_TA= Intrinsic motivation to accomplish; IM_ES= Intrinsic motivation to experience simulation; EM_ID= Identified Regulation; EM_IT= Introjected regulation; EM_ER= External regulation;
AS_AD= Administrative service; AS_AF= Academic feedback; AS_AP= Academic programs; AS_EM = Empathy; AS_RAS=
Responsiveness academic staff; AS_TA= Tangible
56
Testing the Research Model
To assess the measurement model, this study uses Cronbach’s Alpha’s approach from Smart PLS. In table 4.9. most of the values of Cronbach’s Alpha from the constructs are higher than .70 (cultural orientations, university culture, academic motivation and academic satisfaction). The results also showed that the explanatory power of R2 for academic motivation is 18%, for university culture its 7% and for academic satisfaction it is 62%.
Table 4.9.
PLS Cronbach's Alpha, Internal Consistency and R2 in This Study
Constructs Number of interpreted as the standardized beta coefficient in the ordinary regression (Hair et al., 2006). Also, the t-value from bootstrapping procedure can be the significant value for each path coefficient.
Therefore, the relationship between two variables can be assessed. In this study, the bootstrapping 50x method was conducted to test the significance of the path coefficients, thus the research can examine the relationship between each variable. For this study, the five paths (academic motivation to academic satisfaction, cultural orientations to academic satisfaction, and cultural orientations to academic motivation, and university culture to academic satisfaction) proved to be significant.
From the perceptive of Hair et al. (2011), the t - values for two-tailed must be 1.65, 1.96 and 2.58, which characterize weak, moderate and strong significance. Table 4.10 demonstrates there is a moderate positive effect between academic motivation and academic satisfaction from international students (β =0.096, t = 2.019, p <.05), therefore null hypothesis 1 was rejected. It demonstrates there is a strong positive effect between Cultural orientations and academic motivation from the international students (β =0.421, t = 6.831, p < .001) thus, null hypothesis 2 was accepted. Cultural orientations have a moderate positive effect on the academic satisfaction
57
of international students (β =0.101, t = 2.305, p < .05). Consequently, null hypothesis 3 is rejected.
Cultural orientations have a strong effect as well on university culture (β =0.247, t = 3.731, p <
.05). Therefore, the null hypothesis 4 is rejected. University culture shows a strong positive effect on academic satisfaction (β =0.737, t = 20.424, p < .001). Thus, null hypothesis 5 is rejected as well. In conclusion, the entire research null hypotheses have been rejected.
Table 4.10.
PLS Hypotheses Testing Results (N=218)
Path Hº β-path Adj. t-value Sig. Direction Result
AM AS H1 0.096 2.019 ** + Rejected
CO AM H2 0.421 6.831 *** + Rejected
CO AS H3 0.101 2.305 ** + Rejected
CO UC H4 0.247 3.731 *** + Rejected
UC AS H5 0.737 20.424 *** + Rejected
Note. AM= Academic Motivation; AS= Academic Satisfaction; CO=Cultural Orientations; UC=
University Culture
* p < .1, ** p < .05, *** p < .001
Figure 4.1. displays the results of the structural model that can describe 4%, 19% and 65% of the variance in cultural orientations, academic motivation, university culture and academic satisfaction. The variance of the r-square, demonstrates the overall impact of the effect of the four variables. The coefficient of determination, R2 is 0.035 for university culture variable. This means that university culture is explained 4% of variance from cultural orientations. Which is a very logical result since; uncertainty avoidance sub dimension is very small to have a big influence on the students’ perception of university culture. For academic motivation the coefficient of determination, R2 is 0.189 which indicates that this variable is explained 19% of the variance by cultural orientations. Meanwhile for academic satisfaction the coefficient of determination, R2 is 0.654. This value shows that academic satisfaction is explained 65% of the variance from cultural orientations, academic motivation and university culture altogether.
58
Figure 4.1. PLS structural model (N=218).
Note: * p < .1, ** p < .05, *** p < .001
UNIVERSITY CULTURE R² = .061 Managing change .873***(45.384) Achieving goals .879***(42.633) Coordinated teamwork
.873***(34.142)
Cultural strength .833***(28.663)
ACADEMIC SATISFACTION R² = .649 Responsiveness academic staff .831***(31.307) ACADEMIC MOTIVATION R² = .178
Int. motiv. to know .777**(19.206) Int. motiv. to accomplish .797***(26.400)
Int. motiv. to experience stimulation .633***(8.561) Ext. motiv. identified regulation .767
***(19.889)
Ext. mot. introjected regulation .502***(5.453) Ext. motiv. external regulation .339***(3.716)
CULTURAL ORIENTATIONS Uncertainty avoidance .884***(11.107) Power distance.233*(0.972)
Individualism/collectivism .482***(2.172)
59
The table 4.11. represents the four most dominant and least dominant responses from international students studying in Taiwan in dealing with the effect of academic motivation, cultural orientations and university culture on academic satisfaction. The most dominant factor belongs to university culture in the managing change sub dimension with a value of (.873) which indicates this item is very strong in this scale. The least dominant factor from these variables belongs to the variable academic motivation and its sub dimension extrinsic motivation external regulation with a value of (.331).
Table 4.11.
Most Dominant and Least Dominant Responses (N =218)
Constructs Most Dominant Factor Score Least Dominant Factor Score
Note. AM= Academic Motivation; AS= Academic Satisfaction; CO=Cultural Orientations; UC=
University Culture
The path coefficient table 4.12. indicates the direct effect of all the variables that that are assumed to cause on another variable assumed to be an effect. The path coefficients are standardized because they are estimated from correlations (a path regressions coefficient is unstandardized). In this case, the path coefficients are demonstrating the relationships between the
The path coefficient table 4.12. indicates the direct effect of all the variables that that are assumed to cause on another variable assumed to be an effect. The path coefficients are standardized because they are estimated from correlations (a path regressions coefficient is unstandardized). In this case, the path coefficients are demonstrating the relationships between the