In this chapter, it mainly described the findings of each hypothesis in this study.
The result of descriptive statistics, correlation analysis, and hierarchical regression analysis was stated as follows
Descriptive Statistics
The demographic information in descriptive statistics was collected from 249 employees in different technology companies. The descriptive statistics was divided into 10 questions including age, gender, education, position, company type, department, tenure in present company, total tenure in career, annual income, and communicating with foreigners at work. Table 4.1 shows frequency, percentage, and details of demographic information.
Age
Among 249 participants, 32 participants (12.9%) aged below 25 years old, 98 participants (39.3%) aged from 26 to 30 years old, 72 participants aged from 31 to 35 years old, 38 participants aged from 36 to 40 years old, and 9 participants are above 41 years. participants in this study mainly aged from 26 to 30 years old.
Gender
Among 249 participants, there were 81 female participants (32.5%) and 168 male participants (67.5%). participants in this study were primarily female.
Education
Among 249 participants, 14 participants (5.6%) graduated from high school, 121 participants (48.6) got bachelor degree, 111 participants (44.6%) obtained master degree, and 3 participants (1.2%) gained doctoral degree. In this study, participants with bachelor degree were majority.
Position
Among 249 participants, there were 216 participants (86.7%) who worked as first-line employees, 28 participants (11.3%) was manager in basic level, and 5 participants (2%) worked as managers in middle level. Participants who worked as first-line employees were the majority.
Department
Among 249 participants , 14 participants (5.6%) worked in production department, 135 participants (54.2%) worked in research and development (R&D), 13 participants(5.3%) worked in the department of quality management, 22 participants (8.8%) worked in sales department, 9 participants (3.6%) worked in procurement department, 19 participants(7.6%) worked in human resource (HR) or administration department, 4 participants(1.6%) worked in marketing or planning department, 2 participants (0.9%) worked in accounting or finance department, 5participants (2%) worked in the department of strategic planning, 6 participants (2.4%) worked in the department of information technology (IT), and the rest of 20 participants (8%) worked in other departments. The majority of participants in this study worked in the department of research and development.
Tenure in Present Company
Among 249 participants 197participants (79.1%) were in the range from 1 to 5 years, and participantswho worked below 1 year in present company were also included. 39 participants (15.6%) were in the range from 6 to 10 years, 12participants (4.8%) were in the range from 11 to 15 years, and the rest of one participant (0.4%) worked more than 16 years in present company.
Total Tenure in Career
Among 249 participants, 119 participants (47.8%) were in the range from 1 to 5 years, and participants who worked below 1 year in present company were also
(15.7%) were in the range from 11 to 15 years, 10 participants (4%) were in the range from 16 to 20 years, 3 participants (1.2%) were in the range from 21 to 25 years, and the rest of one participant(0.4%) worked more than 16 years in present company.
Annual Income
Among 249 participants, 215 participants (86.3%) earned below 1,000,000 NT dollars per year, 30 participants (12.1%) earned from 1,000,001 to 1,500,000 NT dollars per year, and 4 participants (1.6%) earned more than 1,500,001 NT dollars per year.
The Department Having the Need of Using English
In this part, all the items were designed to be multiple choices. 71 participants (29%) marked production department, 112 participants (45%) marked research and development (R&D), 64 participants (26%) marked the department of quality management, 130 participants (52%) marked sales department, 100 participants (40%) marked procurement department, 59 participants (23%) marked human resource (HR) or administration department, 88 participants (35%) marked marketing or planning department, 46 participants (18%) marked accounting or finance department, 73 participants (29%) marked the department of law and intellectual property, 62 participants (25%) marked department of strategic planning, 55 participants (22%) marked the department of information technology (IT), 2 participants (0.008%) marked other departments. The majority of participants in this study marked the department of research and development as the department requires to use English during the work.
The Situation Requiring Using English in the Company
In this part, all the items were designed to be multiple choices as well. 227 participants (91%) marked emailing, researching information, or communicating through Internet, 171 participants (68%) marked presentation and speech, 182 participants (73%) meeting and customer service by phone, 125 participants (50%)
marked reception and attending social occasion, 146 participants (59%) marked attending conference and exhibition, 130 participants (52%) marked business trip and events planning, 183 participants (73%) marked writing report and making document.
The majority of participants in this study marked emailing, researching information, or communicating through Internet as the situations that need to use English during the work.
Table 4.1
Descriptive Statistics
(continued)
Item Frequency Percentage Item Frequency Percentage
1. Age 6. Department
Table 4.1 (continued)
(continued)
Item Frequency Percentage
9. Annual income
Below NT $1,000,000 215 86.3
NT $1,000,001- NT $1,500,000 30 12.1
Above NT $1,500,001 4 1.6
Total 249 100
10.The department having the need of using English
Production 71
Research & development 112
Quality management 64
Sales 130
Procurement 100
Human resource /Administration 59
Marketing/Planning 88
Accounting/Finance 46
Law / Intellectual property 73
Strategic Planning 62
Information technology 55
Others 2
Table 4.1 (continued)
Correlation Analysis
Correlation analysis aimed to examine the correlation among age, gender, education, position, TOEIC score (English language proficiency), employability, two dimensions of employability (internal employability and external employability) and language anxiety. Table 4.2 shows mean score, standard deviation, reliability, and Pearson correlation coefficients of variables mentioned above. It showed that TOEIC score positively and significantly correlated to employability (r=.19, p<.01, internal employability (r=.18, p<.01), and external employability (r=.17, p<.01). Language anxiety negatively and significantly correlated to employability (r=-.49, p<.01), internal employability (r=-.23, p<.01), and external employability (r=-.20, p<.01).
The correlation among control variables, independent variable, dependent variable, and moderator showed that age positively and significantly correlated to employability(r=.13, p<.05) and internal employability (r=.16, p<.05). Gender positively and significantly correlated to employability(r=.13, p<.05) and internal employability (r=.17, p<.05). Besides, gender negatively and significantly correlated to TOEIC score (r=-.12, p<.05). Education positively and significantly correlated to
Item Frequency
11.The situation requiring using English in the company
Emailing/ Researching information/ Communicating through Internet 71
Presentation / Speech 112
Meeting / Customer service by phone 64
Reception / Attending social occasion 130
Attending conference / Exhibition 100
Business trip / Events planning 59
Writing report / Making document 88
TOEIC score (r=37, p<.01). Position positively and significantly correlated to TOEIC score (r=.15, p<.05), employability (r=.33, p<.05), internal employability(r=.36, p<.01), and external employability(r=.26, p<.01). To sum up, age, gender, position positively and significantly correlated to employability and internal employability.
Position positively and significantly correlated to external employability
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Table 4.2
Mean, Standard Deviations, Correlations, and Reliability (n=249)
Note. Numbers in parentheses represent Crobach’s alpha value. **p<.01 *p<.05
Mean S.D. 1 2 3 4 5 6 7 8
1. Age 31.16 5.15
2. Gender 0.67 0.47 .05
3. Education 3.41 0.62 -.14* .20**
4. Position 1.15 0.41 .48** .05 -.03
5. Language Anxiety 3.20 0.55 -.09 -.02 -.24** -.10 (.93)
6. Employability 3.71 0.44 .13* .13* .00 .33** -.23** (.85)
7. Internal Employability 3.67 0.54 .16* .16* .00 .36** -.20** .87** (.73)
8. External Employability 3.74 0.45 .09 .08 .00 .26** -.21** .94** .64** (.79)
9. English Language Proficiency 556.93 142.17 .01 -.12 .37** .15* -.49** .19** .18** .17**
Hierarchical Regression Analysis Language Anxiety and Employability
Hypotheses on the relationship between language anxiety; sub-dimensions (internal employability and external employability) and main dimension of employability were examined by manipulating hierarchical regression analysis and the results are shown in Table 4.4. First, control variables (age, gender, education, and position) were added in the hierarchical regression analysis, and then independent and dependent variables were added in the second step. Hypothesis 1 describes language anxiety negatively related to employability, internal employability and external employability. The result shows that language anxiety negatively related to employability (β=-.17, p<.001), internal employability (β=-.18, p<.01) and external employability (β=-.17, p<.01). Therefore, Hypothesis 1, 1a, and 1b were supported.
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Table 4.3
Results of Hierarchical Regression Analysis between Language Anxiety and Employability
Note. ***p<.001 **p<.01 *p<.05
Moderating Effect of English Language Proficiency
Hypothesis 2 presumed English language proficiency had positive effect on the relationship between language anxiety and employability. Three steps were conducted during manipulating hierarchical regression analysis. First, control variables such as age, gender, education, and position were added in the analysis. Second, language anxiety and English language proficiency were added at the second level of hierarchical regression analysis. Third, the product of language anxiety and English language proficiency were added at the third level in the analysis. Table 4.5 shows the result of moderating effects of English language proficiency. Model 1 to Model 3 present English language proficiency positively and significantly correlated to the relationship between language anxiety and employability because the beta coefficient Variable
Employability Internal Employability External Employability
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6
was increased positively (β=-.001, p<.05) and remained significantly.
Moreover, in order to examine the moderating effect of English language proficiency on the relationship among language anxiety and two sub-dimensions of employability, internal employability and external employability, the same steps were utilized, but changed employability variable to internal employability and external employability variables. Therefore, Model 3 to Model 6 shows English language proficiency positively correlated to the relationship between language anxiety and internal employability because the beta coefficient was increased positively at the significant level of .05 (β=-.001). Model 7 to Model 9 indicates English language proficiency positively and significantly related to the relationship between language anxiety and external employability because the beta coefficient was increased positively (β=-.001, p<.05) and remained significantly. Thus, only Hypothesis 2 and 2b were supported.
Table 4.4
The Result of Hierarchical Regression on Moderating Effect (n=249)
Note. ***p<.001 **p<.01 *p<.05
Variable
Employability Internal Employability External Employability
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8 Model 9
β β β β β β β β β
Step 1
Constant 3.39*** 3.88*** 3.91*** 3.16*** 3.63*** 3.66*** 3.52*** 4.02*** 4.06***
Age -.00 -.01 -.01 -.00 -.00 -.01 -.00 -.01 -.00
Gender .11 .14* .15** .17* .21** .22** .07 .10 .11
Education -.01 -.08 -.08 -.02 -.10 -.09 -.01 -.07 -.07
Position .36*** .33*** .34*** .47*** .43*** .44*** .30*** .27*** .27***
Steps 2:
Language anxiety -.13* -.16** -.13* -.14* -.13* -.14*
ELP .00 .00 .00 -.00 .00 .00
Steps 3:
LA x ELP -.001* -.001 -.001*
R2 .12 .17 .19 .15 .19 .20 .07 .12 .14
Adjusted R2 .11 .15 .17 .13 .17 .17 .06 .10 .11
F 8.36*** 8.49*** 8.01** 10.57*** 9.37*** 8.41** 4.81** 5.49*** 5.41***
∆R2 .12 .05 .015 .15 .041 .01 .07 .05 .02
∆F 8.36*** 7.83** 4.39* 10.57*** 6.09** 2.30 4.81** 6.43** 4.43*
In order to explain the moderating effect deeply, English language proficiency was divided into two groups via utilizing mean score. Figure 4.1 shows product graph among language anxiety, employability, and English language proficiency. Figure 4.2 reveals interactional graph among language anxiety, external employability, and English language proficiency. Moreover, the summary of hypotheses testing is shown as Table 4.5.
Figure 4.1 Product plots for moderating effect of English language proficiency (Employability as Y Axis)
Figure 4.2 Product plots for moderating effect of English language proficiency (External Employability as Y Axis)
Table 4.5
Result of Hypotheses Testing
Hypotheses Explanation Result
Hypothesis 1.
Hypothesis 1a
Hypothesis 1b
Language anxiety negatively relates to employability.
Language anxiety negatively relates to internal employability
Language anxiety negatively relates to external employability
Supported
Supported
Supported
Hypothesis 2.
Hypothesis 2a
Hypothesis 2b
English language proficiency positively moderates the relationship between language anxiety and employability
English language proficiency positively moderates the relationship between language anxiety and internal employability
English language proficiency positively moderates the relationship between language anxiety and external employability
Supported
Not Supported
Supported