This chapter depicts the primary findings of the study. Firstly, this chapter illustrate the demographic characteristics of 204 participants. Secondly, it presents the study’s descriptive statistical analysis, correlation analysis and multiple linear regression analysis, the discussions of the research findings were also presented in this chapter.
Descriptive Analysis
In this study, a total 204 questionnaires were collected and corroborated. The majority of the participants were female between 23 – 26 years old (65.2%). Most of them hold a Bachelor’s Degree, which can be calculated as 73.5%. Among these participants, 57.4% of them have a 10 – 19 years English learning experience.
Additionally, the frequency of using English in daily life of these participants concentrated in occasionally, sometimes and frequently, the percentages are 25%, 25%
and 23.5% respectively (see table 4.1.).
Descriptive Statistic of English Learning Motivation
As presented in table 4.2., this table shows the mean and standard deviation of English learning motivation which was measured in 5-point Likert’s scale. Based on the result in the table. “Knowledge of the English will help me when I travel abroad”
has the highest mean score (M = 4.61) and “I always volunteer to answer the questions my language teacher asks in class” has the lowest mean score (M = 2.57), the standard deviation was calculated approximately 1.073.
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Sample Characteristics
Table 4.1.Demographic Characteristics of the Samples (N = 204)
Variable Category Frequency Percentage
Gender Male 71 34.8%
Female 133 65.2%
Age 19 – 22 years old 29 14.2%
23 – 26 years old 107 52.5%
Above 27 years old 68 33.3%
Educational Level Senior high school 17 8.3%
Bachelor 150 73.5%
Master & Doctor 37 18.1%
Years of learning English 0 – 9 years 57 27.9%
10 – 19 years 117 57.4%
Above 20 years 30 14.7%
Frequency of using
English Rarely 23 11.3%
Occasionally 51 25 %
Sometimes 51 25 %
Frequently 48 23.5%
Usually 31 15.2%
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Table 4.2.
Descriptive Statistic of English Learning Motivation (N = 204)
Code Items Mean Std. Dev.
Effort & Commitment 3.18 1.08
Effort &
Commitment 1
I am working hard at learning English. 3.13 1.08
Effort &
Commitment 2
I put great efforts to understand
everything my English teacher teaches us in class.
3.43 1.00
Effort &
Commitment 3
I always volunteer to answer the questions my English teacher asks in class.
2.57 1.09
Effort &
Commitment 4
I want to keep improving my English to reach next level.
3.73 1.15
Effort &
Commitment 5
If my English teacher wanted someone to do an extra assignment for the class, I would certainly volunteer.
3.05 1.10
Instrumental Motivation 4.26 0.97
Instrumental 1 Knowledge of English can be useful for my further studies.
4.17 0.97
Instrumental 2 Knowledge of the English will increase my job opportunities.
4.28 1.00
Instrumental 3 Proficiency in the English can bring me some financial benefits.
3.97 1.12
Instrumental 4 Knowledge of the English will help me when I travel abroad.
4.61 0.76
Instrumental 5 Knowledge of the English will be useful for my future career.
4.27 0.97
(continued)
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Table 4.2. (continued)
Code Items Mean Std. Dev.
Integrative Motivation 3.59 1.17
Integrative 1 I decided to study English because I am interested in the culture of English speaking countries.
3.51 1.14
Integrative 2 Studying English is important because it will enable me to better understand the way of life in English speaking
countries.
3.83 1.09
Integrative 3 Studying this language is important because it will enable me to appreciate the English art and literature.
3.66 1.17
Integrative 4 I decided to learn English in order to better understand the life style of English speaking countries.
3.37 1.26
Integrative 5 I decided to learn English so that I can get to know its speakers better.
3.60 1.19
This can be interpreted that most of the English learners in Taiwan have a strong motivation especially when they took English as a tool or skill to achieve certain goal, since the commitment and effort they put in English (M = 3.18) and Integrative motivation (M = 3.59) are relatively lower than instrumental motivation (M = 4.26).
Also, the socres of standard deviation were low, which validated the consistency of each question.
Descriptive Statistic of English Proficiency
In table 4.3., it shows the level of English of the participants, the mode of CEFR Level among respondents is B2 (26.5%). The respondents who got A1 and B1 in CEFR Level have the same percentage (20.6%) and the third level is A2 (18.1%). According to the analysis, it can be explained that in Taiwan most of English learner’s proficiency level are below advanced.
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Table 4.3.
Level of English Proficiency (N = 204)
Variable Category Frequency Percentage
EP A1 42 20.6%
Descriptive Statistic of English Learning System Usage
In table 4.4. and 4.5., it shows that among 204 participants, 117 of them have the ELS using experience, which is 57.4%. Additionally, among these 117 respondents who have used ELS before, most of the users have the experience less than 1 year (47.9%), the second level is 1 to 3 years (35.0%).
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Table 4.6. and table 4.7. depicted that English learners in Taiwan generally believed that ELS is more effective (56.9%) and interesting (56.9%) compared to traditional English teaching method. Moreover, from the respondents who have used ELS before, 62.4% of them consider it is more effective and 66.7% of them believed it is more interesting.
Table 4.6 .
General Attitudes on ELS (N = 204)
Effective Percentage Interesting Percentage
Yes 116 56.9% 123 60.3%
No 28 13.7% 22 10.8%
Neutral 60 29.4% 59 28.9%
Total 204 100% 204 100%
Table 4.7.
Attitudes from ELS Users (N = 117)
Effective Percentage Interesting Percentage
Yes 73 62.4% 78 66.7%
No 15 12.8% 9 7.7%
Neutral 29 24.8% 30 25.6%
Total 117 100% 117 100%
The Relationships Among All the Variables
The following approaches were utilized to examine the relationships between English learning motivation, English proficiency and English learning system by adopting correlation analysis and multiple linear regression. Firstly, correlation analysis was applied to test the degree of correlation among all of the three variables. Secondly, multiple linear regression was also conducted to test all of the three hypotheses of the study.
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Data Coding
To operate correlation analysis and multiple linear regression analysis in order to text the relationship among 3 variables, male was coded as 1 and female was 2, participants’ age between 19 – 22 were coded as 1, 23 – 26 years old as 2 and above 27 years old as 3. For educational level, senior high school was coded as 1, bachelor as 2, master and doctor as 3. 0 – 9 years of English learning experience was coded as 1, 10 – 19 years as 2, above 20 years as 3. Rarely using English was coded as 1, occasionally as 2, sometimes as 3, frequently as 4 and usually as 5. CEFR Level A1 to C2 were coded 1 to 6 respectively. If the participant has used English learning system, the answer was coded as 1, otherwise was 2. Less than 1 year experience on ELS was coded as 1, 1 – 3 years as 2, 4 – 6 years as 3 and more than 7 years as 4.
Correlation Analysis
In this study, Correlation Analysis was conducted to measure the relationships between independent variable, dependent variable and the moderator. The result has to range within -1 to +1 to show the validity of the study (Taylor, 1990). Table 4.8., illustrates the results of means and standard deviation and also the correlation coefficient among English learning motivation, English proficiency and English learning system. The (r) shows that gender and years of learning English has no significant relationship between all of the variables mentioned above as (r = -.011, p
< .05; r = .027, p < .05; r = -.120, p < .05; r = -.006, p < .05; r = -.050, p < .05; r = -.023, p < .05) respectively. However, Age and Frequency of using English does have significant influence with motivation, English learning system and CEFR, which represent English proficiency in this study, the table shows (r = -.182**, p < .05; r
= .155*, p < .05; r = -.240**, p < .05; r = .398**, p < .05; r = -.180**, p < .05, r = .553**, p < .05) respectively. Education also have significant influence with CEFR (r = .333**, p < .05) but did not show influence on both motivation (r = -.035, p < .05) and English learning system (r = -.018, p < .05). Furthermore, all three variables of the study are correlated with each other as Motivation and ELS (r =-.330**, p < .05), Motivation and CEFR (r = .358**, p < .05), ELS and CEFR (r = -.782**, p < .05). Hence, it can be determined that the Result of Correlation Analysis can be used in this study.
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Table 4.8.
Result of Correlation Analysis (N = 204)
M G Age YOE Edu. Fre Mot ELSU YELS CEFR
G 1
Age .164* 1
YOE .103 .173* 1
Edu. -.053 .071 .040 1
Fre -.045 -.116 .107 .150* 1
Mot -.011 -.182** -.006 -.035 .398** 1
ELSU .027 .155* -.050 -.018 -.180** -.330** 1
YELS .004 -.032 .125 .116 .301** .361** -.782** 1
CEFR -.120 -.240** -.023 .333** .553** .358** -.218** .230** 1 Note: *p < .05, **p < .01, M = measures, S.D. = standard deviation, G = gender, YOE = years of study English, Edu. = education, Fre. = frequency of using English, Mot = English learning motivation, ELSU = English learning system usage, YELS = years of using ELS, CEFR = the Common European Framework of Reference for Languages.
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Multiple Linear Regression
Multiple Linear Regression was conducted to examine the relationship between each variable, which are English proficiency and English learning motivation with the moderating effect of English learning system to test if it match 3 hypothesis or not.
English learning motivation and English proficiency
In this study, hypothesis 1 test the relationship between English learning motivation and English proficiency. To test the relationship, English proficiency was set as the dependent variable. According to table 4.9., R squared is .128, which explained 12.8% of the variation in English proficiency variable and F value is 29.656.
From the general outcome, it can be indicated that the relationship between English learning motivation and English proficiency is positively significant (p = .000). The result agrees with many previous studies proving that motivation does connect with performance (Stevenson & Lee, 1996; Yu, 1996; Zimmerman, 2008).
Table 4.9.
Multiple Linear Regression of ELM and EP (N = 204)
English Learning Motivation
Note: Independent Variable: English learning motivation, ***p<.001, **p < .01
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English learning system usage and English proficiency
Hypothesis 2 of this study was to examine the relationship between English learning system and English proficiency. To test the relationship, English proficiency was set as dependent variable. As stated in the report, 12.8% of the variation in English proficiency was explained variable and F value is 24.326. From the overall result, it can be interpreted that the relationship between English learning system and English proficiency is positively significant (p = .000). This result can relate to relevant researches that English learning system does connect with performance (Jarvela, 2016;
Koedinger & Aleven, 2007; Koedinger, Aleven, Roll, & Baker, 2009).
Table 4.10.
Multiple Linear Regression of ELSU and EP (N = 204)
English Learning System Usage
Note: Independent Variable: English learning system usage, ***p<.001, **p < .01
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English learning motivation, English learning system usage and English proficiency
Hypothesis 3 of this study tested the relationship between English learning motivation, English learning system and English proficiency. The relationship was examined by setting EP as the dependent variable; ELM and ELS as the independent variable. The outcome confirmed the moderating effect between ELM and EP was not significant (p = .900). Therefore, it shows that English learning system in this study does not moderate the relationship between English learning motivation and English proficiency.
Table 4.11.
Multiple Linear Regression of ELM, ELSU and EP (N = 204)
Model Variables β
Note: Independent Variable: English learning motivation, English learning system usage, ***p<.001, **p < .01
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Discussions
According to the result from analysis, hypothesis 1 and hypothesis 2 were supported, English learning motivation and English learning system usage are positively related to English proficiency. However, in this study, English learning system usage did not moderate the relationship between English learning motivation and English proficiency (See table 4.12.).
Table 4.12.
Summary of Results
Hypothesis Results
H1 English Learning Motivation has a relationship with
English Proficiency. Accepted
H2 English Learning System Usage has a relationship with
English Proficiency. Accepted
H3 English Learning System Usage moderates the
relationships between English Learning Motivation and English Proficiency.
Rejected
From the tables show above, the target of this study is to examine the relationships between three variables, which are English learning motivation, English learning system and English proficiency among Taiwanese who have English learning experience. It is confirmed that if English learners have a strong learning motivation, it will enhance their English proficiency since it takes consistant practice and proactive use to master a non-native language. The result was analyzed based on previous studies indicated that these variables were related to each other (Chi, Siler, Jeong, Yamauchi,
& Hausmann, 2001; Dörnyei, 1998; Graesser & McNamara, 2010; Kosek & Lison, 2014; Ono & Zavodny, 2007).
All the hypothesese were tested by conducting the descriptive analysis, correlation coefficient analysis and multiple regression analysis. Based on the analysis, in 204 respondents, only 29 (14.2%) of them have the advanced and proficient CEFR level.
However, the result still show that the stronger English learning motivation learner possess, the better English proficiency he can demonstrate (H1). Also, analysis supported thatlearner’s experience on using English learning system also affect the
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English ability (H2). Nonetheless, the moderating effect between English learning motivation and English proficiency (H3) was not significant according to the multiple regression analysis, it could be interpreted that the survey on English learning system in this study does not foucus on specific English learning system, which result in the discrepancy in each learners’ using experience.
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