The first section includes the results of pre-study questionnaires, where the

CHAPTER IV RESULTS

The experiment was conducted to examine if voice-based CMC in line with the text-based one is beneficial for language learners to improve their speaking ability. In the present study, there were 113 students (38 students in Gong; 38 students in Skype;

37 students in control group) participating in the program at first. For the experimental groups, nevertheless, the data is retrieved from those who completed all the topics and then is discussed in the results section. After the 8-week treatment, 32 (males: 32) students in Gong group, 34 students (males: 30; females: 4) in Skype, and 37 students (males: 35; females: 2) in control group are included in the result section.

The purpose of the study is to investigate (a) the effect of voice-based CMC on improving EFL learners’ oral proficiency; (b) the comparison of the effect voice-based SCMC and ACMC had on building EFL learners’ speaking ability; (c) the perception EFL learners’ have on voice-based CMC.

The first section includes the results of pre-study questionnaires, where the

participants’ English learning backgrounds along with their computer literacy were

described, and the results of inter-rater reliability in the current study. The second

section shows the answers to the three research questions as well as the results of

post-study questionnaire. Both descriptive and inferential statistics are adopted to

analyze the results.

4.1 Results of Pre-study Questionnaire and Inter-rater Reliability

For learners’ general language learning background, all the 113 students had learned English for 4.5 years on average. In regard to learners’ computer literacy, all students had been using computers for two years or longer and all had a home connection to the Internet. As Coniam and Wong (2004) pointed out, it is valid and important for a computer-based study that participants in the context of CMC are computer literate with the hardware in general. Results from the pre-study questionnaires showed that this pre-condition was satisfied.

As for inter-rater reliability, it played an influential role in the subjective testing

(oral test) since raters’ personal judgments were called for. Table 4.1 presents the

descriptive statistics and correlations between the two raters’ scorings. The resulting

correlation coefficient is .878 and also achieves the statistic significant level p<.05,

which shows the inter-rater reliability in pre-test and post-test.

Table 4.1: Inter-rater Reliability—Peterson’s Correlation Descriptive Statistics

Mean Std. Deviation

Rater1 42.3333 18.51064

Rater2 44.6667 17.75957

Correlations

Rater1 Rater2

Rater1 Pearson Correlation 1 .878**

Sig. (2-tailed) .000

Sum of Squares and

Cross-products 9936.667 8373.333

Covariance 342.644 288.736

* Correlation is significant at the .05 level

** Correlation is significant at the .01 level (2-tailed).

4.2 The Effect of Voice-based CMC on Oral Proficiency

In answering research question one, whether voice-based CMC can improve EFL learners’ oral proficiency, voice-based ACMC (Gong Group) learners’ performance in pretests and posttests as well as voice-based SCMC (Skype Group) learners’ was carefully examined.

4.2.1 Voice-based ACMC

First of all, Table 4.2 summarizes the mean scores and standard deviation (SD) for Gong group in pre- and post-tests. The mean score of Gong Group in the posttest (54.69) is higher than that of the pretests (39.38) by 15.31, indicating learners’

progress in oral proficiency. Besides, the standard deviation of the posttest (13.44) in

Gong Group is lower than that of posttest (13.66), which indicates the variance within

Gong Group is decreased after the voice-based ACMC treatment. Followed by the

basic descriptive statistics, the result of the ANOVA further shows that there is a significant difference between pretest and posttest. The effect of voice-based ACMC on improving EFL learners’ oral proficiency has reached the statistical significant level (p< .05).

Table 4.2

Gain Scores: Pre- and Post-tests in Gong Group—Results of One-Way ANOVA

Pre-Post Mean Std. Deviation N

Pretest (Gong) 39.38 13.66 32

Posttest (Gong) 54.69 13.44 32

Source

Type III Sum

of Squares df Mean Square F Sig.

Corrected Model 3751.56 1 3751.56 20.43 .000

Intercept 141564.06 1 141564.06 770.97 .000

pre_post 3751.56 1 3751.56 20.43 .000**

Error 11384.38 62 183.62

Total 156700.00 64

Corrected Total 15135.94 63 a R

= .248 (Adjusted R

= .236)

* p< .05 ** p< .01

In addition to the overall improvement on oral proficiency in Gong group,

participants’ performance of pronunciation & fluency and grammar & content in pre-

and post-test was examined respectively, further reporting the effect of voice-based

ACMC in detail. The total score (100) on the oral test in GEPT Elementary-Level is

points account for the grammar of learners’ speech productions. As can be seen in Table 4.3 and 4.4, the mean score of pronunciation in the posttest (31.56), compared with 19.06 in the pretest, reaches the significant level (p= .00), while the progress in grammar from pretest to posttest (p= .16) fails to indicate statistic significance (p< .05). In other words, the finding suggests that voice-based ACMC improve EFL learners’ oral proficiency, especially in the aspect of target language pronunciation and fluency.

Table 4.3

Gain scores of Gong in Pronunciation & Fluency—Results of One-Way ANOVA

pre_post Mean Std. Deviation N

Pretest (Gong_Pro) 19.06 6.89 32

Posttest (Gong_Pro) 31.56 7.23 32

Source

Type III Sum of

Squares df Mean Square F Sig.

Corrected Model 2500.00 1 2500.00 50.10 .000

Intercept 41006.25 1 41006.25 821.78 .000

pre_post 2500.00 1 2500.00 50.10 .000**

Error 3093.75 62 49.90

Total 46600.00 64

Corrected Total 5593.75 63

a R

= .447 (Adjusted R

= .438)

* p< .05 ** p< .001

Table 4.4

Gain Score Gong in Grammar & Content—Results of One-Way ANOVA

pre_post Mean Std. Deviation N

Pretest (Gong_Stru) 20.31 8.97 32

Posttest (Gong_Stru) 23.44 8.65 32

Source

Type III Sum of

Squares df Mean Square F Sig.

Corrected Model 156.25 1 156.25 2.01 .161

Intercept 30625.00 1 30625.00 394.03 .000

pre_post 156.25 1 156.25 2.01 .161

Error 4818.75 62 77.72

Total 35600.00 64

Corrected Total 4975.00 63

a R

= .031 (Adjusted R Squared = .016) 4.2.2 Voice-based SCMC

Subsequent to the outcomes of Gong program, Table 4.5 presents the results of

One-way ANOVA for performance of Skype Group in pre- and post-tests. The mean

score of Skype Group in the posttests is 50, which is higher than that in the pretests

(40.59). Furthermore, the results of the standard deviation in the posttest (13.71), in

accordance with what shown in voice-based ACMC, is lower than that of pretest

(14.96). The lower standard deviation after the treatment presumably implies that the

difference of learners’ target language proficiency within Skype Group was reduced

due to voice-based SCMC treatment. A significant main effect of voice-based SCMC

on improving EFL learners’ oral proficiency (F= 7.314, P= .009) is shown, achieving

the significant level (p< .05). The assumption that the practice of voice-based SCMC

could significantly improve EFL learners’ oral proficiency is positive.

Table 4.5

Gain Scores: Pre- and Post-tests in Skype Group—Results of One-Way ANOVA

Pre_Post Mean Std. Deviation N

Pretest (Skype) 40.59 14.96 34

Posttest (Skype) 50.00 13.71 34

Total 45.29 15.01 68

Source

Type III Sum of

Squares df Mean Square F Sig.

Corrected

Model 1505.88 1 1505.88 7.31 .009

Intercept 139505.88 1 139505.88 677.60 .000

Pre_Post 1505.88 1 1505.88 7.31 .009*

Error 13588.24 66 205.88

Total 154600.00 68

Corrected Total 15094.12 67

After confirming the positive effect of voice-based SCMC upon participants’

general oral proficiency, its influence on pronunciation as well as grammar is worth

further investigating. Table 4.6 and 4.7 present the gain score of Skype in

pronunciation and grammar respectively. In terms of pronunciation, learners in Skype

group significantly made progress (p=.005). However, the p-value of progress made

in grammar from pre-test to post-test is .068, which doesn’t reach the statistically

significant level (p< .05). Consistent with the result shown in Gong group,

voice-based SCMC has significant effect on EFL learners’ oral proficiency on the

aspect of pronunciation and fluency in particular.

Table 4.6

Gain Score of Skype Group in Pronunciation &Fluency—Results of One-Way ANOVA

pre_post Mean Std. Deviation N

Pretest (Skype_Pro) 20.29 6.74 34

Posttest (Skype_Pro) 25.59 8.24 34

Source

Type III Sum of

Squares df Mean Square F Sig.

Corrected Model 476.47 1 476.47 8.42 .005

Intercept 35788.24 1 35788.24 632.35 .000

pre_post 476.47 1 476.47 8.42 .005**

Error 3735.29 66 56.60

Total 40000.00 68

Corrected Total 4211.77 67

a R² = .113 (Adjusted R Squared = .100)

Table 4.7

Gain Score of Skype Group in Grammar & Content: Results of One-Way ANOVA

pre_post Mean Std. Deviation N

Pretest (Skype_gra) 20.29 10.29 34

Posttest (Skype_gra) 24.41 7.86 34

Source

Type III Sum of

Squares df Mean Square F Sig.

Corrected Model 288.24 1 288.23 3.43 .068

Intercept 33976.47 1 33976.47 405.12 .000

pre_post 288.24 1 288.24 3.44 .068

Error 5535.29 66 83.87

Total 39800.00 68

Corrected Total 5823.53 67

a R²= .049 (Adjusted R Squared = .035)

4.2.3 Control Group

To further examine the effect of voice-based CMC, the scores of the control group whose English input comes mainly from English classroom instruction are further analyzed. As shown in Table 4.10, the mean score of the control group in the posttest (40.81) is slightly higher than that in the pretest (40.27) by .054. However, based on the result of ANOVA, although the mean score in the posttest increased a little, the p-value was .019, which did not reach the significant level (p< .05). The outcome indicates that for those who received only the daily instruction in English, hardly could they make progress or even have significant improvement on English oral proficiency. The result also serves to filter out the potential variable, routine instruction in English, which may exist in the two experimental groups.

Table 4.8

Gain Scores: Pre- and Post-tests in Control Group—Results of One-Way ANOVA

pre_post Mean Std. Deviation N

Pretest (Control) 40.27 17.40 37

Posttest (Control) 40.81 16.05 37

Source

Type III Sum of

Squares df Mean Square F Sig.

Corrected Model 5.40 1 5.41 .019 .890

Intercept 121621.62 1 121621.62 434.08 .000

pre_post 5.41 1 5.41 .019 .890

Error 20172.97 72 280.18

Total 141800.000 74

Corrected Total 20178.378 73

With the above mentioned comparisons of learners’ performance between pre- and post-test, the answer to the first research question is positive. That is, the results of the present study suggest that compared with the control group, which receive no treatment in speaking ability, voice-based CMC can significantly enhance EFL learners’ general oral proficiency and the target language pronunciation and fluency in particular.

4.3 The Comparison of the Effects Voice-based ACMC and SCMC Have on

Learners’ Oral Proficiency

To answer question number 2, if learners in voice-based SCMC could

significantly outperform those in voice-based ACMC group with reference to EFL

learners’ oral proficiency, the increase in gain scores from pretest to posttest was

analyzed. Table 4.9 provides the descriptive statistics of One-way ANOVA for the

increase in gain scores, reporting the degree of the participants’ progress in oral

proficiency. After the 8-week voice-based ACMC, the average post-test scores is

15.31, which is higher than 9.41 in the voice-based SCMC and 0.54 in the control

group. The result of One-way ANOVA indicates that the increase of gain scores from

pretest to posttest among the three groups reaches the significant level, p= .000

(p< .05). Scheffe’s post hoc comparison , as can been seen in Table 4.10, further

suggests that Gong group make greater progress than Skype group as well as the

control group, reaching the significant level of .032 and .000 respectively (p<.05).

Different from the original hypothesis in the present study and Abram’s (2003) findings in the effect of text-based CMC, it was voice-based asynchronous group that outperformed voice-based synchronous group in terms of oral proficiency.

Table 4.9

Gain Scores: The Progress of the Three Groups after the 8-Week Treatment

Group Mean Std. Deviation N

Gong 15.31 9.50 32

Skype 9.41 10.71 34

Control .54 5.24 37

Source

Type III Sum of

Squares df Mean Square F Sig.

Corrected Model 3837.35 2 1918.68 25.33 .000

Intercept 7279.27 1 7279.27 96.11 .000

Group 3837.35 2 1918.68 25.33 .000**

Error 7574.30 100 75.74

Total 18100.00 103

Corrected Total 11411.65 102

a R²= .336 (Adjusted R²= .323)

* p< .05 ** p< .01

Table 4.10

Scheffe’s Post Hoc—Multiple Comparison

95% Confidence Interval

(I) Group

(J) Group

Mean Difference (I-J)

Std.

Error Sig.

Lower Bound

Upper Bound

Scheffe Gong Skype 5.90(*) 2.14 .026(*) .57 11.23

Control 14.77(*) 2.10 .000(**) 9.55 19.99

Skype Gong -5.90(*) 2.14 .026(*) -11.23 -.57

Control 8.87(*) 2.07 .000(**) 3.73 14.01

Based on observed means.

* p< .05 ** p< .01

Not only has the comparison of the overall progress in oral proficiency but also that of the specific progress in EFL learners’ target language pronunciation and fluency among the three groups deserved careful examination. As mentioned in section 4.2, both Gong and Skype have significantly positive effect on participants’

pronunciation and fluency. The result of one-way ANOVA on pronunciation and fluency (Table 4.11) shows that the average increase of gain scores in pronunciation is 12.50 in Gong group, which is higher than that in Skype group (5.29) reaching the significant level of .000 (p< .05).

Simply put, the answer to the second research question is negative, suggesting

that regarding the progress participants made in overall oral proficiency as well as in

the aspect of pronunciation, voice-based ACMC group significantly outscores

voice-based SCMC group, yielding to contrary results of the previous studies on

text-based CMC (Abrams, 2003).

Table 4.11

Result for One-Way ANOVA for the Pronunciation and Fluency Progress of

Group Mean Std. Deviation N

Gong 12.50 6.72 32

Skype 5.29 7.06 34

Source

Type III Sum of

Squares df Mean Square F Sig.

Corrected Model 855.97 1 855.97 17.98 .000

Intercept 5219.61 1 5219.61 109.63 .000

Group 855.97 1 855.97 17.98 .000**

Error 3047.06 64 47.61

Total 9000.00 66

Corrected Total 3903.03 65

* p< .05 ** p< .001

4.4 Learners’ Perception of Voice-based CMC

In an effort to understand EFL learners’ perceptions of voice-based CMC (the third research question), the post-study questionnaire was carefully analyzed. In this section, qualitative data from the post-study questionnaire completed by the two experimental groups indicates several interesting points regarding participants’

attitude toward voice-based CMC (Gong/Skype), their intention of using the program in the future, and their preference for the eight different topics assigned in the program. In general, the findings reflect learners’ positive perception of incorporating voice-based CMC into spoken language learning.

4.4.1 Learners’ Attitude toward Voice-based CMC

First of all, Table 4.12 presents the learners’ responses to Question 1, showing

their general perception of voice-based CMC. Overall, learners reported positive attitudes toward having topic discussion in the context of voice-based CMC to improve their oral proficiency in comparison with face-to-face class discussion. There are as much as 84.4% (Strongly Agree, 31.3% and Agree, 53.1%) of all the Gong participants in favor of the statement that if they like to improve oral proficiency through Gong activities; in the same fashion, more than two-thirds of Skype participants (Strongly Agree,11.8% and Agree, 55.9%) hold positive attitude toward voice-based SCMC activities.

Table 4.12

Responses to Question 1 of participants in Gong and Skype

SA A M D SD N % N % N % N % N %

ACMC (Gong) 10 31.3 17 53.1 4 12.5 1 3.1 0 -

SCMC (Skype) 4 11.8 19 55.9 7 20.6 2 5.9 1 2.9

Note. N = Numbers of participants.

SA = Strongly Agree, A = Agree, M = Moderate, D = Disagree, SD = Strongly Disagree Q1: I like to enhance my English oral proficiency through Gong/ Skype.

To explore participants’ attitude, learners were required to further explain their preferences for voice-based CMC as well as their difficulties with CMC programs.

Table 4.13 summarizes frequency of the reasons why participants in Gong preferred

voice-based ACMC rather than face-to-face oral discussion. For all the reasons listed

alternatives if necessary. The top four reasons why they enjoyed Gong activities include three factors related to learners themselves and one to the distinguishing feature of the software, Gong: (1) lower affective filter in the context of voice-based ACMC (F=27), (2) preparation of the discussion content in advance (F= 25), (3) freedom to decide when and where to do the audio-recordings (F=21), and (4) the convenient function of voice speed up/down in Gong (F=19). Aside from the reasons listed on the posttest questionnaire, 11 users chose ‘others’, pointing out their appreciation of the repeated recording function served in Gong, which provides them more opportunities to perfect the recordings by speaking out the target language again and again.

Similarly, frequency of the reasons why participants in Skype preferred voice-based SCMC to class discussion are presented in Table 4.14. The top four reasons reported by Skype users are: the freedom to decide when and where to have the discussion (F=25), the low-anxiety environment of learning spoken language (F=23), the handy use of the Internet for collecting topic-related information (F=19), and the benefits of adequate preparation for the discussion topics (F= 18).

Furthermore, two participants ticked the item of ‘others’ in the questionnaires strongly

claiming that Skype activities strengthen their confidence on their own speaking

ability.

Below are some selections from the questionnaire.

“It never occurs to me that I can communicate with people in English. I believe

and feel that my English speaking ability is now being improving little by little. The

online discussion makes me confident on my English.” (Student 1)

“Discussion in the context of Skype encourages me to utter the language and

also gave me the confidence on speaking English. Whenever I do the oral discussion

at home, my parents are always surprised at my performance.” (Student 2)

Table 4.13

Responses to Q2: Frequency of the Reasons Why Gong was Preferred as Reported by Users

Reasons: Gong users can Frequency(F)

1. feel less anxious when leaving the voiced message at home. 27 2. enjoy the freedom to decide the way of discussion. 9 3. have equal chances to join in the conversation. 5 4. prepare the content of voiced message before doing the recording. 25 5. have the opportunities to listen to as well as imitate others’ pronunciation. 17 6. decide when and where to leave the voiced message. 21 7. surf the Internet to collect the information related to the discussion topic. 10 8. adjust the voice speed to facilitate the understanding of messages left by

others. 19

9. Others 11

Table 4.14

Responses to Q2 – Frequency of the Reasons Why Skype was Preferred as Reported by Users

Reasons: Skype users can Frequency

1. feel less anxious and comfortable without the teacher’s domination 23 2. enjoy the freedom to decide the way of discussion. 14 3. have equal chances to join in the conversation. 4 4. prepare the content of discussions before doing the recording. 18

5. decide when and where to have the discussion. 25

6. surf the Internet to collect the information related to the discussion topic. 19

7. Others 2

Despite the fact that the majority hold positive attitude toward voice-based CMC, there were still one participant in Gong and three participants in Skype reporting that they preferred class discussion to that in voice-based CMC. Three out of these further pointed out that the conversation would be more interesting and richer if they could see the interlocutor’s facial expression and body language while one reported that it was the numerous computer problems he encountered that blunted his interest in voice-based CMC.

Regarding the difficulties students faced during the online topic discussion, Table

4.15 and 4.16 report learners’ opinions on voice-based ACMC and SCMC by

frequency. For all the problems they encountered, participants were once again

allowed to choose more than one of the alternatives. On one hand, as can be seen in

Table 4.17, 8 out of 32 participants in Gong claimed that they had no problems at all

when holding the oral discussion. For the remaining 24 participants, most of them

complained about the lack of instant response/interaction with the interlocutors (F=10), which highlights the major feature of voice-based ACMC, a significant delay of speech time (D, Crystal, 2001). In Table 4.18, on the other hand, there were 6 out of 34 participants in Skype group reporting that seldom did they experience difficulties when carrying out the programs. Yet, up to 20 participants mentioned how difficult for them to deal with time arrangement after school. Some students further explained that due to their tight schedule after school, it is rather hard to find the common time for the synchronous online discussion. Instead of the problems resulting from computer software and hardware, it is time arrangement that becomes Skype users’ main concern. Apart from the issue on time arrangement after school, the second problem reported by high frequency (8) is the lack of interaction between interlocutors such as facial expression and body language.

In summary, the results above-mentioned not only suggest participants’ overall

positive attitude toward voice-based CMC but also provide further understanding of

their preference for CMC to class discussion, accompanied by the problems they

encountered in the context of voice-based CMC.

Table 4.15

Responses to Q3—Frequency of Difficulties in Using Gong

Difficulties Frequency

1. The unfamiliarity with the platform of Gong. 2

2. The unfamiliarity with the platform of Moodle. 1

3. The unfamiliarity with the operation of computer. 0 4. The lack of instant response to the message left on the board. 8 5. The lack of interlocutor’s facial expressions and body language. 9 6. The lack of the immediate interaction with the interlocutor. 10 7. The strangeness of talking in face of a computer. 1

8. The access to the Internet is unavailable. 0

9. The microphone for the voiced recording is hard to get. 1

10. No problems at all 8

11. Others 2

Table 4.16

Responses to Q3—Frequency of Difficulty in Using Skype

Difficulties Frequency

1. The unfamiliarity with the platform of Skype. 0

2. The unfamiliarity with the operation of the recording software. 3 3. The unfamiliarity with the operation of computer. 0 4. The lack of interlocutor’s facial expressions and body language. 8 5. The strangeness of talking in face of a computer. 5 6. The lack of access to the Internet or enough bandwidth of the Internet 2 7. The microphone for the voiced recording is hard to get. 2 8. The difficulty in arranging the time for online discussion after class. 20

10. No problems at all 6

11. Others 0

4.4.2 Learners’ Intention to Have Voice-based CMC

Subsequent to the participants’ attitude toward voice-based CMC, the survey of

their potential intention to keep having oral discussion in the context of voice-based

CMC was included in the post-study questionnaire. Table 4.17 displays the percentage

and numbers of participants in Gong and Skype who have inclination to use voice-based CMC in the future. Up to 81.2% of participants in Gong answered positively when being asked if they are willing to use Gong in the future while 67.6%

of participants in Skype showed inclination to keep using Skype for language learning.

Learners in Gong have stronger intention to use it. Though the majority of participants have intention to use voice-based CMC in the future, the rest of students in Gong (18.8%) and Skype (32.4%) reported either negatively or neutrally on the intention to continue using the programs.

Some participants’ comments on the intention issue are shown as follows:

“I am willing to use Skype in the future. Through the discussion activity, I have

more chance to speak English, which I think it can positively improve my oral

proficiency.” (Student 1) [Positive]

“The activity is quite interesting and I can have further understanding of my

classmates, having closer relationship with them.” (Student 2) [Positive]

“The conversation in Skype is a real conversation. I enjoy speaking English in

the real living environment rather than in class.” (Student 3) [Positive]

“I think the program is good for my English oral ability; however, here is no

knowing that I will have time to continue the program every week. Therefore, I am not

sure if I will use Gong in the future.” (Student 4) [Neutral]

“I am such a busy student that I have no time to carry out extra activities after

school.” (Student 5) [Negative]

“The loading of schoolwork is too heavy for me to continue the program after

class.” (Student 6) [Negative]

In a word, most students have strong intention to keep using Gong/ Skype in the future because they perceived the convenience and the effect of having extra oral discussion in the context of voice-based CMC and also considered the activities interesting. For those who reported unfavorably to use Gong/Skype, on the other hand, that the activities might bring extra schoolwork loading and could deprive them of free time is their main concern.

Table 4.17

Reponses to Q4—Intention to use voice-based CMC in the future as Reported by

Positive Neutral Negative Total N % N % N % N %

Gong 26 81.2 3 9.4 3 9.4 32 100

Skype 23 67.6 5 14.8 6 17.6 34 100

Note. N = Numbers of participants.

Q4: I am willing to use Gong/Skype in the future.

4.4.3 Learners’ Preference for Discussion Topics

Last but not least, learners’ preference for the eight different discussion topics in the present study was explored in the post-study questionnaires to probe into EFL learners’ interests, and could further facilitate task design in the future studies. All the participants in Gong and Skype were asked to give rankings from 1 to 8 for the eight assigned topics based on the degree of their preference. 1 point stands for the most interesting topics whereas 8 points represent the most boring topic; that is, the less scores the topic gains, the more interesting the topic is to the participant.

As can be seen in Table 4.18, participants in Gong give the first rank to

‘YouTube,’ followed by ‘Culture & Chinese Festivals’, and ‘The Contest of Cheerleaders’; the top three in Skype are ‘YouTube’, ‘Net Buy’, and ‘Culture &

Chinese Festivals’, which is slightly different from the rank in Gong. With the analysis of the overall points that all the participants in voice-based CMC gave,

‘YouTube’ is obviously the most interesting and appealing topic for both groups, and

then ‘Culture & Chinese Festivals’ and ‘Net Buy’ are in the second and third place by

the participants’ preference. The result suggests that EFL adolescent learners tend to

show greater interests in Internet-related and culture-related issues because they are

much close to their daily life conversation.

Table 4.18

Responses to Q5— Preference for the Eight Discussion Topics as Reported by

Topics Gong (N=32) Skype (N=34) Total (N=66)

Point Rank Point Rank Point Rank

T1: Superstition 149 5 183 6 332 8

T2: Net Buy 134 4 114 1 248 3

T3: Jokes 149 5 126 3 275 4

T4: Culture & Chinese Festivals 122 2 120 2 242 2

T5: YouTube 120 1 114 1 234 1

T6: The Contest of Cheerleaders 125 3 187 7 312 6

T7: Idol Worship 157 7 169 5 326 7

T8: Blogs & Online Games 150 6 136 4 286 5

Note. 1= the most interesting topic; 8= the most boring topic

According to the post-study questionnaire responses, most participants in Gong as well as in Skype show positive attitude toward voice-based CMC and have strong intention to use the program in the future. That is, results of the present study focusing on voice-based CMC were in accordance with other studies pertaining to attitude towards CALL and text-based CMC (Almekhlafi, 2006; Klassen & Milton, 1999;

Noriko, 2002).