Learners’ Attitudes toward Netspeak and Linggle

To investigate learners’ attitudes toward the two corpus tools in different aspects, the post-questionnaires include eight five-point Likert scale questions on the first page and open-ended questions on the second page. Moreover, the transcripts of the

interview were also analyzed to further examine learners’ attitudes.

The results of learner’ attitudes toward Netspeak and Linggle were examined based on the mean score of each item. The results were organized as in Table 4.14.

To further understand if learners held more positive attitude toward either Netspeak or Linggle, the total mean scores of the two corpus tools were compared. It is observed that learners’ agreed that Linggle was useful in general (M=3.60, SD=.21).

Furthermore, learners believed Netspeak were somewhat useful in general (M=3.34, SD=.84). After comparing the total mean scores of the two corpus tools, it is found that learners’ attitudes toward Linggle were slightly more positive than Netspeak, suggesting that learners were slightly more satisfied with Linggle than Netspeak in general.

As for future willingness of using Netspeak and Linggle, learners were willing to use Linggle (M=3.75, SD=.50) and learners were somewhat agree that they will use Netspeak in the future (M=3.25, SD=.96). In comparison, the mean scores suggest that learners seem to be slightly more willing to use Linggle than to use Netspeak in the future.

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Table 4.14 Results of the post-questionnaires

Netspeak Linggle

After learners’ overall attitudes toward the two corpus tools were analyzed, learners’ attitudes for each item on the post-questionnaires are discussed. The results are shown in Table 4.14. In general, the mean scores of half of the items of both

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corpus tools are 3.50 or higher, indicating that learners held positive attitudes for different aspects of the two corpus tools. The first aspect focuses on learners’ attitudes toward the designs of Netspeak and Linggle, which include target users, interfaces, and operators. The second aspect aims at learners’ perceptions toward using the two corpus tools for English learning. Finally, learners were found to change their

attitudes after using the two corpus tools. Thus, the results would be further discussed.

To begin with, learners’ attitudes toward the designs of the corpus tools are discussed. Item one is designed to understand learners’ attitudes toward the target learners of both corpus tools. The result shows that learners believed Netspeak was more suitable for their proficiency level (M=3.50, SD=.58) than Linggle was (M=3.25, .50). The results of the second item indicates that learners believed that Netspeak had easier interface (M=3.50, SD=.58) than Linggle did (M=3.00., SD=0).

The results of the third item reveals the operators of Netspeak was considered more useful (M=3.75, SD=1.50) compared with Linggle’s operators (M=3.25, SD=.50).

Learners strongly agreed that the five operators provided by Netspeak were extremely useful for them while learners somewhat agreed that Linggle’s operators were useful.

Learners further reported the most and the least useful operators provide by Netspeak and Linggle in the interview. Netspeak’s results were organized as in Table 4.15 and Linggle’s results were shown as in Table 4.16. The results of the most and least useful operators of Netspeak were first addressed. Among the five operators provides by Netspeak, the [ ]-operator were considered as the most useful operator by half of the learners as shown in Table 4.15 (N=50%). The ?-operator and the

#-operator were reported to be the most useful operator for other two learners (N=25%). On the other hand, half of the learners thought the ...-operator were the least useful (N=50%). The ?-operator and the{ }-operator were also chosen as the

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least useful operator by two other learners (N=25%).

Table 4.15 Learners preferences of Netspeak's operators

? # [ ] { } ...

Learners also reported the most and the least useful operators of Linggle. The results were categorized as in Table 4.16. It shows that two learners believed that

“POS” operators were the most useful operators (N=50%). The operator “_” and the operator “/” were also chosen as the most useful operators by the other two learners (N=25%). As for the least useful operator, half of the learners chose the operator “~”

(N=50%). Two other learners chose the operator “?” and “*” to be the least useful operators (N=25%).

Table 4.16 Learners preferences of Linggle's operators

POS _ ~ / ? * note. POS, search for words with specific parts of speech; _, search for any words, ~, search for similar words; /, comapre options; ?, search for words optionally,

* search for zero or more words.

After the analysis of learners’ attitudes toward the designs of the two corpus tools, the mean scores of item four showed that learners were somewhat agree that

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Netspeak was useful for them in general (M=3.25, SD=.96) according to Table 4.14.

Learners agreed that Linggle (M=4, SD=.82) was generally useful for them. Learners appear to feel slightly more positive toward Linggle than Netspeak, which echo with the total mean scores, which were discussed in the previous sections.

Learners revealed their attitudes toward using the two corpus tools for English learning. It is shown from item five to six on the post-questionnaires (see Table 4.14).

The mean scores of item five showed that learners somewhat believe that Nestpeak could help them improve English abilities (M=3.25, SD=.96) while learners agreed that Linggle could help them improve English abilities (M=4, SD=0). The results of item six showed that learners agreed that Netspeak (M=3.50, SD=1.29) and Linggle (M=4, SD=0) were both useful for assisting them to correct error. However, Learners felt than Linggle could be slightly more useful to help them correct errors.

Finally, learners were further asked to show their attitudes toward Linggle’s examples based on Likert Scale during the interview. The results indicated that learners agreed that Linggle provided many examples (M=4, SD=1.41). Moreover, they somewhat agreed that Linggle provided examples from rich contexts (M=2.75, SD= .96).