Language learning potential: Evidence suggesting the feedback

Language learning potential was investigated through the changes that students made based on the AWE feedback they received. To investigate whether AWE feedback leads to students’ noticing and focusing on the use of lexical bundles, students’ drafts before and after using the AWE tool, and their responses to the questionnaire were analyzed.

Before using the tool, only two lexical bundles were detected in two abstracts written by two students. After using the tool, 30 lexical bundles were detected in the final drafts of drafts of abstracts. On average, 2.3 lexical bundles per abstract were detected. Table 3.25 provides descriptive statistics for the number of lexical bundles used in students’ drafts before and after using the tool.

Table 3.25

Descriptive statistics of the number of detected lexical bundles in students’ first and final drafts (N = 13)

Total Mean Median Min Max SD

First Draft 2 0.2 0 0 2 0.4

Final Draft 30 2.3 2 0 5 1.8

Three questions from the six-point Likert-scale questionnaire asked students whether they noticed and focused on the feedback on the use of lexical bundles (0 as ‘strongly disagree’ and 5 as ‘strongly agree’). Table 3.26 provides descriptive statistics

Table 3.26

Descriptive statistics of the responses to the questionnaire regarding the feedback on lexical bundles (N=13)

Questions Mean Median Min Max SD

1 Clarity of the feedback on lexical bundles 3.8 4 2 5 0.8 2 Reconsideration of the sentences because of

the feedback on lexical bundles

4.1 4 3 5 0.8

3 Capability of sentence revision based on the feedback on lexical bundles

3.9 4 1 5 1.21

for the responses to these three answers. The first question asked students whether the feedback provided by the AWE tool related to the use of lexical bundles is clear to them. The results showed that students agreed the feedback they received from the AWE tool is clear to them (mean = 3.8). The second question asked whether they reconsidered what they wrote because of the feedback provided. The responses showed that students reconsidered their sentences once they received feedback from the AWE tool (mean = 4.1). The last question asked whether students were able to revise their sentences based on the provided feedback. The students agreed that they were able to revise their sentences based on the received feedback (mean = 3.9).

The results from the students’ drafts before and after using the AWE tool and the students’ responses to the questionnaire demonstrated that students noticed and focused on the feedback regarding lexical bundles from the AWE tool and made revisions to their abstracts. In their final drafts, it was found that 2.3 lexical bundles were used per abstract (compared to 0.2 in their first drafts). I also investigated Corpus-72 and found that 2.7 lexical bundles were used per abstract in that corpus of published professional writing. Although the number of lexical bundles that students had in their final drafts was a little lower than published abstracts, they are clearly comparable and are on the same order of

magnitude. This result shows that the feedback from the AWE tool raises students’ awareness of lexical bundles and prompts increased use of them.

3.6.2.2. Language learning potential: Evidence suggesting the feedback provided by the AWE tool leads to students’ noticing and focusing on the use of verb categories Students’ drafts before and after using the AWE tool, and their responses to the questionnaire were analyzed to examine whether AWE feedback leads to students’ noticing and focusing on the use of verb categories. It should be noted that the AWE tool only provided feedback to the verb categories not used, or were mostly used in certain moves. Based on the analysis in 3.5, Perfect aspect usually happened in the Introduction move and Modals occurred in the Discussion move; whereas progressive aspect and future tense were rarely used in Corpus-72.

Before using the tool, 12 main verbs were classified in terms of their grammatical categories by the AWE tool and feedback was provided. Eight instances (66.7%) of Tense-Aspect-Voice were used incorrectly, which means that the students either used future tense or the progressive aspect in their abstracts. After using the tool, fourteen verb categories were classified, and only four (28.6%) were used incorrectly. From Table 3.27, it can be seen that students had 100% correct usage of perfect aspect, and 63.6% correct usage of modals. They did not use future tense and progressive aspects anymore.

Additionally, by comparing their two drafts, it was found that students did one of three actions—retain, add, or delete the verb categories. As seen in Table 3.28, students retained two verb categories correctly, but two others incorrectly. They also added eight correctly although they added two incorrectly. More importantly, students deleted six uncommon verb categories from their previous drafts, but only deleted two common

categories. That is to say, although the total number of detected verb categories was not large, it can be seen that students attempted to add common verb categories and deleting uncommon usage.

Table 3.27

Correct and incorrect use of verb categories in students’ first and final drafts (N = 13)

First Draft Final Draft

Verb categories correct incorrect correct incorrect

Perfect aspect 4 0 3 0 Future tense 0 1 0 0 Progressive aspect 0 2 0 0 Modals 0 5 7 4 Total 4 8 10 4 Table 3.28

Correct and incorrect uses of verb categories in students’ final drafts (N = 13)

Retention Addition Deletion

Correct 2 8 6

Incorrect 2 2 2

Three questions from the six-point Likert-scale questionnaire asked students whether they noticed and focused on the use of verb categories (0 as ‘strongly disagree’ and 5 as ‘strongly agree’). Table 3.29 provides descriptive statistics for the responses to these three answers. The first question asked students whether the feedback provided by the AWE tool related to the use of verb categories is clear to them. The results showed that students agreed the feedback they received from the AWE tool is clear to them (mean = 3.9). The second question asked whether they reconsidered what they wrote because of the feedback provided. The responses showed that students reconsidered their sentences, once they received feedback from the AWE tool (mean = 4.0). The last

Table 3.29

Descriptive statistics for the responses to the questionnaire regarding the feedback on verb categories (N = 13)

Question Mean Median Min Max SD

1 Clarity of the feedback on verb categories 3.9 4 3 5 0.64 2 Reconsideration of the sentences because

of the feedback on verb categories

4.0 4 2 5 0.91

3 Capability of sentence revision based on the feedback on verb categories

3.7 4 1 5 1.11

provided. The students agreed that they were able to revise their sentences regarding verb categories based on the received feedback (mean = 3.7).

Results from the students’ drafts before and after using the AWE tool and their responses to the questionnaire showed that students became aware of the use of grammatical categories in each move because of the AWE tool feedback. They agreed that they reconsidered their sentences following receipt of the AWE feedback. They also deleted some incorrect usage and retained/added some correct usage of the verb

categories. Although students’ usage of verb categories in each move in abstracts was not 100% correct, the results here demonstrated the potential of the feedback from the AWE tool improving students’ uses of verb categories.

3.6.2.3. Learner fit: Evidence suggesting the AWE tool for assisting abstract writing is