En muros con aberturas, para valuar la fuerza cortante que toma el concreto en los segmentos verticales entre aberturas o entre una abertura y un borde, se tomará

Table 5.9 gives an overview of the words-per-burst rate in the different tasks and in the different writing processes. The analysis shows that the total words-per-burst rate was highest in the simplest task (SE): 2.89 words per burst. In the L1F and the FLF, the rate was quite close to that of the SE, with 2.73 words per burst in the L1F writing process and a slightly higher rate of 2.77 in the FLF writing process. The difference between the L1 and the FL is insignificant, however. In the L1N and FLN conditions, there was no difference at all: both conditions resulted in 1.98 words per burst.³

SE L1N FLN L1F FLF Total words/burst 2.89 1.98 1.98 2.73 2.77 Words/burst (planning) 0 1.92 1.64 6.50 8.88 Words/burst (formulating) 2.91 2.10 2.11 2.45 2.43 Words/burst (revising) 1.24 0.66 1.04 0.80 1.24 Table 5.9 Number of words per burst

The average number of words per burst in the different writing conditions varied distinctly.

This indicates that the planning type had an effect in the L1 similar to that in the FL. As expected, the rates of words per burst differed most clearly in the planning processes.

Since none of the participants spent any time on planning the SE, there is no result for this aspect in this condition. Comparing the different tasks, the highest words-per-burst rate (FLFpl) is 81.5% higher than the lowest words-per-burst rate (FLNpl). The fact that the lowest and the highest rates occur in the same language indicates that the participants had different (subconscious) strategies for executing note-taking and freewriting in the L1 and in the FL. In the L1 notes, it was easier for the participants to formulate the mentally

3 The numbers of words per burst are lower than the results in most other studies (e.g. Chenoweth and Hayes 2001, Galbraith 2009) because the pauses that end revisions in those tests are longer

generated ideas and the articulatory buffer was larger. The generation of ideas itself also worked more fluently in the L1Npl than in the FLNpl, since in the former, the participants were able to produce longer bursts and higher numbers of bursts per minute than in the latter. Some of the participants did not feel the need to write down a significant amount of information in the L1 tasks, whereas in the FL tasks they used their notes more extensively in order to relieve the working memory. In the FL this process was more laborious, again indicating that the participants made more use of the L1 here to generate ideas, which made formulation more difficult (Poulisse and Bongaert 1994: 53).

The fact that more words per burst were produced in the FLFpl than in the L1Fpl could be explained in different ways. For one, it could be that the writers’ internal monitors were generally more apt to notice errors in the L1 than in the FL, and it was more difficult to switch the monitors off in the L1 condition. The participants could not resist making automatic corrections in their L1, which some of them noted explicitly in the questionnaires. Gio, for example, wrote that she would not use freewriting as a planning method again, because it influenced her use of language in a negative way. Additionally, as noted above, German and English morphology differ, and because of this, the lower number of words per burst does not necessarily reflect a lower rate of idea generation activity.

The individual results of words per burst in planning (Fig. 5.7) reveal that the distinct differences in the words-per-burst rate between freewriting and note-taking arise in large part from the results of Artilleryman and Siebenmorgen, who produced an average number of words per burst of 13.73 (Siebenmorgen) and 18.73 (Artilleryman) in L1 freewriting and an average words-per-burst rate of 22.83 (Siebenmorgen) and 31.78 (Artilleryman) in FL freewriting. With all the other participants, one can also see that the words-per-burst rate in the freewriting planning process was distinctly higher than in note-taking in both languages, but now there is no overall tendency toward a higher number of words per burst in the L1 or the FL: four

Fig. 5.7 Words per burst per participant in planning

SE L1N FLN L1F FLF

of the eight participants (excluding Siebenmorgen and Artilleryman) produced a higher rate in their L1 and the other four produced a higher rate in their FL. That is, the reasons for the higher productivity in the FL compared to the L1 in the freewriting condition apply to 60% of the participants (including Siebenmorgen and Artilleryman), indicating again that the performance of the writing processes – and that of the planning processes to an even larger extent – depends on the individual writer (Bräuer 2009: 56, Torrance, Thomas, and Robinson 1999: 190, van Waes 1992: 185) as well as on language proficiency (Francis 2012: 112).

In the formulating process of the proper essays, the differences in the results regarding words per burst across the different task conditions converge. Overall, the highest rate is found in the SE, which yielded 2.91 words per burst. Among the academic essays, the lowest words-per-burst rate occurred in the L1N (2.10), and the highest was found in the L1F (2.45). The differences between the languages within the different planning conditions were only marginal. That is, the production rate in the formulating process after note-taking rose significantly from the planning to the formulating process (L1N: 9.37%; FLN: 22.3%) and fell even more significantly from planning to formulating after freewriting (L1F: 62.3%; FLF: 72.3%). The rise in the former instance is the result of a relocation of the cognitive capacities from note-taking to the elaborate formulation of the ideas. The fall in the latter – i.e. the reduction of the words-per-burst rate in the freewriting condition – was also predictable, since in formulating academic essays, monitoring is activated in an intensive way, since it is necessary for the writer to develop a structured and well-formulated way of conveying their intentions to the reader. Still, the words-per-burst rate is higher in the essay written after freewriting than in the one written after note-taking, which proves that the activation of the linguistic interfaces keeps on working after the actual

production rates (Table 5.10). James and Artilleryman were very productive in all task conditions, having results of more than three words per burst in nearly all conditions – a result which, according to Galbraith (2009: 17), could be an indicator of a higher rate of idea generation in the writing process, especially if one considers that the bursts in the analysis are ended by pauses no shorter than one second, which is, as suggested above, rather strict.

All of the participants with the exception of James, iPhone and Babs achieved the highest words-per-burst rate in the SE. iPhone and Babs were more productive in the L1F, while James was the only participant more fluent in all tasks other than the FLN academic papers. The words-per-burst rates differed between the tasks for every writer. Only in Sarah’s case were the results nearly static: 1.67 words per burst in the SE and 1.65 in the L1N, L1F and FLF; the exception was the FLN, with 1.35 words per burst. Since Sarah was the candidate who was not able to produce a freewriting text according to Elbow’s (1973: 3) rules (writing a linear text without paragraphing), but instead wrote the freewriting text in list form, the consistent words per-burst-rate demonstrated by her indicates that the new planning condition did not help to improve her fluency, but did facilitate a faster production process, which in turn gave her more time for revision.

With all of the other writers, fluency improved under the freewriting condition.

Only Babs was least fluent in the FLF condition, but her words-per-burst results in the L1F were significantly higher than in either of the note-taking conditions and in the SE. Since her results in the FLN condition were higher than in the L1N and the FLF, the language factor is not the obvious explanation for her less fluent performance in the formulation of FLF. In the questionnaire, she noted that during the FLF formulating stage, more typing mistakes occurred, perhaps hinting at the problem of coordinating the faster internal formulation processes with motoric movements, which are generally better trained in L1 orthography than in FL orthography. This again points to the importance of doing more research in the area of executing processes and their influence on text production (see Chapter 3.1.4).

As in planning, there is no obvious overall interrelationship between the words-per-burst rates in the two languages. In the note-taking condition, six of the ten participants were more productive in the FL, while in the freewriting condition, five of the ten participants were more productive in the L1, four were more productive in the FL, and one obtained the same result in both conditions.

When it comes to the revisions, on the other hand, it is noteworthy that language

does seem to have an effect on the words-per-burst rate. The lowest rates were found in the L1, whereas in all of the FL texts (including the SE), the rates were higher. This indicates that here – at least to a certain degree – the participants concentrated on different aspects in the revisions. They reformulated more passages or added more content in the FL, which again shows that they were more critical or less content with their FL texts than with their L1 texts. The remarkably high number of words per burst in the FLN revisions was not expected, since here the bursts-per-minute rate was the highest rate, and it was assumed that only marginal revisions were carried out, such as corrections of typing mistakes (Chapter 5.4.2). Chapter 7.6 will show that although the number of corrections of typing mistakes and punctuation errors in the revisions of the FLN were high, other elements can be evaluated as being equally important.