Development of rapidity in text production

Fluency as a complex system involves not only automaticity. Automaticity is a trigger, an enabling condition that leads to increased speed in producing utterances. Such rapidity can manifest itself in the time spent delivering a text. The more words a speaker can produce in a given time unit the high-er his or hhigh-er fluency is phigh-erceived to be. In our study the numbhigh-er of words written in one minute may serve as a relevant measure for this feature of fluency, a fact which corresponds with previous studies described above.

The overall writing speed generally increased during the three-year-pe-riod. This was a tendency that was observed at both the average and the individual levels, see Figures 7.3a and 7.3b. However, although the general trend was upward, looking solely at the mean developmental path would lead us to the misleading conclusion that fluency developed almost linear-ly (with growth rates not exceeding 20% in six-month intervals) and stabi-lized after two years of learning. A comparison of the average results with those noted for individuals leads us to reject this simplistic statement. In no student was such straightforward progress observed. Individual devel-opmental trajectories in all study participants visibly diverge from the av-erage line presented in Figure 7.3a. No one student becomes more fluent in a linear-like way. Their writing speed in most cases developed very dy-namically, with growth rates between experimental sessions higher than 20%. What should be stressed here is that fluency did not decrease in any writer. Even those students who were already very fluent composing texts from the very beginning remained at least at the same level or even im-proved slightly. This leads us to the preliminary conclusion that the pro-gression of complexity and accuracy does not automatically result in a less fluent performance. The interplay of all three dimensions will be discussed in the next chapter so no deeper analysis will be made at this point.

As in the case of automaticity, inter-subject variation decreases, with a  growth rate of R = −25% between the first and the last experiment.

However, both results show that fluency, compared with complexity and accuracy, is the only dimension of proficiency where differences between learners smoothed out. However, it is not only between-student

varia-tion that indicates how automaticity and speed in writing are two inher-ent features of the same dimension. We can even see this interconnection between the two in a correlation that was very strong in almost all the students (Table 7.1). In only three learners (S10, S12, S14) did the devel-opment of automaticity and speed not proceed hand in hand.

This should not come as a surprise. Even if the general tendency in the majority of second language learners is for automaticity to develop in parallel with rapidity in text production for some students these two aspects of fluency do not depend on each other in the same way as it does in the case in their fellow students. A likely scenario is that revisions and pauses may affect general fluency in these learners.

As has already been mentioned, the mean development does not corre-spond with the individual trajectories. The dynamics of fluency develop-ment are not only recognizable in the nonlinearity visible in the diagram.

The individual growth rates provide a picture of the actual developmental path. It turns out that in the majority of learners fluency increased sig-nificantly during the first three semesters of learning Swedish (see Fig-ures 7.4a and 7.4b) when the individual growth rates at six-month in-tervals were 32% ≤ R ≤ 111%. As in the case of accuracy, fluency appears to be a property in second language that is often a kind of cornerstone for other language skills, such as, e.g., complexity. Due to the variation between students even this statement cannot be accepted without reser-vation. The majority does not mean all students and the remaining one third of the participants began to write much more fluently at the end of their second or not until their third year of learning Swedish.

Figure 7.3a. Average development of writing speed

Figure 7.3b. Development of writing speed in individuals

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Table 7.1. Correlation between automaticity⁹ and speed

Subject R

S1 .84

S2 .70

S3 .85

S4 .77

S5 .69

S6 .51

S7 .92

S8 .72

S9 .98

S10 .15

S11 .97

S12 .04

S13 .77

S14 .10

S15 .82

9 For a better visualization and in order to not confuse the reader by constantly reminding them that an increase in automaticity in this study means a decrease in transition time the value (TT) has been recalculated to 1// TT so that we get an in-versely proportional result, which allows us to interpret an increasing value as increas-ing automaticity.

Figure 7.4a. Learners with highest growth rates for writing speed during second semester

This divergence between learners once more illustrates another fea-ture of dynamic systems, namely their chaotic and unpredictable charac-ter. The tempo of development is one of the most unpredictable variables in this area. When a learner differs quite significantly from their fellow students in the beginning phases of learning a new language, in other words, when the parameter of fluency has been set very high, further de-velopment can proceed unpredictably, such that a bifurcation may occur.

This phenomenon has also been observed in the case of writing speed.

The writing speed of the three learners with the highest level of fluency in the first experiment, exceeding the group average by at least 20%, had assumed two different development paths after three years: one of the students made further improvement, while two remained at the same level. From the perspective of the time of onset for the language, fluency in these writers obviously increased, as it did in other learners. However, in the case of such quick-starters unpredictability is much more likely than in other students. Their fluency had already approached an attractor state in the first months of learning the new language – even the student whose fluency increased had the lowest growth rate in the entire group, which shows us that stability, or less variability does not mean equilibri-um when open and complex systems are in action.

Looking at the development of fluency from the other side, i.e. from the point of view of those students who were slowest in text produc-tion in the first experiment it turns out that these learners had made the greatest progress in fluency by the end the three-year study period.

Figure 7.4b. Learners with highest growth rates for writing speedduring third semester

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Spearman’s rho for the interplay of general growth and fluency levels af-ter the first semesaf-ter was ρ = −.75 (p=0.01), which clearly shows that the lower the fluency level at the beginning, i.e. the later fluency develops, the more long-term progress can be observed. And these two develop-mental patterns – quick starters who achieve fluency early on and then approach an attractor state, and slower learners, whose development is more dynamic in the long-term perspective – together build a picture of decreasing individual differences in fluency.