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The categories and subcategories of node-switches and other types of errors were used in order to describe the errors made in the final texts and the objects of revision during and after the formulating process.

4.4.1 Error Analysis

For the statistical analysis, the plans and the essays of the participants were read through and after each error/mistake the ‘return’ key was pressed in order to create an ‘error-section’ document in which each error represents the border of an entity. This document was inserted into an Excel spreadsheet with drop-down menus in each line, from which one could choose the error category; this in turn activated the drop-down menus for the respective subcategories. For example, if an error is categorised as being a syntactic node-switch in column 3, the dropdown menu in column 4 offers article, preposition, tense, morphology, sentence construction, grammar and others. Since in some cases a ‘clean’

categorisation was not possible, two columns were added for alternative categorisations.

Babs wrote in her FLF for instance that researchers, pupils and teachers are concerned of the future. At first glance, this seems to be a syntactic node-switch of the subcategory preposition. However, it could also be that the preposition of was activated because the semantic network had initially activated afraid instead of concerned, and afraid takes the preposition of. Because of this, the error was evaluated as a syntactic and as a semantic node-switch. The total number of errors was raised by only one.

Table 4.1 gives an impression of how the Excel spreadsheet is structured. In the first line, the writer, Siebenmorgen, made a language-independent genre node-switch, since in the English as well as in the German community, starting a sentence with but is

considered unacademic. Other errors presented in the example are a syntactic node-switch of the subcategory preposition, a typing mistake, a semantic node switch and a grammatical error that was not L1-induced.

Line Text Error category Error subcategory

1 But of course, genre node-switch language-independent

2 the influence from language syntactic node-switch preposition 3 on thought also works the other way around, as

Dufrene typing mistake

4 states semantic node-switch network

5 as possible. Had Aristotle theory miscellaneous grammar

Table 4.1 Excerpt from Siebenmorgen’s FLN error analysis Excel spreadsheet

Each text by the participants was analysed in this way in the Excel document. The results were then implemented into an SPSS document which was needed for the statistical analysis.

Since the analysis of the influence of the L1 on FL writing is of greater significance in this paper, only a short overview of the types of errors that appeared in the L1 essays is given (Chapter 6.1). The main body of Chapter 6 contains a closer analysis of the relative proportions of the different errors that appeared in the FL texts. Chapter 6.2 presents the total numbers of errors in the different categories, in order to determine whether the influence of the L1 on FL writing is indeed worth a closer analysis – which, as expected, it is. Chapter 6.3 gives an overview of the errors made by each participant; it shows that the results differ markedly between the participants, but that there is a pattern across individuals. Finally, Chapter 6.4 contains an analysis of the errors in the subcategories in both the final essays (FLN and FLF) and in their respective plans (FLNpl and FLFpl). This close analysis is needed in order to see whether there are differences in the activated clusters in the different texts – a result which would indicate that the writing/planning methods activated the rules inside the linguistic structures differently.

In performing the error analysis, the findings of Chapter 5 are included in order to see whether there is a relationship between the degree of fluency and the errors that were committed and left uncorrected in the final texts. If such a relationship could be made out, it would shed light on the participants’ strategies of focussing their cognitive capacities differently in the more fluent text production situation compared to the slower and more controlled one; these insights could in turn be used to develop training methods for overcoming certain types of errors.

4.4.2 Categorization of revisions

After the analysis of the node-switches and other errors in the final texts, the keylogs of the participants were looked at with respect to the keyboard movements made and the corrections and revisions carried out during the writing process (Severinson Eklundh and Kollberg 1996: 168, Chapter 7). Here, no distinction was made between L1 and FL writing, since the analysis was intended to determine whether the participants concentrated on different aspects in the L1 and the FL when revising – as a result of a (potentially) different distribution of their cognitive capacities (Stevenson, Schoonen and de Glopper 2006: 223) and/or because of different writing methods in the L1 and the FL (Grabe 2001:

42, Hirose and Sasaki 1994: 204, Wolff 2000: 110) – or whether no distinct difference between the L1 and the FL could be made out. An attempt was made to discover whether the different activation of the language structures with the help of note-taking on the one hand, and with the help of freewriting on the other, made the writers act differently and concentrate on other aspects after the different planning conditions. This analysis had several different aspects.

Table 4.2 Example of revision analysis (Babs FLN)

As in the burst analysis, the keylogs were inserted into an Excel spreadsheet (Table 4.2).

The first column contains the elements of each burst in the writing process. The next column contains the key/movement with which the burst ended. Since it was necessary to determine whether each revision was made before or after a pause, this information was entered into columns 3 and 4. In column 5, the type of revision was labelled. Just as in the analysis in Chapter 6, it was possible to categorise or subcategorise a revision in two

different ways if it seemed it could have had either motivation. In the example below, the deletion of So and its substitution with Therefore could either have been motivated by the decision on another word for aesthetic reasons, or it could have been that Babs realised that starting a sentence with so would be unacademic. In cases like this, the revision is registered in two categories, but the total number of revisions rises only by one.

In Chapter 7.1, the statistical analyses of the numbers are presented, followed by the distributions of the different kinds of revisions in Chapter 7.2. The analysis of the revisions in the different categories is presented, and for the categories that were relevant to the outcomes, an analysis of the revisions in the subcategories is given as well.

Not every instance of revision resulted in the successful correction of errors on the first attempt. For example, in her FLF essay, Sarah wanted to write the word problem. She first produced the typing mistake por, which she ‘corrected’ to prolb. It was not until the third step that she was able to finish typing the word problem correctly. Since such corrections influence the writing process by reducing fluency and consuming cognitive capacities (Chapter 3.5), it can be presumed that the repeated correction of a single word had a negative influence on the production processes that followed, as well as on idea generation and on the writer's ability to keep the organisation of the structure and the overall goal of the essay in mind. A tally was therefore kept of how many steps the participants needed to correct an error (Chapter 7.3).

The revisions were analysed as a whole, as well as with respect to when they appeared. To do this, the text production process was divided into three parts: planning (Chapter 7.4), essay formulation (Chapter 7.5), and final revision (Chapter 7.6). In each of the parts, an analysis of the distribution of the revisions was made. Here it was possible to analyse in more detail how the participants distributed their cognitive capacities during the production processes and whether they used different strategies in the L1 and the FL writing processes, as well as during and after note-taking and freewriting.

Chapter 7.7 deals with whether the revisions occurred after pausing or whether pauses took place after the revisions. In academic writing, it was presumed that the higher demands on the cognitive capacities of the writers would result in a higher rate of pausing before content-related revisions than before revisions of typing mistakes, which are often noticed at the same moment they are made. On the basis of other studies (Krings 1992, 1994, Spelman Miller 2005: 310, 2006, see Chapter 3.5), it was also presumed that in FL writing, more pauses would occur before as well as after revisions with more superficial impacts on the texts (such as corrections to orthography) than would occur in L1 writing.

Again, the different activation of the language faculty by the two different planning methods might also have had an impact on these processes: it could be that the higher activation of the FL faculty induced by freewriting might have helped the writers in the formulation process by reducing the demand on cognitive capacities. Because of this, the distribution of pausing could have been closer to that seen in the L1 production process.

4.5 Summary

The analyses of fluency, of the errors in the final texts and of the categories of revisions and keyboard movements in the text production process give a distinct picture of the participants’ writing processes, the influence of the cognitive demands of FL writing on these processes, and the impact of the planning methods on the writing strategies. The kinds of linguistic errors that occur and the extent to which they are related to the L1 will also become clearer. If there are differences in the node-switch patterns, this will support Jackendoff’s (2002: 42 ff.) proposition that linguistic information is stored in form of rules, and will also shed light on how the rules are stored. For example, if certain kinds of node-switches occur more frequently in the freewriting condition, this might be an indication that they are stored in a mode that is not triggered by the active activation of the linguistic structures. Additionally, the analysis of the revisions will give an idea of the writers’

abilities to detect and to block L1 influences. It will also shed light on the focus of the writers’ cognitive capacities in the different writing phases in the L1 and the FL, which in turn, will provide a basis for developing instructional material and training in better and more effective writing.

5. Productivity and fluency

Productivity and fluency are important aspects in the analysis of writing processes because they shed light on the cognitive demands that writers face during the writing process, and on the way they deal with them (see Chapter 3.5). In the following, the different results in this area that emerged from the student essays are presented: the lengths of the essays in terms of number of words (5.1.1) and number of characters (5.1.2), and a short comparison of the individual results of the participants (5.1.3). Additionally, the production rate is examined – that is, the number of words and characters that the participants produced (and deleted) during the writing process (5.2). In Chapter 5.3, the amount of time the participants needed for each task is analysed (5.3.1), as well as how this time was distributed among the writing subprocesses (planning, formulation, final revision; 5.3.2) and how much time the participants spent on executing versus pausing (5.3.3). Chapter 5.4 presents the number of the bursts the participants executed during the writing process (5.4.1), the words per burst ratio (5.4.2) as well as the characters per burst ratio (5.4.3), and a short overview of the individual results with respect to characters per burst (5.4.4). These analyses are conducted for the whole writing process, as well as for the individual writing subprocesses (planning, formulation, final revision). Finally, the kinds of bursts the writers produced – i.e. p-bursts of r-burst – will be looked at (5.5.1), and the numbers of bursts that ended mid-word (5.5.2).