For the sake of achieving the objectives of the study the data were inserted into a specifically designed Excel workbook. The explanation of the data arrangements is discussed here because of the significance of the procedure of computerisation and software in the methodology.
Apart from the technical issues of arranging and programming the worksheets, the following features related to capturing the study method were found to be worth mentioning. These features could highlight the strength of the practicality of the methodology as well as showing how the results could be as error-free as possible, specifically when a researcher intends to apply the model to a larger body of data.
- The expandability: The data and data worksheets could be added and the results in the results worksheets will be changed.
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- Updatability: In any stage of the research, for any reason, whenever data were changed, the change automatically resulted in changing and updating all related results worksheets including the score, usage, and categorisation of them.
The expandability and updatability of the results will be helpful for the future addition and modification of the Excel workbook, and could be called a striking aspect of this methodology. It could be considered a significant factor of the methodology and contribution to future research.
Table 3-12: A screenshot from the analysable Excel workbook, showing the P1 worksheet with 17 translation samples and scoring strategies for one of the translational problems
The workbook built for data analysis contained n problem data sheets (which may be called P-sheets) and 4 results sheets. For the initial phase n=10, and for the extended analysis n=51. Table 3-12 shows analysable Excel workbook, which reflects the P1 worksheet with 17 translation samples. As can be seen, the name of the problem is mentioned on the top of the table, i.e.
marked collocation in the source text. The next Column shows the different translations done by the 17 students and the next column shows the strategies that are employed by them to solve the related problem which is here the problematic expression (applied imagination). On top of the same column, the expression is mentioned. Columns E and F show the strategy code and the name of the strategy which is used by each student. The last four columns reveal the scores given by the three raters to the strategies followed by their average scores.
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A minor addition can be seen in the Excel P-sheets in comparison to the problem-strategy tables in the pilot study (section 3.8) and in the data scoring sheets.1 In P-sheets, which are Excel worksheets, because of the necessity of codifying the strategies, column E is added. This is a strategy test column which initially shows whether the name of a strategy is within the considered list of strategies (subsequently be shown in Table 4-21) to avoid any ignoring or non-inclusion in further analysis, and secondly exchanges the strategies’ names with traceable codes which could be automatically compared and analysed in the other related worksheets. These codes are numbered from 1 to 23 and are in accordance with our selected 23 strategies in Table 4-21. As can be predicted from the names below the sheets in Table 3-12, the four initial worksheets, which are located before the P-sheets, are related to the automatically updated analytical result, which we simply called result worksheets. The results worksheets automatically show the primary analysis of the P-sheets such as scores, frequencies and the pattern of the problem-strategy sets.
The first result worksheets which is called global, relates to the main factors that could affect the P-sheets and the other three result worksheets. It contains an open-ended list of strategies used in the research with the codes given to them. These codes inter-related with the P-sheets and could ensure us of the unification of the naming which is important factor in data analyses. For example, strategy 1, which is the first strategy found in the corpus of this study is named as
‘Translation by marked collocation’, is given code 1, and the second one, which is named as
‘misinterpretation’ is given code 2, etc. When a strategy is identified by the researcher to be used for each problem in any of the worksheets, these numbers could be given to them (in column E as is shown in Table 3-12 above), while their name will be automatically be presented in the following cells in the right side of the given numbers in the P-sheets (Column F above). This codification and arrangements are linked to data analysis in the next three result worksheets.
1 There might be other columns and rows which were added in the actual P-sheets in the Excel file which are not of special importance. They are not mentioned here not just because they cannot be seen in the samples of the thesis to require clarifying. They were only created for ease of calculation and reference in the process of working with the data; therefore, they do not possess any significant value in our data analysis.
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3.11 Concluding Remarks
Following a conceptual discussion in the previous chapter on defining a strategy-based model for translation training, the need for exploring a quantitive methodology for finding the educationally significant strategies was discussed. This chapter started with critical scrutinizing of Baker-Davies’ problem-strategy model. The deficiencies found in their model directed us to define a new paradigm for a systematic study of students’ most problematic points and appropriate strategies for any language pair. Teaching strategies either to be recommended or practiced or to be avoided assumed to be the main imperative considerations for running a translation classroom as well as designing a translation-based course book. The important question of degree of educational significance found to be vital for the teaching program based on teaching strategies.
At the first practical step, the methodology introduced for studying the segments of the texts distributed to groups of students at translation courses. We discussed how the analytical review of the projects through the specifically designed P-S tables could lead us to reach a methodological framework for our educational goals. Locating the problems and strategies based on Baker-Davies’s tables and codifying the new problems and strategies seem to be the most delicate phases of the method.
It was discussed how the relation between frequency of the occurrence and the average scores given to the designated strategies are important considerations to find the areas of educational significance, e.g. when the low frequency will have confluence with the low score given by the raters. It was also revealed that such a paradigm have the capability of being generalised into any language pairs, though the pilot study was established in a Persian-to-English case. This methodology will be attested and put on show by its different aspects and details through the next Chapter.
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