Márta Lesznyák: A longitudinal investigation of translation trainees’ translation and post-editing competence development I
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3 Results and Discussion
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3.3 Advanced students (2nd year students at the end of their studies)
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3.3.5 Translation/post-editing performance

3.3.5 Translation/post-editing performance

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Table 20 presents the summary statistics for error types by work mode (HT or PE) in the second data collection wave, and it also compares the two groups with the help of independent samples t-tests. Closer inspection of the table shows that, in addition to the total number of errors, accuracy and fluency error numbers differ significantly in the two groups (p < .05), and it is always post-editors who commit fewer errors.
 

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Table 20 Differences Between Human Translator and Post-Editor Performance at the End of the Second Year. Results of the Independent Samples T-Test
 
Human translators (n = 11)
Post-editors (n = 16)
 
 
 
M
SD
M
SD
t-test
p
accuracy errors*
8.32
3.08
6.44
1.72
2.03
.053
fluency errors*
4.91
3.19
2.05
1.45
2.34
.036
style errors
5.77
1.78
5.53
1.70
0.35
.728
terminology errors
3.77
1.19
4.28
0.80
–1.33
.194
total number of errors*
22.77
4.03
18.75
3.36
2.82
.009
Note. M = mean, SD = standard deviation, * factors with significant differences
 

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It is worth noting that terminology error means show a different tendency than all other error types: the mean value is somewhat higher for the post-editor group than for human translators, although the difference is not significant. Implications of this finding will be discussed below (3.4.2.2 The quality of the target texts (error numbers) in the second data collection wave).

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To find out whether differences between error numbers within a subgroup were significant, repeated measures one-way ANOVAs were carried out.

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In the human translator group, the Mauchly’s test indicated that the assumption of sphericity had been met (χ2(5) = 6.893, p = .231). The repeated measures one-way ANOVA determined that some mean error numbers differed statistically significantly (F(3, 30) = 6.092, p < .002). Post hoc analysis with a Bonferroni adjustment revealed that accuracy errors (M = 8.32) were statistically significantly higher in number than terminology errors (M = 3.77). In addition, there was a marginally significant difference (p = .059) between the number of stylistic errors (M = 5.77) and terminology errors (M = 3.77). For the sake of readability, the results of the pairwise comparisons are reported in detail in Appendix 9. Second data collection wave (second-year students).

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It should be noted again that the low number of terminology errors may be due to error correction decisions.

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In the post-editor group, the assumption of sphericity was met, too (Mauchly’s test: χ2(5) = 2.944, p = .709); as a result, no correction for the degrees of freedom was necessary. Repeated measures one-way ANOVA indicated that there was a significant difference between error numbers (F(3, 45) = 24.233, p < .001). Pairwise comparisons with Bonferroni adjustment showed that there were significantly more accuracy errors (M = 6.44) than terminology errors (M = 4.28) and fluency errors (M = 2.50). Fluency errors were also significantly lower in number than stylistic errors (M = 5.53) and terminology errors (M = 4.28). Results of the pairwise comparisons are reported in detail in Appendix 9. Second data collection wave (second-year students)
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