1. Evaluation of Electronic Translation Tools Through Quality Parameters Vlasta Kučiš University of Maribor, Department of Translation Studies Sanja Seljan, Ksenija Klasnić University of Zagreb *Department of Information Sciences **Department of Sociology

2. Overview Theoretical part EU & multilingualism Education for translators EMT (European Master’s in Translation) Empirical part Research (goal, sample, tools) Evaluation Results Conclusion

3. How to make Multilingual Communication & Translationin the 21.st century… ???

4. Translation and the EU • EU - communication in 23 official languages  Increased translation demands • Multilingualism policy unique in the world  all languages = equal status • DGT  the biggest translation service  8.000 pages per day / 6.000 translators • Changes in translation profession development of language technologies • Education for translators - EMT

5. DGT brings the EU closer to the citizens

6. Multilingualism is about building bridges, between people and across policies. • Efficient and pragmatic internal language regimes Dimensions: Access to institutions, rights and obligations Interaction between citizens

7. Official EU languages 1958-200824.Croatian  2012 ???

8. Evolution of the translation servicein the European Commission

9. European Master’s EMT • High-quality training for professional translators experts in multilingual communication • Enhance the status of translation as a profession  criteria of excellence • Competences: language, intercultural, thematic, technological, organisational

10. II RESEARCH • Sample N=51 student all 4 years (convenient sample) • Department of Translation Studies, University of Maribor • 2 EU-texts of similar length • text 1 =159 words / group A; • text 2 = 140 words / group B • German - Slovene • 45 minutes • Evaluation - by professional bilingual translator (German + Slovene as mother tongues)

11. Tools Group A • traditional • electronic dictionary Ger-Slo(Debenjak) • online dict. Duden www.duden.de • search engines (Google + Yahoo ) Group B • Slov. Evrokorpus www.evrokorpus.gov.si • Slov. Evroterm www.evroterm.gov.si • Terminology base integrated into SDL Trados

12. Mistake categories: • Lexical mistakes • Spelling & punctuation mistakes • Syntactic & stylistic mistakes

13. Results • Total number of mistakes and paired samples statistics p<0.001 – average number of all mistakes has statistically significantly decreased

14. Lexical mistakes Statistically significant difference al level p<.001, df=50

15. Spelling & punctuation mistakes • no. of spelling mistakes: A) 243 B) 131 • coefficient of variability – bigger in B) -> need for adequate education for use of translation tools Statistically significant difference al level p<.001, df=50

16. Syntactic & stilistic mistakes • no. of spelling mistakes: A) 236 B) 138 • coefficient of variability – bigger in B) -> need for adequate education for use of translation tools t=4.43 Use of translation tools has at statistically significant level decreased number of syntactic and stylistic mistakes with p<.001, df=50

17. Improvements in %

18. CONCLUSION • Introduction of CAT tools significantly influence the quality • coefficient of variability – bigger in B) -> need for adequate education for use of translation tools • T-tests – statistically significant difference at all levels with p<0.001 • Acceptance of hypothesis: • Online translation tools contribute to the quality and consistency of technical translations at all 3 levels • facing new challenges in education, business, cooperation