AI Summary & Key Takeaways
AI InsightSurvey results indicated that the majority of the students found the corpus application in the translation course beneficial as a pedagogical resource with the exception of a few students, who stated that they experienced difficulties due to unfamiliar vocabulary and limited number of examples in the collocate output.
📌 3 Key Takeaways
Abstract
Translation courses are a vital part of undergraduate English Language Teaching (ELT) programs and the importance of finding new ways to enhance student learning in this context cannot be stressed enough. It is reported that second language (L2) learners of English tend to produce incorrect or deviant collocations in their L2 written outputs, be it their academic or casual writing or translation products due to failure to recognize them as expressions to be learnt. In this regard, this study sought to implement the Data-driven Learning (DDL) approach in the ELT translation course to raise L2 learners' consciousness of verb-noun collocations and assess the effectiveness of the approach using a pre-experimental pretest/post-test design and a survey to evaluate the effectiveness of the instruction. In the study, 16 participants (13 females and 3 males) completed a six-week program. The results obtained from the Wilcoxon signed-rank test applied to compare the mean ranks of the learners' pretest and post-test scores indicated a significant improvement in the collocational knowledge of the targeted expressions from Pre-test to Post-test 1 (Z = -3.519, p = .005). Survey results indicated that the majority of the students found the corpus application in the translation course beneficial as a pedagogical resource with the exception of a few students, who stated that they experienced difficulties due to unfamiliar vocabulary and limited number of examples in the collocate output.