Collocation and Translational Accuracy of IranianStudents through Data-driven Learning

Collocation refers to a natural combination of words; it is the way words are closely associated with eachother. Collocations describe word combinations, but joining words are not acceptable combinations. Thepresent study was designed as a collocation-based research. It was an endeavor to analyze the influence ofdata-driven learning (DDL) as a pedagogical instruction in its own right on the translational accuracy ofIranian students. The participants, undergraduate learners of English at the University of Semnan and theIslamic Azad University of it, were divided into three groups: one employing collocation lines, one obtainingdata by means of dictionaries of collocation, and one gathering data offered and suggested by the instructor onthe board. The hypothesis offered was that there was no meaningful difference between the various teachingmethods. The findings revealed that there is a widely and meaningful correlation between the student’svocabulary knowledge and collocational knowledge, and there is a strong and significant relationship betweenthe students’ general collocational knowledge and their translational accuracy. The outcomes also revealed thatdata-driven learning (DDL) is more productive compared to traditional chalk-and-board and dictionaryconsultation methods.

Keywords:

Collocation , Data-driven learning , Translational accuracy , Vocabulary