THE EFFECT OF COGNITIVE FUNCTION OF METAPHORS ON TEACHING ECONOMIC TERMS TO IRANIAN ECONOMIC MAJORS IN ESP COURSES
Publish place: Journal of Teaching Language Skills، Vol: 34، Issue: 3
Publish Year: 1394
نوع سند: مقاله ژورنالی
زبان: English
View: 200
This Paper With 21 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_JTLS-34-3_004
تاریخ نمایه سازی: 6 اردیبهشت 1400
Abstract:
The purpose of this study was to investigate the effect of two strategies of explicit teaching of economic terms on learners' vocabulary learning and retention. In the first explicit strategy, known as 'etymological elaboration', the focus was on presenting conceptual metaphors through 'identify-the-source' tasks, that is, providing the learners with the source domains underlying the metaphors, i.e., the literal meaning of the concepts. In the second explicit method, using 'identify-the-meaning' tasks, the metaphors were instructed by means of the context-based definitions. To be sure if there is any effect for the explicit teaching of metaphors or not, a third group was selected to function as the control group. In this group, the economic texts were taught in the traditional way, that is, by translating the texts into the learners' first language, i.e., Persian. The participants were three intact groups of university students majoring in Economics at Isfahan University, Isfahan, Iran. The results of the study demonstrated that the learners in Experimental Group ۱ outperformed those in Experimental Group ۲ and Control Group in vocabulary and retention tests. The study concluded that making students acquainted with the literal meaning of the conceptual metaphors, i.e., their underlying source domains will help them in learning and retention of technical economic terms.
Authors
Adeleh Heidari
University of Isfahan
Azizollah Dabaghi
University of Isfahan
Hossein Barati
University of Isfahan
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :