Contributions of the Keyword Method, Thematic Clustering and Developing Morphological Awareness to the Iranian EFL learners’ Mastery of Low Frequency English Words
Publish Year: 1403
نوع سند: مقاله ژورنالی
زبان: English
View: 75
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_ELT-16-33_008
تاریخ نمایه سازی: 5 تیر 1403
Abstract:
This study investigated the effects of three vocabulary development strategies of keyword method, thematic clustering and developing morphological awareness on the Iranian EFL learners’ vocabulary repertoire. Adopting a quasi-experimental design, sixty high-intermediate to advanced Iranian EFL learners were randomly assigned to three experimental groups and partook six online sessions of vocabulary instruction during a week. Using a pre-test and three post-tests, the vocabulary repertoire of the subjects was measured. The pre-test was administered a week before the commencement of the treatment sessions; the first post-test was administered immediately after each treatment; the second post-test was held ۲۴ hours after each treatment and the third post-test was held one week after the end of the treatment sessions. Paribakht and Wesche (۱۹۹۳) model of measuring vocabulary enhancement was used to quantify the vocabulary repertoire of the subjects. Split-plot ANOVA test revealed that the subjects in the keyword group outperformed the subjects in the other two groups in all the three post-tests. Moreover, it was revealed that the thematic clustering group outperformed the developing morphological awareness group. The findings of this research may have pedagogical implications for English teachers, learners and material developers.
Keywords:
Authors
Farahman Farrokhi
Department of English Language & Literature, University of Tabriz, Iran
Fatemeh Gholami
Department of English Language & Literature, University of Tabriz, Iran
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 :