A SWOT Analysis of Instagram English Teaching Pages
سال انتشار: 1400
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 175
فایل این مقاله در 20 صفحه با فرمت PDF قابل دریافت می باشد
- صدور گواهی نمایه سازی
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_EFL-6-3_002
تاریخ نمایه سازی: 5 دی 1400
چکیده مقاله:
In recent years social networking sites have affected almost all aspects of our lives. The Instagram social network has become popular among people, and there are lots of pages on this social media, which are explicitly presenting English materials to their followers. This non-experimental descriptive study aimed to determine the strength, weaknesses, opportunities, and threats of English teaching pages on Instagram. Twelve English teaching pages were observed due to their high number of followers to discover the strengths, weaknesses, opportunities, and threats. To provide more fruitful points for the SWOT analysis, ten active Instagram users were interviewed. They were asked to fill out a SWOT analysis written interview about Instagram English teaching pages. The interpretative approach and frequency and percentage were used to analyze the data, owing to the nature of the gathered data in this research. Employing the results of this study, admins of English teaching pages can take a forward step to make their pages more beneficial and more effective in the process of English teaching. The findings can also help those scholars or teachers who want to use Instagram to present their services. Being aware of the effectiveness of English teaching pages helps language learners be more cautious about selecting them as a source of learning English.
کلیدواژه ها:
نویسندگان
فرزانه رضایی
Ph.D. Student in TEFL, English Department, Islamic Azad University, Isfahan (Khorasgan) Branch, Isfahan, Iran
عزیزه چالاک
Associate Professor of TEFL, English Department, Islamic Azad University, Isfahan (Khorasgan) Branch, Isfahan, Iran
مراجع و منابع این مقاله:
لیست زیر مراجع و منابع استفاده شده در این مقاله 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 مقاله لینک شده اند :