Flipped Classroom as a Supporting Plan for Iranian EFL Learners’ English Improvement in Super Intensive Courses
Bibliographic Data
| ID | 21807226 |
|---|---|
| Authors | Mustapha Hajebi (Islamic Azad University Bandar Abbas, corresponding author) |
| Year | 2020 |
| Volume | 10 |
| Issue | 9 |
| Pages | 1101 |
| Publication date | 2020-09-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Theory and Practice in Language Studies (JOURNAL) |
| Journal identifiers | ISSN: 1799-2591 • E-ISSN: 2053-0692 |
| Publisher | Academy Publication (PUBLISHER • GB) |
| DOI | 10.17507/tpls.1009.13 |
| OpenAlex | W3082027643 |
| Language | EN |
| Citations received | 2 |
| References cited | 6 |
The present study sought to investigate the effectiveness of flipped classroom as a supporting plan for Iranian EFL learners’ English improvement in super intensive courses. The participants included a sample of 40 students from Accent English language institute of Bandar Abbas, Iran, then divided into two experimental and control groups randomly. The dependent variable was English improvement and independent variable was watching and learning by films that gathered by Hajebi (2020). This study took in 30 sessions and involved treatment, pre-test, post-test and random assignment that it was in line with true experimental design, so the design of the current study was quantitative design. To analyze the data the frequencies and percentage of each item in the questionnaires computed with the aid of SPSS. The findings indicated that not only did flipped model of instruction improve students’ English performance but also it improved their overall attitudes and beliefs towards it and boosted students’ motivation and learning. Furthermore, this study may offer some implications for language teaching and learning
English language · Flipped Classroom · Mathematics education · Medical education · Quasi-experiment · Computer Science · Innovative Teaching Methods · Medicine · Online and Blended Learning · Psychology · Technology-Enhanced Education Studies · Artificial Intelligence
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| Citations per year | 0.67 |
|---|---|
| Citation span | 2023 - 2025 (3) |
| Highly cited | No |