Exploring Flipped Classrooms in EFL Teaching: A Comprehensive Systematic Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The flipped classroom model has gained significant attention as an innovative pedagogical approach to teaching English as a Foreign Language (EFL). This method promotes active learning, student engagement, and improved language proficiency by shifting content delivery to pre-class activities and dedicating class time to interactive and collaborative tasks. This systematic review synthesizes findings from seven peer-reviewed studies published between 2016 and 2024, selected through a PRISMA-guided search of ERIC, ScienceDirect, and Google Scholar databases. The analysis highlights the flipped classroom’s effectiveness in enhancing EFL learners’ speaking, listening, and reading skills, fostering autonomy, and reducing language learning anxiety. Despite its benefits, challenges remain, including technological disparities, variations in student readiness, and insufficient teacher training. The review underscores the need for tailored professional development, equitable access to digital resources, and adaptive strategies to address these obstacles. Additionally, cultural and contextual factors significantly influence the model’s success, necessitating further exploration to optimize implementation in diverse educational settings. This systematic review contributes to the growing body of research on flipped classrooms, providing insights for educators and policymakers to enhance the efficacy of this approach. By addressing identified challenges and leveraging their advantages, the flipped classroom model offers a promising avenue for transforming EFL education and meeting the demands of 21st-century learners in a globalized world.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it