Co-Teaching in EFL Classroom: The Promising Model
Bibliographic record
Abstract
The research aimed to examine whether co-teaching in EFL classrooms could have positive impacts on students’ learning outcomes and their overall academic performance, including the improvement of the four language skills (listening, speaking, reading and writing). The experiment of the study was conducted throughout the summer course of 2018 for six weeks at the College of Basic Education with a class of 24 female students. The classes were held every day for one hour and twenty minutes. A simultaneous comparison between two classrooms was conducted in which one class was taught by a single instructor (the control group), and the other class was based on co-teaching (the experimental group). The two groups were taught by Khalifa AlKhalifa and Dalal Boland who acted as “one brain in two bodies” in their EFL classroom. Numerous sittings took place before each class to discuss how the lesson was to be divided between them and to reach an agreement on several matters, such as which instructor would deliver the lesson, which activities were to be solved, and how the second instructor would be beneficial in providing support and assistance to students throughout the entire class period. Moreover, both instructors established goals and objectives for every lesson and made sure that students meet those objectives by the end of every class period. Well-established plans and ideas on how to grasp those targets were agreed upon throughout the implementation of different materials to cover the content of the syllabus. After the summer semester came to an end and when the class average of both classes was compared, the results proved that the students who were in a co-taught classroom showed a significant improvement in their academic performance, whereas students who were taught solely by one instructor showed less improvement in their overall academic skills. This shows that well-planned co-teaching programs could lead to better student support within classroom settings, which consequently leads to improved EFL learning.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".