The Use of the Communicative Language Teaching Approach to Improve Students’ Oral Skills
Bibliographic record
Abstract
The purpose of this study is to determine the use of the Communicative Language Teaching approach in the English classroom and the strategies and resources used by the teachers to improve students’ oral skills. The participants were 6 English teachers and 105 students enrolled in the 2nd, 3rd, and 4th grades at a public elementary school in the city of Loja, located at the southern part of Ecuador. A mixed method approach was applied in this study. In order to collect the data, a questionnaire was given to the English teachers and class observations were carried out. The results obtained throughout this study reveal that modeling, repetition, pair and group work are the main strategies used by teachers to help students develop communicative competences. These strategies were frequently used but still not enough to promote active participation during classes. It is important to highlight that there is a variety of strategies besides the ones previously mentioned that can be incorporated to offer students more opportunities to orally produce the language. Additionally, teachers provide different kinds of feedback such as metalinguistic feedback and elicitation as a way to help students improve their oral skills.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".