Conceptualizing Communicative Language Teaching (CLT) in the EFL Context: Ethnographic Experiences of CELTA and Non-CELTA Holders
Bibliographic record
Abstract
Communicative language teaching (CLT) has become the favourite teaching approach of many English teachers because of its focus on communication (Kumaravadivelu, 2006). A number of researchers have investigated EFL teachers' perceptions and implementation of CLT in Saudi tertiary level education. Some researchers reported on how CELTA training affects EFL teachers' perceptions and implementation of CLT. However, there is a gap in the literature with regard to the lived experiences of how non-native English speaker teachers (NNESTs) who do or do not have a CELTA qualification understand and apply CLT in Saudi tertiary level EFL education. Therefore, this mixed-methods ethnographic research focuses on filling this gap. Data were collected through three research tools, namely a survey, vignettes and classroom observations. All the participants were teaching EFL at the Saudi tertiary level. Twenty-six CELTA holders and forty-four non-CELTA holders participated in the survey about their perceptions and implementation of CLT. Four CELTA holders and three non-CELTA holders wrote a number of vignettes on how they conceptualize and apply CLT. Classroom observations were conducted for two CELTA holders and two non-CELTA holders. The statistical survey data were analysed using SPSS, and the vignettes and classroom observations were examined thematically. The findings revealed that both CELTA and non-CELTA holders have a reasonable understanding of CLT. However, they also showed that the teachers only implement CLT to some extent, suggesting that more training on applying communicative activities and group- and pairwork is needed in EFL classrooms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".