Teacher Professional Development: EFL Teachers’ Experiences in the Republic of Benin
Bibliographic record
Abstract
Using a survey, this study examines EFL teachers’ views on professional development, the models of teacher development they are familiar with, and their experiences in the area. The study also inquires into the teachers’ knowledge and opinions about inquiry-based teaching. The results indicate that though the EFL teachers often have the opportunity to participate in teacher development activities, these activities do not enable them to develop the skill of reflection and action on practice as they are patterned on top-down models of teacher development and happen in a one-shot workshop-style. Other teacher development activities such as action-research, reading research findings in the field, peer observation, mentoring, or teacher networking are unfamiliar to them. While the participant EFL teachers acknowledged that the top-down teacher development activities give them exposure to informative input, they also reported that such activities, paradoxically, have little impact on their teaching and students’ learning. Most of them acknowledged having very little knowledge of teacher development activities that involve self-intiative and autonomy, and they expressed interest in learning about and trying action-research in their 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".