Bibliographic record
Abstract
Speaking ability is one of the major skills of English learning that is difficult to deal with and needs much attention and specific care.Since most of the students' needs and difficulties are treated by their teacher, it seems beyond the means of an only teacher to investigate all problems and deficiencies, and find proper solution for them.Besides the only teacher has limited knowledge and resources to deal with all upcoming difficulties, and when it is done, one cannot monitor his/her own actions towards the sufficiency of it.Accordingly, the purpose of this study was to see to what extent does the implication of the principles of critical friends' techniques, affect the speaking ability of Iranian intermediate EFL learners.Therefore, in study quasi-experimental study that used a pretest, treatment (critical friends' principles), and post-test, there was one control group (N= 25), and one experimental group (N=28) with both male and female young adult learners.The SPSS software was used to compute and analyze the amount of the treatments impact, and the independent t-test built up the core statistical analyses of the study.During the treatment phase, the principles of critical friends were implemented in order to have its results affect the students' learning, specifically their speaking ability which was the focus of the study.The findings of this study showed a significant difference between the experimental and control groups, proving the positive effect of using critical friends on improving students' speaking skills.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.935 | 0.942 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".