The Role of Small-Group Discussions in the Enhancement of Iraqi EFL Learners' Speaking Skills
Bibliographic record
Abstract
Aims: The study seeks to investigate the impact of Small-Group Discussions on improving Iraqi University students' speaking proficiency in English as a Foreign Language (EFL). This includes examining the communication between Iraqi students and their interactions with native English-speaking students and students from the UK and Canada. The Iraqi students now acquiring English language proficiency still require more development in their oral communication abilities.Methodology: Pre-test and post-test measures were employed to collect the data. A quantitative data analysis method is implemented. Small group discussion is a learning process in the classroom consisting of two or more students who interact with each other, where each group member can express their ideas. In a small group discussion, students must combine their different ideas with those of other students in the same group to understand the text well.Results: The results from the three hypotheses revealed a significant difference from which we can conclude that the learning of the speaking skills by small group discussions may create a comfortable and safe speaking environment. The study recommends That teachers employ this method and actively motivate their pupils to engage in these groups.Conclusions: The study concluded with significant results that proved that interaction with peers who speak Arabic as their mother tongue can create a useful, safe and comfortable environment for speaking, and that interaction with native English speakers can benefit students by getting to know different English dialects as spoken by native speakers.
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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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".