A Comparison of Vocabulary Learning Strategies of Iranian EFL University Students: Repeating versus Cooperating with Peers
Bibliographic record
Abstract
Vocabulary learning and assessment are considered as the key basis for the training of English as a foreign language. However, it is time-consuming, uncertain and repetitious for the teachers to assess the proficiency of the students’ vocabulary storage. This paper reports the results of a study which aimed to investigate the effect of Repeating as a direct vocabulary learning strategy versus Cooperating with Peers as an indirect vocabulary learning strategy teaching on the improvement of word knowledge on reading comprehension skill of Iranian undergraduate students. In order to attain the aim of the research, a vocabulary test was administrated to one hundred and forty-six male and female pre-intermediate EFL university students. Ultimately, seventy-eight pre-intermediate language learners were elected and appointed into two experimental groups (A and B) based on a vocabulary pre-test. The group (A) was taught vocabulary through Using Repeating vocabulary learning strategy and the group (B) was taught Cooperating with Peers vocabulary learning strategy for the aim of improving their lexical knowledge in reading comprehension skill. In the end of the treatment period, another vocabulary test (post-test) was implemented to all the students of two groups. After analyzing the data of the study that administered through using Independent samples t-test statistics, the results showed that there was a considerable difference between the two experimental groups under analysis in terms of their vocabulary improvements. The outcomes revealed that Repeating as a direct vocabulary learning strategy can cause to higher accomplishments of word storage in reading comprehension skill of Iranian pre-intermediate EFL undergraduate learners.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".