The Influence of Using Word forks on Developing Collocative Competence of Intermediate Iranian EFL Learners
Bibliographic record
Abstract
One of the most problematic areas of learning English as a foreign or second language is learning phrasal verbs (PVs) in collocation with certain nouns. The present study was designed to test a procedure called the word fork technique to help intermediate EFL students to develop their collocative competence in using PVs. A group of 30 intermediate Iranian EFL students were randomly selected. They were given a pre – test and a post – test each in two phases. In order to check the efficacy of using the word fork technique in developing the participants' collocative competence in using PVs they were required to devote a time period of about 15 to 20 minutes of each class session practicing PVs, using the newly developed technique. This lasted for 20 session. Based on the data obtained, it can be concluded that the new technique can efficiently help the target population to improve their collocative competence in using PVs in specific and their communicative ability in English in general.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 teacher head, 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".