On the Effects of Focus on Form, Focus on Meaning, and Focus on Forms on Learners’ Vocabulary Learning in ESP Context
Bibliographic record
Abstract
This study investigated the effectiveness of three kinds of vocabulary instruction. Seventy learners in the classes of English for Specific Purposes (ESP) were divided into three different groups receiving different instructions: Focus on Form Instruction (FoF) (Dictogloss task), Focus on Meaning Instruction (FoM) (Reading and Discussion task), and Focus on Forms (FoFs) Instruction (Word lists). The first two groups were experimental groups, and the last group was control group. The results of this research indicated that learners in FoF group achieved significantly higher scores than those in FoM and FoFs. Also, learners’ scores in FoM group were significantly higher than FoFs group. These findings were justified by main features of FoF tasks (dictogloss) including depth of processing hypothesis, discovery learning, pushed output, noticing hypothesis, awareness raising, negotiation, collaboration, and motivation.
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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 | 0.002 | 0.012 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".